Soaring jet fuel prices exceeding $200 per barrel, flight cancellations, chronic geopolitical instability… In 2026, the tourism sector faces unprecedented unpredictability.

Amid these upheavals, the customer journey is becoming increasingly complex, and customer service teams are regularly overwhelmed. Yet it is precisely during these moments of stress that your travelers’ loyalty is put to the test. In this context, Artificial Intelligence is no longer just a lifeline: it is a unique opportunity to regain control, reassure your teams, and turn the unexpected into a competitive advantage.

How does AI help manage this operational complexity while meeting new demands for hyper-personalization? An in-depth look.

1. The 2026 Traveler: Autonomous, Demanding, and AI-Assisted

The era of traditional keyword-based search is coming to an end. Today, AI has emerged as the traveler’s primary entry point.

The shift to conversational queries

Travelers no longer search; they “converse.” According to a recent global report by Expedia Group, 50% of travelersnow say they are ready to use generative AI to plan their trips (Expedia Unpack Report). AI has become a true personal assistant capable of handling complex queries in natural language.

Hyper-personalization is becoming the standard

This technological transition comes with a requirement: the end of standardized tourism. Recommendations must be dynamic and adapt to the context (weather, budget, preferences). 

In practice, this hyper-personalization translates into frictionless customer service and support journeys. When a traveler asks, for example, to modify a complex reservation involving several family members with different baggage options, AI no longer directs them to a generic form. Connected to the CRM, it immediately recognizes the customer’s loyalty status, analyzes the file history, and instantly offers viable, personalized flight alternatives, directly in the chat window.

2. Managing the unexpected: AI as an “operational shield”

While AI may seem like a dream scenario upfront, it is in crisis and contingency management that it reveals its true ROIand protects your brand image.

The surge in customer service requests

Given the complexity of passenger rights, even the slightest geopolitical or weather-related crisis generates thousands of repetitive questions. These requests for refunds or explanations regarding fuel surcharges cause wait times to skyrocket, exhausting both customers and agents.

The bot as a line of defense and a tool for reassurance

Deploying an intelligent callbot or chatbot creates a true operational “shield”. AI absorbs massive spikes in activity, immediately reassures the customer with its 24/7 availability, and helps teams stay afloat.

The impact of such a system is decisive in a crisis. Imagine a sudden airspace closure leading to a cascade of flight cancellations. Instead of letting travelers overwhelm the call center, the chatbot proactively takes over. On the website or via WhatsApp, it informs affected travelers, displays available alternative flights, and automatically initiates the refund process. Phone lines are thus reserved for extreme emergencies.

3. Chatbots & Callbots: The Pillars of the Customer Experience

While chatbots scripted using decision trees remain excellent tools for guiding users through simple, well-defined paths, the contribution of conversational AI (NLU) now allows us to go much further by understanding the user’s true intent, even when their request is phrased vaguely or complexly.

Key benefits for your performance

• 24/7 availability: Immediate response, eliminating frustration caused by time zones.
• Handling of traffic spikes: Infinite scalability during service disruption announcements.
• Reduction in operational costs: Automation of low-value-added tasks (FAQs, certificates).
• Improved satisfaction (CSAT): Clear information, delivered when the customer needs it most.

In practice, when a customer asks, “Can I reschedule my dates for next week because of the strike?”, the AI-powered bot understands the exact intent. It retrieves the information from the booking system, checks the cancellation terms associated with the booking, and immediately suggests alternative dates directly within the interface, with no wait time, thereby improving the customer experience.

4. Automate without dehumanizing: the perfect balance

Hospitality is, above all, a human endeavor. Unlike public AI systems that sometimes suffer from “hallucinations” (outdated or fabricated information), tourism professionals must guarantee absolute reliability.

Escalation to an agent: safeguarding the customer relationship

The success of an AI project in 2026 depends on the partnership between machines and humans, turning your advisors into augmented agents. Automation does not replace hospitality; it protects it. The bot handles high-volume tasks (FAQs, schedules, simple procedures) to free up your advisors’ time so they can focus on their true calling: empathy and personalized service.

This synergy is particularly evident in critical situations. When a customer stuck at a customs checkpoint abroad contacts their agency via the chatbot, the conversational engine instantly detects the sense of urgency based on the vocabulary used. It pauses the automation and immediately escalates the conversation to a human agent via Livechat. The agent then receives the complete history, already pre-qualified by the bot, to intervene and resolve the issue without making the customer repeat their problem.

Anticipate to excel

Artificial Intelligence has become the essential standard in tourism by 2026. Whether it’s offering ultra-personalized support during the purchase process or using a chatbot as a buffer during peak call volumes, mastering conversational AI is your best driver of growth and resilience. Don’t let crises overwhelm you—take back control of your customer relationships.

Discover how our chatbot and callbot solutions can transform your customer service! Request a demo.

Summary

• The AI Act, the first comprehensive European regulation on artificial intelligence, enters the phase of full implementation in 2026.
• This year marks a turning point for businesses using AI systems, particularly for “high-risk” models and generative AI. This article analyzes the concrete obligations, compliance issues, and impacts on innovation, as well as the limitations and challenges related to AI governance within the European framework.

What is the AI Act and why is 2026 crucial?

The Artificial Intelligence Act was adopted in August 2024 to regulate AI in Europe. It is distinguished by its risk-based approach, defining specific obligations based on the system’s criticality:

• AI with unacceptable risk: prohibited (e.g., invasive social scoring).
• High-risk AI: subject to documentation, audits, and human oversight.
• Low-risk AI: obligations limited to transparency.

While certain bans have been in effect since 2025, 2026 will be the year when operational obligations become fully enforceable: controls, audits, mandatory documentation for critical systems, and potential penalties for non-compliance. (digital-strategy.ec.europa.eu, commission.europa.eu).

The text did not take effect overnight. As the European Commission explains:

• August 1, 2024: official entry into force of the text.
• February 2, 2025: ban on certain practices deemed “unacceptable.”
• August 2, 2025: obligations regarding so-called “GPAI ” (General-Purpose AI), such as large language models and other versatile systems.
• August 2, 2026: Major implementation of transparency rules and obligations for high-risk AI systems.
• August 2, 2027: Specific obligations for AI systems already integrated into products (automotive, medical devices, etc.).

Practical implementation in 2026?

1. High-risk systems under supervision

All AI systems impacting sensitive decisions (recruitment, credit, healthcare, justice, critical infrastructure) must comply with:

• Continuous human supervision
• Complete documentation of data and models
• Risk management and auditability
• Traceability and reporting to the competent authorities (europarl.europa.eu)

2. Transparency and Generative AI

So-called “GPAI” models (e.g., advanced chatbots, AI agents…). The term GPAI (General Purpose AI) refers to versatile artificial intelligence systems capable of performing a wide variety of tasks without being limited to a specific use. These models must:

• inform users that they are interacting with an AI,
• indicate when content is automatically generated,
• provide summaries of training data and system limitations (digital-strategy.ec.europa.eu).

3. Penalties and Oversight

Non-compliant companies face:

• Fines of up to 7% of global revenue,
• administrative penalties for inaccurate declarations (luxembourg.representation.ec.europa.eu).

4. Global Impact

Even outside Europe, any AI used on the European market or affecting EU citizens must comply with the law.

Conclusion: 2026, the year of regulated and responsible AI

The year 2026 marks the implementation of the AI Act:

• Concrete obligations and audits,
• Enforcement and penalties,
• Strict governance of critical systems.

Companies must act now to ensure compliance and leverage this framework to strengthen trust and innovation.

At Dydu, we are committed to ensuring our solutions fully comply with current standards. Our platforms guarantee:

• integrated human supervision,
• complete traceability of AI interactions and decisions,
• data security and compliance,
• detailed documentation of the models used.

Thus, Dydu enables companies to deploy high-performance, secure, and compliant conversational assistants.

Ready to see how a secure, compliant French chatbot can transform your customer interactions? Request a demo.

Abstract

• Hyper-personalization applied to conversational AI is profoundly transforming the way users interact with digital systems. Thanks to advances in generative AI, machine learning, and autonomous agents, chatbots and intelligent assistants are now able to adapt their responses in real time according to the context, history, and preferences of each individual.

This article analyzes the mechanisms of conversational hyper-personalization, its concrete benefits for the user experience, and the ethical and regulatory limitations it raises for 2026.

What is hyper-personalization in conversational AI?

Among the major trends expected in 2026 in the field of AI is hyper-personalization. What does this mean in concrete terms? Hyper-personalization applied to conversational AI refers to the ability of a conversational agent to adapt its responses in a subtle and dynamic way to each user, taking into account their context, interaction history, and explicit or implicit behavioral signals. Unlike traditional personalization, which is often limited to segmentation by profile or predefined rules, hyper-personalization relies on artificial intelligence models capable of producing unique, contextualized responses that evolve over the course of the dialogue.

In the context of modern conversational AI, this approach relies primarily on generative AI, and in particular on large language models (LLMs). Building on the proven success of conversational chatbots, hyper-personalization enables more natural interaction, closer to human exchange. The conversational agent no longer simply responds to an isolated query: it interprets the user’s intention and adjusts the tone, level of detail, and sometimes even the response strategy based on the overall context of the conversation.

Hyper-personalization is also distinguished by its temporal dimension. It is not static, but scalable. Each interaction enriches the system’s understanding of the user, making subsequent exchanges potentially more relevant. This conversational continuity transforms AI into a truly intelligent intermediary, capable of supporting the user over time, whether in a customer support, personal assistance, or information mediation context.

How does conversational hyper-personalization work?

Conversational hyper-personalization relies on a few key mechanisms that enable AI to adapt its responses in real time while maintaining a consistent and relevant interaction.

