Capgemini Executive: The Challenge of Enterprise Agentic AI Lies Not in Models, But in Operating Models
Fernando Alvarez, Chief Strategy and Development Officer at Capgemini Group, argues that the bottleneck for enterprise agentic AI systems is not model capability but the operating model—specifically, whether teams can control agent access scopes, observe execution processes, and evaluate changes using their own data. Mistral Studio’s recent update provides features such as OpenTelemetry tracing, evaluation, and access boundaries that correspond to these constraints; however, the relevant quotes come from the vendor’s own blog, meaning the framing of the solution and the naming of the problem are subject to the provider's commercial interests.
Fernando Alvarez, Chief Strategy and Development Officer at Capgemini Group, has made a specific assertion: the challenge of enterprise agentic AI systems lies not in the models, but in the operating model. By this, he means that even if model capabilities are sufficiently strong, demonstrations will remain stuck in the demo phase if teams cannot control which systems agents can access, cannot observe what happens at each step of execution, and cannot evaluate the impact of changes using their own data.
This assertion is not isolated. Julien Smadja, Vice President of AI at shipping company CMA CGM, noted that their AI system, built in collaboration with Mistral engineers, covers critical processes such as cargo release, customer assistance, and logistics orders; for each new automated process, the time from development to production readiness has been shortened from months to weeks. Gualtiero Bazzana (Member of the Executive Committee and Chief AI Officer) pointed out that most industrial AI projects are still stalled at the pilot stage; his team plans to build agents and workflows on Mistral Studio for clients' engineering and R&D departments to move pilots into production.
The 'operating model' described by Alvarez has corresponding technical infrastructure in Studio’s latest update. OpenTelemetry tracing displays every step of each run, including model calls, tool usage, and approval nodes, allowing teams to see where processes slow down or fail; the evaluation feature allows testing changes to prompts, models, or tools against proprietary datasets before release; and access boundaries restrict agents so they can only reach systems actively connected by the enterprise.