How can companies transform their customer relationships through conversational agents?

AI agents can be integrated into the customer relationship ecosystem: website, customer portal, partner portal, WhatsApp, Messenger, or even directly within the CRM.

Today, generative AI solutions are driving the transformation of customer service. According to PwC (2024), 78% of companies plan to experiment with generative AI in the next three years, and 10% are already advanced, confirming a strong momentum of large-scale adoption.

To learn more: Why 2025 is the perfect year to adopt AI agents in customer service?

Companies today must balance operational efficiency, customer responsiveness, and cost control.
A conversational agent handles a large portion of simple or recurring requests while ensuring continuous 24/7 availability.

Key benefits:

• Maintain customer satisfaction even during peak activity periods.
• Reduce operational costs linked to first-level support.
• Allow human advisors to focus on high-value-added interactions.

In practice, a conversational agent can:

• Qualify a request and direct it to the right department.
• Manage appointment or quote scheduling.
• Automatically answer frequently asked questions.
• Provide first-level after-sales service or internal support.

More than just a response tool, it becomes a strategic component of omnichannel orchestration: it streamlines customer journeys and ensures continuity across channels until the issue is resolved.

Key data:

• HubSpot (2024): 70% of customer service managers using AI chatbots report a positive ROI.
• IBM: Chatbots can handle up to 80% of routine inquiries and cut support costs by as much as 30%.
• MIT Technology Review: 90% of companies report faster request resolution after implementation.

To learn more: Customer journey orchestration

An AI agent is not meant to replace humans. Its boundaries must be clearly defined from the start:

• Complex or emotional requests should be transferred to a human advisor.
• Performance depends on the quality of knowledge management, a structured, updated, and contextualized knowledge base is essential.
• Collected data must comply with GDPR regulations

A healthy balance between automation and human intervention ensures a credible and sustainable customer service experience.

To learn more: Knowledge management best practices

The most effective approach follows a “test & scale” logic:

• Define the priority use cases (FAQs, after-sales service, appointments, qualification).
• Start with a limited scope and measure the results.
• Gradually integrate the conversational agent into the CRM and business tools.
• Track key performance indicators: resolution rate, cost per interaction, customer satisfaction, overall ROI.

Each winter, the Méribel and Les Menuires ski resorts must handle a massive volume of customer inquiries.

In 2024–2025, they deployed a DialOnce conversational AI agent in just two weeks. The results: several thousand interactions and a 75% resolution rate.

The chatbot manages recurring requests (schedules, prices, weather, activities) and redirects visitors to relevant resources, freeing up teams to focus on complex or urgent cases.

This implementation illustrates how an AI agent can absorb high volumes, enhance the customer experience, and stabilize operations during peak season.

The goal is not to automate customer relations, but to better balance them between humans and AI.

Agents become a driver of efficiency and consistency across the customer journey, they are integrated into a holistic vision of customer relationship management.

It is within this complementarity that a smooth, effective, and sustainable experience is built.