The main technological levers

• Contextual data
• AI relies on information such as conversation history, the channel used, the time of the exchange, and the preferences expressed by the user.
• The goal is to place each interaction in its context, rather than treating requests in isolation.
• Language models and machine learning
• Thanks to machine learning and generative AI, the conversational agent continuously adjusts its responses: content, tone, level of detail, and proactivity can evolve depending on the situation and user profile.
• Controlled conversational memory
• The most advanced systems incorporate a supervised memory, allowing them to retain certain key elements from previous exchanges.
• This reinforces the continuity of the dialogue and the feeling of personalization, without any loss of consistency.
• More autonomous conversational agents
• Hyper-personalization is increasingly part of a logic of agents capable of anticipating certain needs, suggesting actions, or proactively supporting the user, without explicit intervention at each stage.

In the era of agent-based AI, the more autonomous conversational agents become, the more crucial it is to master the challenges associated with transparency in order to deploy sustainable hyper-personalization that is accepted by users.

Concrete use cases for conversational hyper-personalization.

Hyper-personalization in conversational AI is gradually spreading into operational use cases, particularly in the areas of customer relations, financial services, and consumer digital assistants.

In the banking and insurance sectors, conversational hyper-personalization makes it possible to orchestrate sensitive interactions around complex data. AI agents can guide customers in understanding financial products, flag inconsistencies, or anticipate needs (for example, when a customer’s situation changes). The main challenge is not only efficiency, but the ability to build trust in exchanges with high emotional or regulatory value.

Commerce and service platforms also exploit this logic through so-called “concierge” agents. These conversational AIs offer personalized recommendations, take past preferences into account, and adapt their language to the detected intention (exploration, hesitation, decision). Unlike traditional recommendation engines, the added value lies in the dialogue: the user can refine their expectations in real time, and the AI gradually adjusts its proposals.

Finally, consumer digital assistants are evolving towards more continuous and contextual interactions. Hyper-personalization is no longer limited to recognizing a voice or user account, but aims to understand habits, implicit preferences, and recurring usage contexts. This evolution brings conversational AI closer to the role of a personal assistant, capable of anticipating certain requests without explicit intervention.

Challenges, limitations, and risks of conversational hyper-personalization

While conversational hyper-personalization opens up significant opportunities in terms of user experience, it also raises critical ethical, psychological, and regulatory issues. The first risk frequently identified is that of personalization being perceived as intrusive. AI that seems to “know too much” about the user can generate a feeling of unease, sometimes referred to as the creepy effect, which can undermine trust rather than reinforce it.

The issue of data is central. The effectiveness of hyper-personalization relies on the use of personal information, whether explicit or inferred.

Without a clear framework for consent, transparency, and limitations on use, these practices can conflict with regulatory requirements, particularly in terms of data protection and AI governance. In the European context, the link between the GDPR and new regulations on AI requires increased vigilance in the design of conversational systems.

Another issue concerns biases and reinforcement effects. Without a control mechanism, hyper-personalized AI can lock users into repetitive patterns, whether in terms of recommendations, tone, or content offered. In a conversational context, these biases are all the more sensitive because they occur in an exchange that is perceived as “human,” which can reinforce their impact.

Finally, hyper-personalization raises the question of responsibility and understanding of the decisions made by AI. The more autonomous and adaptive a conversational agent becomes, the more difficult it is to explain precisely why a specific response or recommendation was made. This opacity can be a barrier to adoption, particularly in sectors where traceability and explainability are essential.

Thus, the major challenge for the coming years is not only to make conversational AI more personalized, but to design hyper-personalization that is controlled, understandable, and acceptable to users.

Conclusion: Towards responsible conversational hyper-personalization

Hyper-personalization in conversational AI is transforming the way users interact with digital services. By making exchanges more contextual and adaptive, it improves relevance and engagement, provided it is deployed with transparency and data control.

The challenge is no longer just technological, but strategic: offering truly useful conversations without crossing the line into intrusion.

Would you like to see how conversational AI can be hyper-personalized in practice? Request a demo.

Summary

• AI agents, or agentic AI, represent the new generation of artificial intelligence. Capable of planning, deciding, and acting autonomously, they enrich the conversational experience and automate complex tasks. While global giants (Salesforce, AWS, n8n, Google, etc.) are accelerating their efforts in this area, France is seeking to position itself between innovation, sovereignty, and responsibility.

What is an AI agent and how can it be defined in concrete terms?

The AI agent, also known as agentic AI, marks a new stage in the evolution of artificial intelligence. An AI agent is capable of planning, deciding, and acting autonomously, adapting to its environment and the user’s needs.

From text generation to autonomous action

An AI agent no longer just generates content: it takes action.

Specifically, it can:

• understand an overall objective (e.g., “organize a customer webinar”);
• develop a multi-step strategy (book a room, send invitations, prepare a presentation);
• mobilize external tools (APIs, messaging, CRM) to execute these actions;
• and adjust in real time based on the results obtained or user feedback.

The rapid evolution of AI: from chatbots to autonomous agents

Here’s how the transition to this new era took place:

This diagram illustrates the evolution of artificial intelligence, from its beginnings to the new era of agentic AI. In 2017, simple AI relied mainly on traditional chatbots operating according to predefined scenarios. The year 2022 marked a turning point with the emergence of generative AI, capable of classifying documents and emails, generating personalized responses, summarizing conversations, and even predicting certain behaviors. In 2025, we entered the era of agentic AI, where systems orchestrate multiple intelligent agents, make decisions, and act autonomously, offering a completely redesigned, more fluid, proactive, and personalized customer experience.

Why does the definition of agentic AI remain unclear according to experts?

Defining agentic AI is no simple task, and that is precisely what makes it such a fascinating subject.

There is no official consensus: each technology player has its own interpretation.

Multiple visions depending on the player

• IBM describes AI agents as “systems capable of acting autonomously in a given environment to achieve a specific goal.”
• AWS refers to “contextual AI capable of reasoning and using tools to perform complex tasks without direct human supervision.”
• Red Hat emphasizes the collaborative dimension: “cooperative agents” capable of communicating with each other and interacting with business software.

These nuances show that the term “AI agent” covers both a technical and philosophical approach: to what extent can and should we delegate decisions to a machine?

A still-evolving concept

Agentic AI is currently more of a horizon than an established category.

It refers to a set of converging technologies (LLM, API, automation tools, decision engines) that are moving toward a common goal: giving AI the ability to take initiative.

Some experts even prefer to talk about “orchestrating AI”: not an all-powerful AI, but a system capable of coordinating several specialized intelligences.

This approach seems the most realistic and promising in the short term.

This capability is based on a continuous learning cycle often summarized in four steps:

AI agent cycle:

Perceive (analyze the situation or request)

Reason (identify the objective, plan the steps)

Act (execute the necessary action(s) via tools/APIs)

Learn (adjust its strategy based on the result or user feedback)

In other words, an AI agent “sees,” “thinks,” “acts,” and “learns.”

Thus, according to Dydu, agentic AI is not just an emerging technology: it is a logical evolution of intelligent assistance, paving the way for more fluid, proactive, and personalized user experiences, without ever relinquishing human control.

AI agents: how companies can take advantage of them without losing control

1. What opportunities do AI agents offer companies?

AI agents are ushering in a new era of intelligent automation: they plan, act, and adapt.

The benefits are numerous:

• Automation of multi-step tasks, such as planning, sending emails, generating reports, or customer follow-up.
• Time savings and operational efficiency, thanks to autonomous workflows capable of handling entire processes without human intervention.
• Increased personalization, taking into account context, history, and user preferences.
• Better use of internal data, made possible by API integrations and direct access to business tools (CRM, ERP, messaging, document databases).

Concrete examples:

• In e-commerce, an AI agent can automatically manage product returns and trigger the sending of a return label.
• In healthcare, it can coordinate appointments between multiple parties (patients, doctors, departments).
• In customer relations, it can anticipate needs: detect that a product is defective and offer a replacement without being asked.

3. What limitations and precautions should be considered?

Agentic AI is not without its challenges. Its rise raises major issues of control, security, responsibility, and ethics, which require a clear framework before any large-scale deployment.

• Human supervision and governance

The more autonomous an agent is, the more human supervision becomes essential. An agent may perform unvalidated actions or make rational decisions that lack discernment in complex or sensitive situations.

Beyond the legal question (“who is responsible in the event of an error?”), internal governance—rules of action, levels of validation, control mechanisms—is a key lever for limiting risks.

• Complexity and operational control

The proliferation of specialized agents increases the complexity of systems. Without clear orchestration rules, inconsistencies or conflicts of action may arise.

In addition, agents can place heavy demands on technical resources (APIs, data, workflows), making it essential to precisely control usage and costs.

• Security, compliance, and ethics

Data protection, decision traceability, and GDPR compliance remain fundamental requirements.

Even advanced language models can produce plausible but inaccurate responses. In an agentic environment, these errors can spread if they are not supervised. Finally, a technically optimal decision may not respect human intent, values, or implicit contextual constraints.

• In short, agentic AI should not be thought of as total automation, but as a system that is supervised, monitored, and aligned with clearly defined human, business, and ethical rules.

How does France compare to the rest of the world?

France is advancing at a steady pace, although it still lags behind the United States and China in terms of large-scale industrial deployment.

Solid strengths:

• According to the INPI, France ranks among the top 10 countries in the world for filing patents related to artificial intelligence.
• It has a recognized research ecosystem (Inria, CNRS, Paris-Saclay, Institut Prairie) and emerging champions such as Mistral AI, Hugging Face, LightOn, and Dust.

Obstacles to overcome:

• European regulations (AI Act) and the GDPR impose a strict framework on the transparency and traceability of automated decisions, which can slow down the deployment of fully autonomous agents.
• The lack of talent in AI and the slow adoption rate among SMEs remain areas of concern: according to France Digitale, less than one in two companies will have integrated advanced use of AI by 2025.

