The right AI model usage isn't one where AI is exploited to its fullest potential. The right model is one where the organization maintains a degree of robustness to absorb ambiguity, verification, rework, and human oversight.

We assess your AI use cases using an empirical model based on experience in AI projects and industrial resources management.

We enable you to map each use case on this curve and identify the actions needed to return to the optimal position..

Our model analyzes the key variables that determine the actual performance of an AI use case:

• Personal and collective maturity level vs. AI tools

• Task complexity

• Effective model capability

• Quality of the human-AI exchange protocol

• Effective human expertise

• Quality of output

• Estimated true end-to-end total cost

• Human capability debt

• The results that you obtained

Following the asessment, you will have an actionable view:

• Mapping of your AI use cases

• Usage pressure score per activity

• AI governance recommendations

• Prioritized action plan

• Plan for preserving human capabilities.

Are you a leader / an executive?
The diagnostic answers the strategic question:

• Does AI truly increase the value produced by the organization without creating new critical dependencies?

• You gain a clear understanding of the risks, hidden costs, potential gains, and governance trade-offs.

Objective: make AI a true leverage for a sustainable performance, not a cause for fragility

Are you responsible for technology or in charge of a digital transformation?
The asessment helps you streamline your AI architecture:

• Which model for which use case?

• Which tasks should be automated, assisted, or left under human control?

• What controls should be implemented?

• How could you limit our reliance on large, general-purpose models?

• How could you build a scalable, learning, and controlled architecture?

Objective : choose the most sober models that are truly capable, with the right level of governance and security.