Frame objectives
Clarify business issues, teams, friction points and current indicators.
AI diagnostic for business: roadmap, ROI and priorities
Identify high-potential processes, assess data and constraints, estimate gains and leave with a prioritised AI roadmap.
An AI diagnostic supports an investment decision
It is not a tool demonstration. TeamIA assesses processes, data, constraints and expected gains to recommend what should be automated, deferred or rejected.
Map processes
Review tasks, tools, data, approvals and business dependencies.
Assess use cases
Compare value, feasibility, risk, integration effort and required supervision.
Prioritise the roadmap
Select first projects, estimate gains and define the next decisions.
Decision-ready deliverables
- Map of priority processes and friction points
- Value, feasibility, risk and data matrix
- Estimate of gains, costs and success conditions
- Roadmap with pilots and next steps
Duration, participants and effort
The format depends on the number of processes and the required level of detail. It involves business owners, users and, where needed, data or IT owners.
- Focused interviews and operational friction
- Systems, data, volumes and access constraints
- Value, feasibility, risk and budget assessment
- Prioritised recommendations and metrics
The diagnostic can also prepare a funding application
Depending on location and eligibility, schemes in France or Luxembourg may support a study, proof of concept or first implementation. Eligibility must be checked before commitment.
Questions about an AI diagnostic
How do a diagnostic, workshop and proof of concept differ?
A workshop identifies needs, a diagnostic validates value and feasibility, and a proof of concept tests a technical hypothesis on a limited scope.
What deliverables does the company receive?
A map of opportunities, prioritised use cases, gain assumptions, data and integration requirements, and an actionable roadmap.
What determines diagnostic pricing?
Pricing depends on the number of processes, teams and systems assessed and the expected level of detail.
Does a diagnostic require building an AI agent?
No. It may show that conventional automation, better data or a process change is the better decision.
Let us discuss your business process
A first conversation helps define the need, expected value and practical next steps.