The agency AI is already revolutionizing European business, but 90 % of companies remain blocked in a transactional approach – here are the 3 challenges to be met to go to the experiential AI.
Agental artificial intelligence already transforms the European commercial landscape. These new AI agents are revolutionizing everything, from automated customer support to hyper-personalized marketing, including the optimization of stocks or the proactive resolution of customer incidents.
However, despite impressive technological advances, most organizations remain blocked in a transactional AI approach. Their agents excellent certainly in the creation of content and the automation of repetitive tasks, but are struggling to create authentic connections with customers and employees.
This limitation considerably slows down the potential of AI. Without a fine understanding of human interactions, these systems fail to build the lasting links essential for loyalty and commitment. Companies wishing to take advantage of the experiential AI will have to rethink their relational approach in depth.
Complexity increases with the growing interconnection of AI systems. This rapid development highlights the structural weaknesses of many organizations: partitioned platforms, fragmented data, obsolete architectures and limited calculation resources. Faced with this permanent transformation, the leaders legitimately wonder about the procedure to follow.
Create a unified data ifrastructure
The foundation of success is based on the aggregation and harmonization of customer experience data from all contact points: physical shops, social interactions, technical support, mobile applications and digital exchanges. This consolidation allows the AI to generally understand the customer journey and to formulate relevant recommendations in real time.
The teams can thus question this data in natural language to detect large -scale optimization opportunities. This methodology already generates tangible results: acceleration of commercial cycles, improvement of transformation rates and strengthening customer loyalty.
Although organizations are increasing agentic AI platforms, their effectiveness fundamentally depends on the establishment of a centralized and coherent data architecture. This informational supply chain constitutes the basis of AI’s performance and decision -making intelligence.
Establish rigorous ethical governance
Organizations must imperatively define a strict ethical framework for the use of AI, by favoring the securing of sensitive information and the prevention of algorithmic discrimination. These safeguards are crucial to developing user confidence and respecting European regulatory evolution.
Concrete illustration: A French insurance company has anticipated the risks of bias in its predictive AI by identifying that algorithms led only on its young urban customers would generate inadequate analyzes for other demographic segments. This preventive vigilance has facilitated the deployment of an early detection system for fraud, which automatically alerts specialized teams during suspicious anomalies.
The transition from isolated experiments towards global strategies requires close coordination between customer, trades and techniques relationships. Efficient organizations achieve it by establishing transparent decision -making processes and clearly defined responsibilities, generally via committees dedicated to the evaluation and prioritization of IA initiatives.
Favor user -impact use cases
In a context of accelerated transformation, adopting a pioneer posture provides a decisive competitive advantage. Innovative companies start with targeted applications that identify organizational gaps, develop internal skills and prove profitability. These initial successes then legitimize more substantial investments.
A convincing IA strategy must emanate from the general management, which defines vision both for immediate opportunities and for emerging technologies such as agentics. This approach allows customer experience teams to quantify immediate profits while preparing future changes.
The trade of tomorrow will no longer be limited to transactions, but will orchestrate lasting relationships, anticipate needs and personalize large -scale experiences. The challenge is no longer whether this revolution will take place, but to ensure that it is actively part of it.