In summary, France is not lagging behind in research, but it needs to accelerate its operational adoption. Agentic AI could be a lever for transformation, provided that innovation is combined with a solid ethical framework.

What are the prospects for the evolution of agentic AI?

The global market for AI agents is estimated to be worth nearly $70 billion by 2030 (source: Gartner, 2025).

Two major trends are emerging for the coming years:

• Specialization: agents will become experts in a specific field (finance, healthcare, HR, e-commerce, etc.).
• Inter-agent collaboration: systems will be able to cooperate with each other to perform a common task, paving the way for true ecosystems of intelligent agents.

These prospects open up new horizons: proactive assistance agents, autonomous logistics flow management, predictive customer support, etc.

Conclusion: finding the right balance with agentic AI

Agentic AI is ushering in a new era for businesses: multi-step automation, proactive personalization, optimal data utilization, and more fluid interactions with customers. But this increased autonomy comes with major challenges: essential human supervision, shared responsibility, security, GDPR compliance, and ethical risks. Some complex or sensitive decisions still require human intuition and discernment, highlighting the importance of keeping control over agents.

The rise of AI agents does not signal the end of human intervention, but its transformation. By automating repetitive or operational tasks, agents allow teams to focus on complex situations, human relations, management, and decision-making.

New roles are emerging around the supervision, governance, and optimization of AI systems, placing humans at the heart of the value chain.

At Dydu, we design solutions that allow you to take full advantage of AI agents while maintaining the necessary control and security. Our modular and interoperable platforms facilitate the integration of autonomous agents into your processes, for smarter, more efficient, and more responsible interactions.

Discover our bots and the evolution of intelligent agents through Dydu solutions!

Summary

• Dydu has been recognized by Klein Blue Partners as one of the 100 startups to watch in AI & Insurance, in the Customer Relations category.
• This distinction highlights more than 16 years of expertise in designing conversational agents that are still serving insurers today.
• Our mission: to streamline customer relations, enhance the human touch, and support the digital transformation of a rapidly evolving sector.

Why is this recognition particularly significant for Dydu?

We are honored to be included in Klein Blue Partners‘ 2025 overview of the 100 startups to watch in AI & Insurance, in the Customer Relations category.

This ranking highlights companies that are structuring and energizing the artificial intelligence ecosystem as it applies to the insurance world. Klein Blue notes in particular:

• Rapid growth of AI solutions in the sector,
• The rise of SaaS and API-first approaches,
• A strong focus on co-pilots and conversational assistants, which have become strategic levers for efficiency and customer satisfaction.

For Dydu, this recognition has a special resonance.

For more than 16 years, whether in the context of customer relations or employee relations, we have been putting our expertise at the service of major players in the sector such as CNP Assurance, Groupe Pasteur Mutualité, and MSA Santé Famille Retraite Services. To help them streamline their internal communications, simplify the customer journey, and free up time for advisors and support teams to focus on what matters most: human relationships. Being cited in this study confirms that our vision of useful, ethical AI focused on the customer experience is in line with the challenges facing the sector.ith the challenges facing the sector.

Conversational AI: at the heart of a reinvented customer experience in insurance

With increasing digitalization, policyholders’ expectations are changing rapidly. They are looking for services that are available at any time, simple, fast, and personalized, whether it’s to track a claim, obtain a certificate, or modify a contract.

In this context, conversational AI, whether in the form of chatbots or callbots, meets these new requirements. It facilitates the comparison of online offers and provides immediate answers. This includes the most complex requests, such as tracking a health reimbursement claim, managing a claim involving several parties, or simulating compensation in the event of a contingency.

For example, a callbot can handle an insured person reporting a car accident: it identifies the contract number, collects initial information (type of damage, circumstances, location), and then automatically directs the call to the right department or an available advisor to finalize the claim.

This allows insurers to rethink customer relations, offering closer communication, greater responsiveness, and services tailored to the modern lifestyles of policyholders.

How do conversational AI solutions optimize customer relations in insurance?

At Dydu, our insurance chatbots combine intelligent automation and human support to meet the real needs of policyholders, thanks in particular to our live chat escalation option, which allows users to be redirected to an advisor in complex situations.

This complementarity between AI and humans guarantees a smooth, responsive, and personalized experience at every stage of the policyholder’s journey. Our chatbots and callbots, available 24/7, handle recurring requests: simple claims, issuing certificates, tracking reimbursements, or checking coverage. This allows advisors to focus on listening, empathy, and advice for situations that require it.

The concrete benefits:

• Efficiency and performance: On average, 30 to 40% of conversations are handled entirely by the bot, which helps reduce congestion in traditional channels and frees up time for advisors to focus on listening, advising, and building trust with policyholders.
• Customization and integration: our solutions adapt to business tools (CRM, CMS, extranet, etc.), offering a consistent experience and a satisfaction rate of over 85% for users.
• Multi-channel availability: website, apps, instant messaging, or social media.
• Security and compliance: data hosted in France, GDPR compliance, robust encryption protocol, health data hosting possible (HDS).
• Simplicity and support: no-code back office and dedicated contact person for smooth, customized deployment.

The result: a more responsive and personalized customer relationship, while optimizing the operational efficiency of teams.

Conclusion: A shared dynamic in the AI & Insurance ecosystem

Being named one of the 100 AI & Insurance startups to watch by Klein Blue Partners is more than an honor: it is recognition of the meaning we give to innovation.

In a constantly evolving ecosystem, Dydu continues to assert its identity: conversational AI at the service of human relationships. We warmly thank Klein Blue Partners for this recognition, as well as our customers and partners for their continued trust.

Discover how our insurance chatbots make customer relations smoother, more human, and more intelligent.

Summary

• On August 14, 2025, OpenAI unveiled GPT-5, presented as a major advance in generative AI. What does it promise? More sophisticated reasoning, truly native multimodality (text, image, audio), reduced hallucinations, and enhanced energy efficiency. But beyond its technical prowess, GPT-5 is already sparking debate and criticism: its limitations persist, the risks of misinformation remain, and questions of digital sovereignty are intensifying.
• For conversational AI, this launch marks a turning point: GPT-5 paves the way for more fluid and personalized uses, while raising the question of autonomous agents capable of performing complex tasks or making decisions.

What are the major new features of GPT-5?

With GPT-5, OpenAI is seeking to reach a new level of maturity in language models. Several technical developments are particularly noteworthy.

• Enhanced reasoning: GPT-5 follows complex instructions more accurately thanks to a hybrid architecture. Several models (fast, deep reasoning, etc.) are connected to a router, which is able to automatically choose the best approach based on the query.
• Native multimodality: GPT-5 now understands and generates text, images, and audio in a fluid and integrated manner. In previous versions, this capability already existed, but in the form of extensions: the core of the model remained textual, and image or sound modules were added separately.

With GPT-5, these different modes are merged from the outset, offering a more natural and unified experience, for example, analyzing an image while generating a coherent verbal explanation or creating an illustrated report from a simple text instruction.

• Reduced hallucinations: according to Vectara, GPT-5 has an error rate of only 1.4%, a record for an LLM.
• Configurable personalities: four response styles to choose from, adapted to the context of use.
• Energy optimization: a notable effort has been made to generate “useful tokens,” although some users regret that the tone is colder than that of GPT-4.
• First steps toward agentic capabilities: GPT-5 can already chain tasks, make certain decisions, and execute actions more autonomously, paving the way for future intelligent agents.

For example, the model can:

• Plan a series of steps to respond to a complex request,
• Retrieve information from a document or authorized website,
• Generate a report and send it by email via API integration.
• These functions are still limited, but they foreshadow the arrival of truly autonomous agents, capable of acting in a digital environment while complying with rules defined by the company.

What limitations and risks remain?

Today, it is essential to understand the limitations of generative AI, and these limitations do not spare GPT-5. The new version of GPT can create text, images, code, and even sound. This power is impressive, but it also carries risks.

For example, GPT-5 can generate misleading content or deepfakes (falsified images or videos that appear real and can be misleading). This can be a problem for businesses, the media, or even in everyday life if such content is disseminated without verification.

Today, there is no perfect method for detecting all misleading content generated by AI. To regulate its use, several rules have been put in place: in France, the SREN law; in Europe, the Digital Services Act (DSA); and international initiatives such as C2PA, which seek to clearly identify the origin of digital content. These rules help to make platforms and content creators more accountable, but they do not replace the active role of the user.

That is why education and vigilance remain essential. Understanding that content can be manipulated, learning to verify sources, and knowing how to detect the signs of a deepfake are essential reflexes for using GPT-5 safely. In a professional context, these precautions are particularly important for teams that use AI in customer relations or communication.

GPT-5 and the competitiveness of European companies

GPT-5 is a very powerful model, but its use also raises strategic questions for businesses, particularly in Europe.

• Dependence on American giants
• OpenAI, Google, and Anthropic remain the major players in large language models. This means that European companies using GPT-5 may become dependent on these providers for access to the technology and for updates.
• Local and specialized alternatives
• In France, companies such as Mistral AI are developing local models. These models may be more suitable for certain specific uses and for ensuring better control over data. Sometimes, smaller, specialized models are sufficient to meet specific needs, without requiring a gigantic model such as GPT-5.
• Sovereignty and regulation
• Europe is working to regulate AI with the AI Act, in order to protect users and data. The rules are different in the United States and China, creating a complex environment for European companies. The issue of digital sovereignty is therefore becoming central: it is not just a question of choosing a high-performance model, but also of ensuring control over data and compliance with local standards.

What impact will this have on work and conversational uses?

GPT-5 opens up new possibilities for human-machine interactions, but it does not transform everything overnight. Its role remains that of an augmentation tool rather than a replacement.

On the one hand, it can enrich customer support with more fluid dialogues, automate certain tasks, and further personalize responses. These developments offer real opportunities to improve customer relations and increase efficiency.

