The ENGIE Group, a global leader in the Energy Transition, is accelerating the transformation toward a carbon-neutral economy through solutions that reduce energy consumption and respect the environment.

In this interview, Flavia Lenzi, Head of Marketing & Customer Service at ENGIE Italy, and Elisa Fontana, Senior CRM Consultant at Engineering, share the challenges and opportunities in adopting an AI-Driven CRM from both a business and technological perspective: a living, adaptive, integrated, and scalable CRM - where every customer is followed with surgical precision, every piece of data is turned into action, and every operator is empowered, not replaced.

The use cases we have identified and implemented so far at a global level cover several areas: customer service (optimizing consultants’ work, digitalization, and self-care through chatbots or automated email replies), but also marketing (personalizing communication campaigns to improve customer experience and satisfaction, thereby increasing customer value).

In Italy, we have experimented with several types of Artificial Intelligence - predictive, generative, and now agentic. With predictive AI, we have long used solutions that support our analyses, such as a speech analytics tool that captures customer conversations in real time, identifying relevant topics and sentiment in both phone and digital interactions. We also use machine learning models for purchase prediction and churn prevention - that is, estimating the likelihood that a customer will leave us in the coming months - to enhance our caring and re-engagement campaigns.

Last year, we tested our first Generative AI use case, aimed at enhancing the activities of our call center operators during customer calls. We developed an engine that allows them to interact in natural language with our knowledge base, more smoothly and quickly, enabling faster and more efficient conversations.

We also use generative AI in our communication campaigns, personalizing the subject line, content, and tone of messages based on the information in our CRM, so that each customer receives communications more aligned with their profile. This enables us to deliver the level of personalization customers increasingly expect, leveraging data and Generative AI.

We have also developed a customer segmentation model that groups customers according to similar behaviors and characteristics. This allows us to offer differentiated experiences: tailored scripts for direct contact or personalized outbound communications by segment.

The latest frontier we have explored is agentic Artificial Intelligence - that is, virtual agents. We wanted to extend this technology to end customers, testing their interest, curiosity, and reactions in a controlled environment, without risking our reputation or the customer experience. We therefore chose a simple and well-defined use case: the onboarding phase. During this phase, customers already receive proactive communications explaining what is happening with their supply contract. In one of these communications, we introduced the option to chat with a virtual agent to ask specific questions about their contract, offer, economic conditions, or activation date.

The opportunities arising from the integration between Artificial Intelligence and CRM mainly develop along three key directions.

The first is automation: AI enables the automation of numerous processes, particularly in customer service, through the use of chatbots, virtual assistants, and intelligent ticket management systems. New possibilities are also emerging in marketing: the integration of AI and marketing automation makes it possible to generate personalized and automated content, adapted in real time to customer behavior and characteristics.

The second is personalization. AI enables advanced personalization, both at the individual level and across dynamic segments, making it possible to deliver more relevant content, products, and promotions - at the right time and through the most effective channel. This approach significantly enhances the customer experience and the relevance of interactions.

The third is predictivity. One of AI’s main added values is its predictive analysis capability. In sales and marketing processes, it allows companies to identify customers with a high propensity to purchase or at risk of churn, providing tools to increase conversions and reduce customer attrition.

Finally, agentic artificial intelligence is emerging - systems capable not only of analyzing and suggesting actions but also of acting autonomously within defined boundaries, coordinating operational activities and interacting with other business applications. When integrated into the CRM, agentic AI can learn in real time from behaviors and interactions, dynamically evolving its contribution; it can perform complex tasks - such as qualifying leads, automatically updating customer records, orchestrating multi-channel campaigns, or initiating post-sales actions - freeing staff from repetitive activities and expanding the organization’s operational capacity.

This paradigm opens scenarios where the CRM is no longer just a management tool but an intelligent ecosystem capable of anticipating needs, suggesting actions, and building more personalized and meaningful relationships.

For the next steps, we are convinced that Artificial Intelligence offers great potential - both for operational efficiency and for improving the employee experience. It must be a tool that simplifies life and enables people to do their jobs better.

We therefore aim to extend it to other relevant use cases, characterized by high volumes, costs, or repetitive activities, where the impact can be greatest. For example, introducing a voice-based virtual agent that can also answer phone calls for simple requests (such as bill duplicates), providing a 24/7 service when call centers are closed.

On the operational side, our goal is to eliminate all time-consuming tasks for operators - such as call summarization and updating - to free them up and allow them to focus on building relationships and showing empathy toward customers. The same applies to standardized written requests, where Artificial Intelligence can assist in classifying and drafting a pre-filled response, which the operator can then personalize.

In my view, the next steps toward full integration between Artificial Intelligence and CRM require a balance between technology, people, and strategy: only by combining these elements can AI evolve from a potential opportunity into a concrete lever of competitiveness within CRM processes.

Technology: it is essential to have CRM solutions capable of interacting with various business systems and managing integrated, clean, and reliable databases. Without quality data, AI cannot generate truly useful insights.

People: adopting AI is not just a technological matter, but above all a cultural one. Companies need to develop internal skills that enable people to fully leverage the potential of AI, transforming it into a tool that empowers their capabilities rather than overwhelms or replaces them.

Strategy: the primary goal must be to generate tangible value for the customer and, as a result, for the company. This means designing applications capable of personalizing interactions, anticipating customer needs, and improving the efficiency of marketing, sales, and customer service processes.