Your Daily AI Challenges
You’re leading an ambitious AI program within a complex organization. Between the expectations of the executive committee, scattered initiatives, and regulatory pressure, these are the challenges our clients most often describe.
01
No comprehensive view of your AI portfolio
Initiatives are scattered across business units, the IT department, and project teams. It is impossible to obtain a reliable, consolidated view for steering, prioritizing, and making decisions.
03
The trades aren't getting involved enough
Feedback on requirements is informal and varies by department. The AI culture is struggling to take hold, and relevant use cases remain under-identified.
05
Identifying the right AI providers takes time
For each use case, making a “make or buy” decision requires ongoing industry monitoring that your teams don’t have the bandwidth to handle.
02
The ROI of your AI projects remains unclear
ETP returns, model costs, value created: this data exists but is scattered across various sources. Presenting a credible report to the ExCom is a laborious and often imprecise process.
04
The AI Act creates tangible regulatory pressure
Initiatives are scattered across business units, the IT department, and project teams. It is impossible to obtain a reliable, consolidated view for steering, prioritizing, and making decisions.
06
The COMEX reporting lacks structure
Demonstrating the value of the AI program to senior management requires clear, visual, and defensible reporting—something that generic tools cannot provide.
A concrete solution for every challenge
Praxia is designed specifically for the IT departments of large companies. Each module addresses an operational need identified in collaboration with our clients.
01
A single repository that brings together market use cases and your internal projects
From concept to implementation, including make-or-buy decisions by industry. A repository of over 400 AI use cases (predictive AI, generative AI, AI agents). For each use case: market trends, corporate feedback, and recommendations from 4 to 5 specialized vendors.
02
Foster an AI culture, establish a structured process for gathering business requirements, and drive governance
Reports tailored for executive leadership (Executive Committee). An AI governance framework: project prioritization, RACI, structured quarterly reviews, and calls for business ideas. Engage your entire AI community in a collaborative approach.
04
Measure and demonstrate the actual benefits of your AI projects
By business line, by phase (POC, production), with a consolidated dashboard for the Executive Committee. ETP gains, project costs, model costs, and overall impact—all in a single visual report, ready to present to Executive Management.