But limitations remain. The model continues to produce errors (“hallucinations”) and its logical reasoning is sometimes fragile. This means that human supervision remains essential to avoid inaccurate or inappropriate responses.

In terms of work, GPT-5 does not spell the end of existing jobs. As Mathieu Changeat, co-founder of Dydu, points out:

“LLMs are augmentation tools, not autonomous entities: they require reflection, strategy, critical thinking, etc.”

Finally, this development highlights the importance of training and AI literacy: understanding the model’s limitations, identifying its biases, and learning how to use it safely and effectively.

GPT-5, a breakthrough to be exploited methodically

GPT-5 represents a significant advance for conversational AI. Its enhanced reasoning capabilities, multimodality, and automation potential open up new opportunities to enrich customer relationships and optimize internal processes.

However, it is not a miracle solution. Limitations remain: residual hallucinations, the need for supervision, and the need for a clear strategy. Indeed, the AI of tomorrow will not rely solely on giant models such as GPT-5. It will tend towards more specialized, lightweight, and sustainable approaches, driven by Small and Medium Language Models, capable of combining performance, cost control, and energy efficiency. But today, human expertise remains central to ensuring the reliability of interactions and fully exploiting the potential of AI.

At Dydu, our approach combines technological power with a strategic framework: choosing the right model, personalizing interactions, human supervision, and team training to maximize value. This method ensures that GPT-5 becomes a real lever for the company, without creating excessive dependence on AI.

Discover now how our solutions can transform your customer interactions with GPT-5.

Summary:

• RCS (Rich Communication Services) messages are the successor to traditional SMS: they enrich exchanges with images, videos, carousels, interactive buttons, and read receipts, while remaining accessible directly from the native messaging app.
• This technology revolutionizes customer relations by making every interaction more engaging, fluid, and personalized. Companies can thus enhance the customer experience, improve satisfaction, and boost conversions through interactive and measurable messages.
• Thanks to Dydu’s RCS/SMS chatbots, it is possible to automate these exchanges, offer 24/7 support, and personalize each conversation according to the customer profile. In just a few clicks, your campaigns become intelligent, effective, and user-centered.

What exactly is RCS?

RCS (Rich Communication Services) is a mobile messaging protocol that enhances traditional SMS by adding rich and interactive features. These include media sharing, read and typing indicators, group chat, action buttons, and carousels.

Google has integrated RCS into its Messages app and promoted its global deployment. The goal is to offer a uniform, interactive, and integrated messaging service directly on compatible devices.

What is the difference between RCS and SMS?

SMS and RCS differ mainly in their level of interaction and customization. SMS is limited to text, while RCS enriches each message with images, videos, interactive buttons, or carousels. It also allows you to track the recipient’s reading and typing, and create dynamic group conversations.

In short: SMS informs, RCS engages.

To go further and reach all customers, even those whose phones are not RCS-compatible, a solution such as Time2Chat complements this approach.

Time2Chat: a complementary solution?

Not everyone has an RCS-compatible phone, so Time2Chat completes the equation, transforming traditional SMS into unlimited conversation for 24 hours:

• Simple conversational experience: start with an SMS, then enjoy free and unlimited exchanges for a 24-hour session.
• Universal channel: accessible to everyone, with no app or technical requirements.
• Immediate use: appointment confirmation, order tracking, after-sales service, notifications, quick surveys.

Real-life example: a customer receives a delivery notification → they reply to reschedule the delivery time > they ask the bot a question > all of this is possible within the same 24-hour session, with no technical barriers.

How does it integrate with Dydu?

This is where conversational AI comes into its own:

• The Dydu chatbot can be connected to Time2Chat to automate exchanges during the 24-hour window.
• The customer chats via text message as they would with a human advisor.
• The bot responds, provides information, suggests options, or directs the customer to an agent if necessary.

The result: the company benefits from a universal channel (SMS) enriched by conversational intelligence.

Why is RCS an opportunity for businesses?

This conversational channel improves customer relations by making each message attractive and measurable.

• Enriched experience: visuals, videos, clickable buttons, etc.
• Trust: verified and secure sender.
• Performance: detailed statistics (read rate, clicks).

Players such as Doctolib, Century 21, TheFork, and Skello are already using SMS 2.0 to improve the customer experience and increase their conversions.

RCS and conversational AI: what is the potential?

The combination of this advanced messaging mode and chatbots has opened up new opportunities for businesses. It improves communication while offering a seamless experience tailored to each user.

With this combination, you can:

• Automate customer service 24/7: instant answers to frequently asked questions and support throughout the process.
• Guide customers through their journey: buttons, carousels, and quick responses for making appointments, requesting information, or tracking orders.
• Integrate transactions directly into the conversation: confirmation, payment, and tracking, all in the same channel.

The benefits of SMS 2.0 coupled with chatbots apply to several specific situations, which we detail below.

What are the specific use cases for RCS chatbots?

RCS solutions transform a simple message into a true digital interaction. Depending on your industry, there are many benefits:

• Education & e-learning: exam reminders, important notifications, bot-based assistance for recurring questions, and enhanced platform authentication.
• Healthcare: appointment reminders, treatment notifications, post-consultation follow-up, and automated satisfaction surveys.
• Real estate: prospect qualification, property recommendations tailored to buyer profiles, appointment management, and integrated electronic signatures.
• Human resources: rapid distribution of targeted job offers, interview confirmations to reduce absenteeism, chatbot for frequently asked questions (vacation, payroll, scheduling).
• FoodTech & hospitality: reservation confirmations and reminders to limit no-shows, welcome or post-stay messages, orders and payments tracked directly via RCS.
• Retail & e-commerce: follow-up on abandoned shopping carts with tailored offers, interactive order tracking notifications, enhanced loyalty programs, and VIP invitations.

RCS chatbot: how does it work for your customers?

Your customers receive information directly in their Google Messages app on Android or, more recently, on iOS.

If the phone is not compatible, the message automatically reverts to a traditional SMS (fallback). With this technology, you can provide instant, targeted responses 24/7. The experience remains simple and natural, and strengthens customer engagement and satisfaction.

Now you know how RCS chatbots can improve the everyday customer experience, let’s see how your business can take action and easily launch its first RCS campaign.

How to launch an RCS campaign in your business?

Launching an RCS campaign is quick and easy:

1. RCS agent registration: your brand is validated by Google and operators to ensure security and identification.
2. Integration via API (smsmode): your RCS messages are connected to your existing systems to automate sending and tracking.
3. Automation and Dydu chatbot: configure your scenarios, automate responses, and track statistics in real time.

Request a Dydu demo to see how your company can launch its first RCS campaign effectively.

Do you need technical skills to launch an RCS chatbot?

No technical skills are required for your teams. Dydu and smsmode offer a turnkey solution, taking care of configuration, integration, and support. You will be trained on the Bot Management System (BMS), an intuitive and simple interface that allows you to manage the knowledge base, test responses, and track bot performance. The success of the bot depends above all on your business knowledge and user needs to provide the right answers and solutions, not on your technical skills.

RCS and CRM: how to connect enriched messaging to your internal tools?

RCS conversational AI integrates easily with your existing tools: CRM, calendars, e-commerce, customer service. Dydu offers connectors for platforms such as Salesforce, ServiceNow, Jira, and other tailor-made solutions according to your needs.

Managing an RCS project: What role do Dydu, smsmode, and your teams play?

Dydu and smsmode handle the technical implementation and support. Your teams focus solely on content and conversational scenarios via the BMS. A Customer Success Manager guides you after deployment to optimize and enrich the bot over time.

The RCS message, a key lever for conversational marketing

SMS 2.0 is not just an evolution of SMS: it is a true conversational channel that transforms customer relations. Richer, more interactive, and measurable, it allows companies to engage their users in a simple and effective way. Combined with a Dydu chatbot, it becomes a powerful tool for automating exchanges, personalizing journeys, and offering 24/7 availability.

Launch your RCS chatbot now with Dydu.

Summary

The government is investing heavily in artificial intelligence: more than €109 billion committed by the private sector and €200 billion at the European level. All of this is part of the “Dare to AI” plan, launched in early July 2025 to make AI accessible to all French companies by 2030.

What is the “Dare to AI” plan?

The national “Dare to AI” plan aims to democratize the use of artificial intelligence in all French companies, particularly SMEs and mid-cap companies, which are lagging behind (only 13% of them currently use AI).

It is based on three main areas:

• Raising awareness: creation of a network of 300 AI ambassadors, organization of regional events, and annual launch of AI Business Day.
• Training: launch of the AI Academy at the end of 2025, a free platform offering tutorials and training courses tailored to apprentices, employees, managers, and job seekers.
• Support: implementation of AI Data Diagnostics (40% co-financed by the State via Bpifrance), a catalog of ready-to-deploy solutions, guaranteed loans, and acceleration programs for 100 high-potential companies.

The plan is aimed at all levels of digital maturity and seeks to remove barriers to the adoption of AI.

Why now?

France and Europe are experiencing an unprecedented acceleration in investment in AI:

• €109 billion in investment announced by private actors at the Paris Summit for Action on AI in February 2025.
• €200 billion at the European level with the “InvestAI” plan.

These investments are shaping an ecosystem conducive to innovation and competitiveness, offering companies a unique opportunity to take the plunge. But to take full advantage of this momentum, it is essential to understand the challenges of AI in 2025, topics that we explore in our white paper.

What does this mean for your business?

• Today: assistance, training, and financing are available to help you take action.
• Tomorrow: structural support and the massive arrival of generative AI will transform how AI is used.

The figures speak for themselves: a 20% average productivity gain is expected for companies using AI. But beware: not adopting AI now means running the risk of falling behind the competition in the long term.

How does Dydu help you turn this plan into real growth?

At Dydu, we develop intelligent conversational agents tailored to the needs of businesses:

• Chatbots and callbots to streamline customer relations.
• Digital assistants to support your employees and staff on a daily basis.
• Industry-specific solutions already deployed in banking, insurance, healthcare, automotive, energy, and the public sector.

Our approach:

• Personalized support to identify your priority use cases, backed by 16 years of experience with clients from all sectors and a wide range of projects.
• Scalability to integrate generative AI innovations.

The figures speak for themselves: widespread adoption of AI can generate an average of +20% productivity per company.

Find out more about our solutions, use cases, and approach on our website.

AI is no longer a gamble on the future; it is an immediate reality and a strategic lever for remaining competitive. With the “Osez l’IA” (Dare to use AI) plan, the French government and Europe are offering a unique framework to accelerate the adoption of artificial intelligence in all companies. The question is no longer whether you should go for it, but how you are going to do it.

At Dydu, we help you turn this national ambition into concrete results with our conversational AI solutions (chatbots, callbots, digital assistants). Whether you want to improve the customer experience, automate your internal processes, or support your employees, we accompany you every step of the way, from diagnosis to implementation.

Request a demo today!

As the market experiences a resurgence in activity, driven by stabilizing prices and falling interest rates, more households are reviving their plans to buy. This is also having an impact on rentals, with demand on the rise again, much to the delight of real estate agencies.

But this momentum also brings its share of challenges: managing a growing volume of requests, often through digital channels, with customers who expect quick and personalized responses.

It is in this context that conversational AI comes into its own. Deployed in the form of a chatbot or callbot, it allows agents to pre-qualify candidates and respond immediately to recurring questions. This frees up time to follow up on priority files. With solutions such as those offered by Dydu, AI simplifies management and provides both a better customer experience and greater efficiency for teams.

The search for housing: a daily challenge

Searching for housing, whether to buy or rent, remains a difficult and time-consuming process. Candidates take multiple steps: consulting listings, calling agencies, and submitting applications online or in person. This process, already complex for the applicant, generates a considerable administrative burden for real estate agencies.

From search to allocation, a process simplified by AI

Faced with these issues, the main advantage of conversational AI lies in its ability to automate critical but time-consuming steps in the applicant’s journey:

• Finding the right housing: Real estate chatbots provide accurate information on available housing, eligibility criteria, and assistance programs (APL, income limits). As a result, applicants save time and can more quickly identify offers that match their situation.
• Help with putting together the application: Reminders of the necessary documents, automatic follow-ups in case of missing documents.
• Smart pre-qualification: Filtering of applications that do not meet the criteria to optimize processing by teams, by rejecting applications that are clearly outside the scope and redirecting them to the right contact person if necessary.
• Management of peak activity: During rental campaigns or program launches, the chatbot absorbs the volume of interactions without additional delay.

For example, a woman looking for an apartment interacts directly with an agency chatbot:

In a matter of seconds, the chatbot analyzes her criteria and offers a pre-selection of relevant listings tailored to her preferences.

It immediately reminds her of the list of documents to be provided to complete the application, checks her eligibility for certain subsidies, and allows her to make an appointment for a viewing. Whereas previously the candidate would have had to contact several real estate agencies and wait several days, the experience is now immediate, targeted, and reassuring.

The effectiveness is already measurable: in 2024, CDC Habitat’s chatbot automated more than 155,000 conversations, 92% of which were successful. And this success is not limited to the search: once settled in, tenants also benefit from ongoing assistance thanks to conversational AI.

Tenant management and support

In the rental market, day-to-day management remains “burdensome” for both tenants and agencies. Between organization, property maintenance, and administration, each task can quickly take up time and generate dissatisfaction.

Bots are gradually becoming facilitators capable of simplifying many everyday tasks:

• Frequently asked questions: rent, utilities, certificates, payment terms.
• File tracking: real-time notifications, progress updates.
• Everyday life: reporting technical issues, tracking complaints, uploading insurance certificates.
• Changes of residence: formalities related to moving, simplified arrival or departure.

This ongoing support guarantees a smooth experience for the tenant while freeing teams from repetitive requests.

Conversational solutions are now extending to more sensitive or even critical situations: maintenance, debt collection, or emergency management.

When AI turns the unexpected into immediate solutions

Tenant calls are not only about administrative procedures: they also concern everyday incidents, technical emergencies, and payment-related questions. In all these cases, the ability to quickly qualify the request is crucial.

1. Call pre-qualification: a structured process

When a tenant contacts their landlord, via a callbot for example, the callbot automatically identifies the caller via the ERP/CRM and asks a few targeted questions to clarify the reason for the call. There are three main scenarios:

• Simple request: the bot provides the answer directly (for example, how to obtain an insurance certificate) and generates a ticket that is automatically resolved.
• Complex request: the callbot creates a ticket in the rental management system, documented and ready to be processed by a human manager at a later stage (e.g., heating failure requiring technical intervention).
• Emergency: if the severity is confirmed (water leak, power failure, etc.), the call is immediately escalated to an advisor or on-call service.

In summary, here is how the process works:

This process not only allows calls to be filtered and categorized, but also determines in advance whether the incident is the responsibility of the tenant (minor repair) or the landlord (technical intervention). The result is better resource allocation, fewer unjustified interventions, and smoother handling of critical situations.

2. Rent collection and follow-up: proactive communication

The same logic of qualification and automation applies to collection. Conversational AI makes it possible to:

• Automatically remind tenants of payment deadlines,
• Notify them of late or unpaid rent as soon as it is detected,
• Propose appropriate solutions (payment plans, referral to a specialist advisor).

This lightens the load on teams, who are often busy with repetitive reminders, while ensuring clear and proactive communication with tenants.

Automation at the service of real estate agencies

Faced with a real estate market that is regaining momentum and teams that are often overwhelmed, conversational AI is now establishing itself as a facilitator for streamlining the customer journey. From finding accommodation to day-to-day management and administrative follow-up, chatbots and callbots make it possible to meet tenants’ expectations in terms of responsiveness, availability, and simplicity, while optimizing the internal resources of landlords and developers.

With its sector expertise and proven solutions, Dydu supports real estate players in this transformation by designing conversational assistants tailored to their needs and capable of integrating into their business processes.

Are you a landlord, developer, or property manager looking to improve your teams’ responsiveness while offering better service to your customers?

Request a demo now!

How can you respond instantly to thousands of travelers without breaking the bank?

This is the challenge posed today by the digitization of the tourism sector and the growing demands of both B2B and B2C customers.

Relationship standards in tourism are now aligning with e-commerce giants such as Amazon and Airbnb. Reservations are increasingly being made via AI, which is emerging as a decisive competitive advantage.

Leaders are turning to conversational AI not just to move faster, but to better serve, personalize, and transform their customer relationships.

The tourism sector is undergoing rapid transformation: in Europe and the United States, 73% of travelers already use AI to plan their trips.

But for B2B players in tourism, tour operators, hotel groups, camping chains, distributors, platforms, etc.,  the real question is no longer “do we need a chatbot?”, but rather:

How can we take full advantage of AI to personalize the experience, relieve teams, and maximize ROI?

The reality: the limitations of basic chatbots in tourism

Why “having a chatbot” is no longer enough

Long confined to fixed scripts or simple interactive FAQs, first-generation chatbots have shown their limitations:

• Approximate understanding,
• Generic responses,
• Growing frustration on the customer side,
• Inability to handle omnichannel or personalization.

Result: The “basic” bot does little to relieve teams in after-sales service and does not improve customer satisfaction or conversion during the purchase phase.

What customers expect in 2025: instantaneity, personalization, omnichannel

Standards are now dictated by industry giants. Expedia, Booking, and Airbnb have invested heavily in generative AI, with measurable results:

• +15% customer satisfaction for Expedia,
• +20% revenue for Airbnb,
• +10% additional bookings for Booking.

And customer expectations have followed suit:

• 78% of travelers say they want AI to provide them with personalized travel recommendations
• 73% of customers value instant responses
• 61% want AI to help them organize their trip

A chatbot without AI? It’s an agent that responds… without understanding the question.

The competition is innovating. Are you ready to follow suit?

The shift to AI in tourism is no longer a trend, it’s a race for performance. And the big B2B players coming out on top are those that combine:

• Intelligent automation,
• Integration CRM & data,
• Real-time personalization,
• Structured ROI management.

With this in mind, we are unveiling the five AI levers for transforming customer relations into a sustainable competitive advantage.

The five AI levers for boosting ROI and customer satisfaction

1. Understand intentions, not just words

An intelligent chatbot doesn’t just recognize keywords, it understands the user’s real intention thanks to Natural Language Understanding (NLU).

The result is a smoother, more human, and less frustrating experience.

Let’s take an example: “I would like to change my trip tomorrow evening.” Thanks to integrated generative AI, the chatbot analyzes the real intention, understands the context (date, customer profile, etc.) and proposes a targeted action without relying on a fixed decision tree. 

An AI-powered bot will be able to analyze, cross-reference with the CRM profile, and propose immediate action.

2. The right message, at the right time, for the right customer

Today, personalization means maximizing your chances of conversion.

Thanks to AI, a bot can:

• Propose an optimized itinerary based on tastes, weather, budget,
• Suggest additional options (upsell, cross-sell),
• Automatically re-engage an inactive prospect with a targeted offer.

Integration with the existing digital ecosystem is crucial (CRM, business tools)

A chatbot connected to CRM, booking tools, and customer data becomes a real business lever.

Customer history → contextualized responses.

KPIs tracked in real time → continuous adjustment.

Behavioral segmentation → better qualification.

For large companies, integration with business systems is an absolute prerequisite. Decision-makers now demand interconnected, controllable, and measurable bots. To ensure that the right message is sent at the right time to the right customer, the bot must be omnichannel. 

3. Offer a seamless omnichannel experience

In 2025, customers will navigate between websites, mobile apps, social media, live chat, point-of-sale terminals, and more. And they will expect one thing: a consistent, immediate, personalized response on the channel of their choice.

An effective chatbot should not be limited to a single channel. It must follow the user wherever they are, whether via a Facebook chatbot, WhatsApp, Messenger, Slack, Teams, or on a website.

This is the promise of omnichannel: a single conversational engine, deployed everywhere, with unified logic.

By centralizing the management of exchanges, bots guarantee a seamless experience, without any disruption between channels. Connected to a CRM, they retrieve customer history to personalize each response, regardless of the point of entry.

Thanks to Dydu, distribution across all channels is not limited to a simple presence: each point of contact becomes relevant, consistent, and responsive.

4. Availability and immediacy

In tourism, the unexpected is the norm. Flight delays, strikes, bad weather, a surge in requests during peak season… These peaks in demand can overwhelm channels if the system in place is not designed to anticipate them.

This is where conversational AI comes into its own.

A well-designed chatbot is available 24/7, without interruption. It allows travelers to ask questions or resolve issues at any time, including at midnight on the eve of a departure, in the middle of the summer season, or on a public holiday.

Another decisive advantage is the immediacy of information. The chatbot can automatically relay essential information about unexpected events, schedule changes, or exceptional closures, etc.

At the same time, its scalability allows it to maintain consistent service quality, whether it is handling 10 or 10,000 requests simultaneously. Unlike human customer service, which is limited in terms of staff and time, the bot does not tire, slow down, or become unavailable.

The result: fewer queues, less frustration, and better absorption of critical periods without having to recruit urgently or sacrifice customer satisfaction.

5. Human/bot complementarity: a winning combination

AI is not intended to replace humans, but to enhance them.

The best customer journeys intelligently alternate between automation and human interaction.

Examples:

• The bot handles simple requests (FAQs, cancellations, schedules).
• It transfers complex cases to a human advisor via an integrated live chat module.
• It pre-qualifies requests to save time for teams.

79% of tourist offices and 71% of tour operators have integrated AI. This highlights the importance of expert support such as that offered by Dydu.

In a sector as demanding as tourism, immediacy and personalization are no longer bonuses, but standards. Conversational AI is not just a time saver for teams: it is a strategic lever for building loyalty, converting customers, and absorbing peaks in demand without compromising the customer experience.

By activating the right levers—understanding intentions, personalization, omnichannel, scalability, and human/bot complementarity—it becomes possible not only to meet expectations, but also to exceed them.

Ready to take the next step?

At Dydu, we are already helping tourism players turn their chatbots into real performance accelerators.

Contact us for a personalized demo!

During sales, massive promotions, or seasonal peaks, online stores often face a sudden and intense increase in customer demand. How can you respond effectively to these requests while maintaining a smooth and personalized experience? The answer lies in one word: chatbot—or rather, an intelligent shopping assistant capable of acting as a real conversion lever.

E-commerce companies know this: more than 75% of them will adopt AI solutions to improve their customer experience by 2026.

Chatbots boosted by generative AI: a fully-fledged sales advisor

Long confined to the role of automatic response, chatbots are evolving. The rise of generative artificial intelligence now allows bots to interpret complex queries, contextualize exchanges, and engage in conversations with a level of fluidity and relevance never before achieved.

Gone are the days of rigid scripts: now it’s all about personalized conversations, where the chatbot understands the user’s intent, asks questions, recommends products, and even knows how to handle objections like a store advisor.

The result? A more intuitive, engaging, and above all, more efficient customer experience.

Absorb traffic without compromising quality

Automate product responses

A significant portion of customer inquiries are simple questions, but they are crucial to the purchase.

For example, on a cosmetics website, you might see frequently asked questions such as: “Is this product suitable for my skin?”, “Can I use it if I’m pregnant?” etc. Even if these answers are often found on the product pages, customers prefer to get a direct answer rather than searching for it themselves.

The e-commerce chatbot then becomes a facilitator, able to synthesize relevant information, reassure the buyer, and unlock a purchasing decision in a matter of seconds.

Manage massive traffic during peak sales periods

Sales, Black Friday, the holiday season… These periods lead to an explosion in traffic and requests. Automation via a bot allows you to maintain a high level of service, even with thousands of simultaneous conversations, 24 hours a day, 7 days a week.

This means that the bot can handle incoming requests simultaneously and throughout the entire purchasing journey:

• Pre-sales: the chatbot reassures your visitors from the very first interactions by answering questions about products, terms and conditions of sale, or the brand itself.
• Purchase:
  • It removes friction points (delivery, payment, technical errors) to reduce cart abandonment.
  • It can also make product recommendations based on the user’s questions and profile.
  • It can push promo codes to encourage purchases.
• After-sales: it provides effective follow-up (packages, returns, refunds) to streamline customer relations and strengthen loyalty.

Create more engaging conversation entry points

In current usage, many interactions with bots begin by clicking on the chat icon at the bottom right of the screen. This is where we are used to starting a conversation with a chatbot.

But if you want to trigger more focused and engaging conversations, a new approach is to integrate the most frequently asked questions directly into the product page — for example: “Is this product suitable for sensitive skin?” or “Is it available in other colors?” These clickable elements open a conversation with the bot.

This mechanism triggers proactive interaction at a strategic point in the purchasing journey. As a result, users feel supported and engagement increases.

Measurable results in engagement and conversion

Some brands that have implemented a generative AI-based chatbot have found that:

• Conversion rates are 10 times higher when users interact with an intelligent virtual assistant.
• The average basket size increases thanks to more personalized support.
• The return rate decreases because customers receive better advice upfront.

Every conversation between a customer and your chatbot contains valuable information: What are the most frequently asked questions? Where do customers encounter friction? Which products generate the most doubts or returns? Ignoring this data means missing out on opportunities for continuous improvement, whether in your content, your offers, or your user experience. A detailed analysis of these post-sale exchanges allows you to adjust your customer journey, anticipate future sticking points, and refine your next marketing campaigns.

And tomorrow: towards a new norm in e-commerce?

With the emergence of multimodal systems (chat, voice, image), brands are entering a new era of conversational commerce. The goal is no longer to guide users through a fixed purchasing funnel, but to adapt to their needs at the right time through conversation.

This is a paradigm shift. Brands that can offer this fluidity and personalization will have a head start.

Dydu, your partner for an AI-enhanced e-commerce experience

At Dydu, we support e-commerce brands in implementing intelligent conversational solutions that can address the following challenges:

• Boost conversion rates with bots that recommend, advise, reassure, and guide.
• Manage traffic spikes without overloading support teams.
• Increase engagement by creating strategic touchpoints throughout the customer journey.
• Control costs while improving customer satisfaction.

Our technology integrates easily into your digital ecosystem (website, CRM, PIM, analytics solutions, etc.) and complies with GDPR requirements from the design stage.

Why not make conversational AI your next growth driver? Let’s talk!

In social housing, landlords are facing increasing pressure: growing tenant demands, the need to respond quickly, and declining human resources.

In the face of these challenges, conversational automation is emerging as an effective lever for modernizing rental management. More and more social landlords are deploying real estate chatbots to improve customer service, save time, reduce management costs, and meet tenants’ expectations in a fair, fast, and consistent manner.

In this article, you will discover how these tools meet the specific needs of social landlords, their most common uses, and the results that can be achieved, based in particular on feedback from CDC Habitat.

Rental management under pressure: tenant expectations vs. social housing provider constraints

In the social housing sector, social housing providers are now faced with a growing paradox: increasing tenant demands coupled with stagnating or even declining human resources. Files to be processed, housing assistance requests, calls about rent, reports of technical emergencies, and more. Rental management has become more complex. At the same time, tenants, who are increasingly accustomed to using seamless digital services, have expectations similar to those of customers in other sectors: 24/7 availability, immediacy, and ease of access.

Faced with these pressures, landlords’ teams are sometimes overwhelmed: overflowing switchboards, delayed responses, and a decline in the perceived quality of service.

The result is dissatisfaction that can turn into a reputational challenge.

In this context, digitization and operational efficiency are no longer luxuries, but essential levers for maintaining trust with tenants… while keeping costs under control.

1. Automation for social housing: conversational AI, chatbots, and callbots

To meet these new challenges, many players in the social housing sector are now turning to conversational AI solutions such as those offered by Dydu, which can handle all or part of tenant interactions. The goal is to improve responsiveness without adding to the workload of teams.

At Dydu, we see frequent use cases:

• A chatbot responds to simple, recurring, and documentable requests:
  • Rent amount or balance,
  • Status of assistance such as APL,
  • Supporting documents to be provided,
  • Insurance certificate,
  • General questions about the social housing application process.

It is also possible to add a voice option to the chatbot to offer a smooth and intuitive voicebot experience. This voice channel, coupled with AI, allows incoming calls to be answered automatically and callers to be guided without human intervention, while remaining interfaced with the landlord’s business tools.

• A live chat allows more complex requests to be escalated to human advisors, providing assistance and a personalized relationship.
• A callbot is sometimes used to handle large numbers of calls at certain critical times:

• Reminder campaigns for unpaid bills (late fees, rent increases, etc.),
• Management of technical alerts or emergencies,
• Proactive communication about localized incidents.

Some solutions even allow you to manage both written and verbal channels while interfacing with the landlord’s internal information systems. This is a key requirement for seamless automation of business processes.

Case study: CDC Habitat modernizes its rental management with conversational AI

Faced with the challenge of unclogging traditional channels and improving the customer experience, CDC Habitat has embarked on an ambitious overhaul of its rental management with the support of conversational automation solutions.

Two objectives guided this transformation:

• Enhance self-care for tenants and prospects in day-to-day procedures
• Lighten the load on internal teams for first-level requests

The solution deployed is based on:

• A chatbot on the tenant space and commercial portal
• A live chat for situations requiring human support
• A callbot for large-scale reminder campaigns

In 2024, CDC Habitat recorded:

• 155,000 conversations via chatbot, with a 92% resolution rate without human intervention
• 32,717 calls handled in 4.5 days via the callbot as part of an SLS campaign.

These figures represent a significant operational time saving, a notable improvement in the collection rate and increased tenant satisfaction, thanks to a fast, clear response available 24/7.

Beyond the figures, this initiative is helping to modernize the image of social landlords: tenants appreciate a more fluid and proactive relationship, and internal teams can now refocus on complex cases.

Why switch to automation? ROI, efficiency, and image

For a social housing provider, switching to automated tenant communications via conversational AI is not just a technological issue. It is a strategic lever, and at Dydu, we support social housing providers every step of the way to help them overcome several fundamental challenges.

• Reduced rental management costs: fewer on-call duties, fewer calls to handle directly, and a less congested switchboard.
• Scalability: the ability to process tens of thousands of files without hiring additional staff, even during peak periods.
• Modernized image: in the eyes of tenants and elected officials alike, a landlord is perceived as innovative, responsive, and attentive by implementing automation solutions.
• Enhanced accessibility: a service available 24/7, ensuring fair treatment for all users.

Digital transformation is accelerating in the public sector as well as in the social housing sector. These solutions deliver a tangible return on investment while improving the tenant experience.

Conclusion

Automating tenant interactions is no longer an option, but a pragmatic response to the daily challenges faced by social landlords. As the example of CDC Habitat has shown, the benefits are immediate: smoother service, reduced internal costs, increased tenant satisfaction, and a modernized image.

At Dydu, we support social housing providers in this transformation.

Whether you are looking to launch your first project or industrialize an existing one, we design customized solutions that are interconnected with your business tools and designed for real-world use.

Because a more responsive, fairer, and more modern service starts with a simple conversation.

Ready to rethink your tenant relationship and modernize your rental management?

In 2025, 83% of European employees will use collaborative messaging on a daily basis in their companies, according to Eurostat, Digital Economy and Society. Teams, Slack, Google Chat… These tools have become the new hubs of internal communication. And in these environments, collaborative chatbots, also known as internal chatbots, are taking on a strategic role.

Deployed directly in Microsoft Teams or Slack, these conversational bots are no longer just automation gadgets. They are becoming everyday assistants, capable of streamlining HR requests, reducing IT support workloads, and automating internal communication.

Why are these “social” chatbots reinventing internal collaboration? What are the benefits for HR, IT, and employees? And above all, how can you effectively integrate them into your existing collaboration tools?

What is a Slack or Teams chatbot?

An internal social bot is a conversational agent integrated into a collaborative platform used in companies, such as Slack or Microsoft Teams. Unlike external (customer-oriented) chatbots, their mission is to facilitate exchanges between employees and automate internal interactions.

They operate in spaces where employees are already connected all day long. As a result, they are accessible in one click, at the right time, without leaving their work environment.

Key features:

• Native integration with Slack or Microsoft Teams
• Natural language interaction, 24/7
• Connection to business tools (HRIS, CRM, ITSM, intranet, etc.)
• Instant responses, even outside normal working hours
• Customizable scenarios according to department or role

Why choose a Slack or Teams chatbot?

With the rise of hybrid working, companies need agile, scalable, and engaging tools to maintain smooth communication. A collaborative chatbot ticks all these boxes.

Here are the concrete benefits of an internal social bot:

Present where your teams work

Slack and Teams are already where daily discussions take place. A chatbot deployed in these channels meets users where they are active, without friction.

Instant and autonomous

Employees ask a question, the chatbot responds. Zero tickets. Zero wait time. And if it can’t answer, it automatically redirects to the right person or tool.

Full business integration

Social bots can connect to internal systems such as Jira, ServiceNow, SAP, Workday, or your in-house HRIS. As a result, they don’t just answer, they take action (creating tickets, extracting HR data, etc.).

Real-world use cases for a Slack or Teams chatbot

Onboarding and integration

• First-day welcome scenario
• Introduction to the manager, team, and tools
• Access to internal rules and regulations, practical guides, and useful contacts

HR support

• Viewing vacation balance
• Access to schedule, pay stub, or expense report
• Frequently asked questions: remote work, benefits, procedures

IT support

• Password reset
• Ticket creation and tracking
• Maintenance or incident notifications

The future of collaboration lies in internal social bots

Collaborative tools have become central to organizations, and integrating a chatbot into Slack or Teams is no longer an option, but a natural evolution. Internal social bots enable you to:

• Reduce friction in daily exchanges
• Automate recurring requests
• Improve employee engagement
• And save valuable time without overloading your support teams

Dydu supports you in this transformation with sovereign, secure technology and proven expertise in deploying bots on Teams and Slack. The right message, at the right time, in the right workspace: that’s the promise of a well-designed social bot.

Invisible but indispensable, the chatbot Facebook is establishing itself as a strategic lever in customer relations.

Deployed on Facebook Messenger, WhatsApp, and Instagram, it allows companies to communicate instantly with their customers, directly in the apps they use every day.

By 2025, more than 5.2 billion people will be actively using social media. Expectations are changing: instantaneity, fluidity, personalization. Brands must adapt.

How can you respond to customer requests 24/7 without increasing costs?

WhatsApp chatbots, Messenger bots, and Instagram bots offer a concrete solution: automate exchanges, improve the customer experience, and remain present throughout the customer journey.

What is a Facebook chatbot for customer relations?

A Facebook chatbot is a conversational agent integrated into Messenger or a Facebook page. It allows brands to automate responses, assist with purchases, or manage customer service—all directly on the platform.

It is part of the social bot family, virtual assistants designed for social platforms such as Messenger, WhatsApp, and Instagram.

Advantages

• Direct presence in Messenger or Instagram DM
• Automatic responses to frequently asked questions
• Proactive notifications (orders, promotions, reminders, etc.)
• CRM, e-commerce, or ticketing tool integration
• Option to transfer to a human advisor

The main types of social bots

Facebook/Messenger chatbot

• Ideal for interacting directly on a Facebook page
• Abandoned cart reminders or targeted promotions
• Automated FAQs and customer service support
• Redirection to an advisor in just a few clicks

WhatsApp chatbot

• Excellent for mobile-first customer relations
• Order tracking, customer service management, proactive reminders
• Uses the WhatsApp Business API to send personalized messages
• Perfect for post-purchase customer support

Instagram bot (DM)

• Responds directly to users’ private messages
• Ideal for B2C brands in fashion, beauty, and lifestyle
• Can direct users to a product, an e-commerce link, or an advisor
• Seamless interface, integrated into the social shopping experience

Use cases for social bots in business.

Retail & E-commerce

Messenger chatbots or WhatsApp bots are transforming customer relations:

• Personalized product recommendations via Messenger or Instagram
• Real-time order tracking in WhatsApp
• Automated abandoned cart reminders
• Redirection to secure payment from the messaging app
• 24/7 customer support with option to switch to an advisor

Tourism & Travel

• Booking confirmation via WhatsApp
• Baggage information, check-in, or flight schedules via Messenger chatbot
• Instant assistance during the trip
• Smooth management of emergencies (delays, cancellations, etc.)

Customer service (multi-sector)

• Facebook chatbot integrated into your company page
• Automation of FAQs: schedules, prices, delivery
• File tracking, after-sales service, specific requests
• Human transfer if necessary with reduced response times

Why integrate a social chatbot into your strategy?

Thanks to social bots, your company benefits from numerous advantages:

• Be where your customers are: Messenger, WhatsApp, Instagram
• Ultra-fast response times, even outside business hours
• Automation of recurring requests: FAQs, order tracking, returns
• Integration with your business tools (CRM, e-commerce, helpdesk, etc.)
• Customization of exchanges based on customer profile or history
• Conversion optimization with targeted follow-ups.

By deploying your chatbot on the social channels most used by your customers, you maximize its adoption and effectiveness. In other words, a useful, accessible, and well-positioned bot naturally promotes engagement. Messenger, WhatsApp, and Instagram DM become seamless points of contact, integrated into your audience’s daily habits.

Conclusion

Today, customer relations are played out in social messaging.

With a Facebook chatbot, a WhatsApp chatbot or an Instagram bot, you are where your customers expect you to be… and you respond to them immediately, efficiently and personally.

With Dydu, you benefit from cutting-edge technology, an accessible interface and tailor-made support. The right message, at the right time, on the right channel: that’s the promise of a well-designed social bot.

The automotive industry is undergoing major changes, driven by the rise of electric cars, the arrival of new entrants such as Chinese brands BYD, Nio, and Xpeng, and the challenges associated with the green transition. Established manufacturers such as Renault, Citroën, Peugeot, Audi, and Toyota must adapt to new environmental regulations and increased competition. At the same time, players such as Tesla are seeing their position challenged, caught between market diversification and Elon Musk’s controversial strategic choices. In this context, customer experience is becoming a crucial differentiator.

In response to these developments, digital technology is becoming increasingly strategic. Conversational artificial intelligence, via chatbots, callbots, or Livechat, is emerging as a lever for efficiency and performance in pre-sales, customer service, after-sales service, and internal uses. According to an ICDP study, 65% of customers consider responsiveness to be a key factor in satisfaction with automotive after-sales service. These technologies enable responsiveness, personalization, and fluidity throughout the customer journey.

Overview of use cases for conversational AI in the automotive industry

Pre-sales & marketing

Conversational AI enables you to engage customers early in their purchasing journey and effectively qualify their needs:

• Lead qualification: the chatbot interacts with the visitor, asks a few questions (budget, type of vehicle, location, etc.) and passes on a qualified lead to the sales teams.
• Vehicle configuration: guided and interactive support in choosing the model, engine, finishes, and options.
• Test drive booking: online booking of a test drive at a dealership or at home, with management of available slots.
• Promotion & marketing campaigns: sending personalized offers or news via instant messaging (WhatsApp, Messenger, etc.).

After-sales

After-sales service remains a key point of contact for customer loyalty. AI can automate and improve several steps:

• Workshop appointment booking: a chatbot or callbot guides the customer and suggests available slots.
• Simple fault diagnosis: the bot asks questions to identify symptoms before a visit to the workshop.
• Parts/accessories ordering: assistance in finding and purchasing compatible accessories or parts.

Conversational AI also allows after-sales teams to refocus on high value-added tasks. By automating responses to simple questions (appointments, warranties, availability), it frees up time for more personalized support, which is conducive to selling additional services such as servicing, warranty extensions, or maintenance contracts.

Customer relations & support

Conversational AI improves service quality and guarantees continuous availability:

• 24/7 support (hotline): automated responses to frequently asked questions (FAQs: warranties, delivery times, maintenance, etc.).
• Assistance in the event of a breakdown or accident: initiation of a breakdown procedure or direct contact with emergency services.
• Complaint handling: first level of automated management, with referral to the right human contact if necessary via a live chat escalation.

Network support and internal use

Conversational AI doesn’t just benefit customers: it also improves the operational efficiency of internal teams.

• Sales team support: an internal chatbot provides quick answers about offers, products, stock, etc.
• Sales and advisor training: conversation simulator bots can train employees on customer cases or sales scenarios.

Case study: Renault & Dydu: a chatbot serving the network

At Renault, conversational AI is not limited to customer interaction. The manufacturer has also chosen to digitize its internal sales support tools using a chatbot developed with Dydu.

The context: to address cost and support availability issues, particularly on weekends and open days, Renault launched the Move Maeva chatbot in 2023 for salespeople and sales managers in its French network (approximately 5,000 users).

The objectives:

• Eliminate telephone support while maintaining a high level of assistance.
• Automate level 1 responses.
• Centralize requests via a ticketing system integrated into the bot.
• Ensure 24/7 availability.

The results:

• More than 102,000 visitors and 12,900 interactions since launch.
• A 90% understanding rate.
• Better traceability of requests thanks to the centralization of tickets in the associated tool.

Collaborative bot management: a dedicated team of six people works on chatbot maintenance, relying on monthly workshops to analyze conversations, enrich the knowledge base, and refine the relevance of responses.

A promising project: appreciated by both support teams and field users, Move Maeva has enabled Renault to improve the quality of support while lightening the operational load. Developments are already underway, such as the ability to add attachments to tickets and the integration of a live chat for complex requests.

This use case perfectly illustrates how conversational AI can go beyond external customer relations to boost the efficiency of internal teams in an environment as demanding as car sales.

Dydu, partner to automotive brands

At Dydu, we support players in the automotive sector with a comprehensive range of tailored conversational solutions:

• Callbot: accessible by phone, it qualifies calls, automates appointments, and reduces waiting times.
• Chatbot: integrated into your website, mobile app, or instant messaging service, it offers seamless, personalized assistance.
• Livechat: complementing the chatbot, it allows complex requests to be transferred to a human advisor for seamless, continuous support.

Our technologies integrate easily with your business tools (CRM, workshop scheduling, ticketing, etc.) and comply with industry security and confidentiality standards.

Whether you’re looking to attract new customers, streamline after-sales service, or support your internal teams, conversational AI is a strategic lever for staying competitive in a rapidly changing automotive market. Responsiveness, personalization, availability, efficiency: these technologies improve both the customer experience and team performance. At Dydu, we put our expertise at the service of brands to transform these challenges into concrete results.

The digitalisation of municipal services is no longer an option, but a necessity in order to meet citizens’ growing expectations in terms of efficiency and responsiveness. Callbots are proving to be powerful tools for improving the quality of public service management .

1. Welcoming and guiding citizens

One of the first benefits of callbots is their ability to take on certain time-consuming tasks for municipal staff. These telephone agents can play a crucial role in guiding citizens to the appropriate services according to their needs. Dydu bots are capable of:

Answer incoming calls: in order to identify the nature of the request (administrative procedures, housing application, local events etc.).
Direct the caller to the relevant department.
Provide a first level of information if necessary.

This process not only reduces the workload for reception staff, but also improves the experience for citizens by providing them with a quick and accurate response.

2. Managing administrative appointments

Administrative appointments can sometimes be complex to manage, whether they concerncivil status, permits or housing applications.

Callbots can :

Manage appointment booking: by asking citizens the right questions to identify their specific needs.
Interact with citizens to offer them an appointment slot.
Send automatic reminders for appointments or reminders for missing documents on a file.
Manage cancellations or modifications.

This system considerably reduces the workload of agents, while offering citizens a 24/7 service.

3. Answers to frequently asked questions

Town halls receive a large number of repetitive questions, and it is possible to programme your callbot so that they can respond instantly on :

• opening times
• administrative procedures
• town planning and housing
• transport and mobility
• social assistance and personal services
• local events

In other words, you can personalise it as you like!

This frees up time for municipal staff to concentrate on more complex tasks. At Dydu, our voice assistants are able to handle over 80% of citizens’ frequently asked questions, reducing the number of calls and emails that council departments have to deal with manually. Our town hall bots (callbot or chatbot) are built with a pre-written knowledge base that can be used as a support and that you can customise and adapt to your needs. Here’s a concrete example with a customer testimonial from Pleaux town hall!

4. Reporting and monitoring incidents

Citizens regularly report incidents such as noise pollution, damage to public thoroughfares or malfunctions in urban facilities.

Voice agents can simplify this process by enabling citizens to:

Report these problems directly via an automated call or chat.
Provide automatic updates on the progress of their report.
Notify citizens when their report has been taken into account, is being processed, or has been resolved.

In this way, you improve the transparency of your services to ensure citizen satisfaction.

5. Satisfaction surveys and citizen participation

Telephone assistants don’t just respond to requests, they can also play a part in:

Assist citizens with their procedures step by step.
Invite citizens to take part in a short satisfaction survey or give their opinion on a local project.
Gather opinions and feedback.
Notify them of new services available.
Issue alerts in the event of major events such as roadworks, water orelectricity cuts, or weather warnings…

Not only does this allow you tooffer a quality of service, it also allows you to measure the quality of the services provided. At the same time, you are encouraging active citizen participation. Dydu bots are effective in carrying out these types of actions and give town halls the opportunity to collect valuable data to improve their services.

Integrating a callbot into your municipal service is an opportunity to modernise it, making it more efficient while reducing your costs by 30%. To find out more about Dydu bots, request your callbot demo!

In an environment where technology is advancing at lightning speed and consumer expectations continue to rise, it’s imperative that companies adopt innovative solutions to improve their customer service. Among these solutions, callbots stand out for their ability to revolutionize customer interactions. The French customer relations observatory (Observatoire de la Relation Client) states that 55%* of French people use the telephone to contact their support service. These conversational agents, powered by artificial intelligence (AI), offer continuous assistance, available 24/7, enabling companies to respond to web users’ needs efficiently and, above all, without interruption. Discover how these virtual agents can transform your customer relationships, simplifying processes, generating business and improving satisfaction on both sides of the phone!

Reduce costs, simplify processes

Callbots have a significant impact on reducing operational costs by automating repetitive interactions with users. According to a Capgemini study on conversational interfaces, 76%* of companies report tangible benefits from implementing voice assistants. In particular, this translates into a reduction in customer service costs of over 20%*. By automating responses to frequently asked questions, and directing more complex calls to human advisors, voice assistants reduce staffing requirements while maintaining quality service.

Thanks to their ability to handle simple requests quickly and efficiently, they enable companies to benefit from a reduction in call-backs, which are often costly and time-consuming for businesses. By reducing these redundant interactions, callbots optimize employee time while ensuring greater customer satisfaction. What’s more, reducing the number of calls helps improve employee morale and reduce turnover.

Generate business, pre-qualify calls

By being available 24/7, bots give companies the chance to never miss an opportunity, even outside office hours. They can handle inquiries, provide information on products and services, and even initiate sales, all without human intervention. According to a study by Accenture, companies that take advantage of AI, including callbots, could increase profitability by 38%* by 2035 by increasing productivity.

What’s more, they are an excellent tool in call pre-qualification. Voice assistants can gather relevant information from users before transferring the call to a human advisor, enabling sales teams to focus on high-value opportunities. One of our customers using this tool reports that their bot fully handles 25% of calls and pre-qualifies 60% of the remainder, enabling advisors to shorten application processing time. In this way, intelligent pre-qualification optimizes the use of human resources, improves team efficiency and can also increase conversion rates.

Improving customer satisfaction and the employee experience

One of the most notable benefits of callbots is their ability to eliminate waiting times, which is crucial to delivering a positive user experience. With new consumer expectations on the rise, responsiveness is also key. According to AMARC (Association pour le Management de la Réclamation Client), a response time of less than a few hours translates into 10% perceived tension, while a delay of over a day generates 40% tension. Thanks to bots, Internet users no longer have to wait for answers to their simple questions, which reduces their frustration and improves their overall satisfaction. A Forrester survey shows that 73% of consumers say that valuing their time is the most important thing a company can do to provide good service. On the employee side, these virtual agents can play a supportive role, providing real-time information or taking over time-consuming tasks. This enables them to concentrate on more complex and rewarding interactions, while reducing the stress associated with managing repetitive requests.

Our customer MACSF has implemented a callbot to extend the support department’s opening hours and pre-qualify policyholder requests. The bot prequalifies over 80% of incoming requests, generating a better user experience, an increase in the number of subscriptions and a smoother request processing process.

Today, virtual assistants are essential tools for any company seeking to optimize its customer service and improve the employee experience. By reducing costs, generating qualified leads, and offering a better user experience, these technologies pave the way for more agile and efficient management of customer and employee relations.

To find out more, discover our Callbot Dydu or book your demo!