Platform / Early exposure screen
Find the questions that deserve a closer look.
A short screen should not pretend to settle a complex legal classification or discover every operational risk. EU AI Fit starts proportionately, then gives workspace teams a deeper, retained assessment when the system's context, effect or uncertainty justifies it.
Why this matters
Most teams begin with a product name. The Act begins with purpose and context.
The same model can support a low-impact writing assistant, a workplace decision or a safety function. A useful first step therefore asks what the system does, who it affects, how its output is used and where it is deployed.
EU AI Fit separates obvious scope and transparency signals from deeper questions about affected people, data, fairness, accuracy, security, human oversight, suppliers and operation. Uncertainty remains visible instead of being converted into a reassuring score.
Who it is for
Useful before a formal assessment begins.
- Teams discovering AI use across the organisation
- Product and procurement owners considering a new system
- System owners and reviewers examining operational exposure
- Advisers scoping an initial client conversation
How the work moves
From an initial use case to a reasoned next step.
- 01
Screen the use
Capture enough purpose, context, affected people and decision influence to identify the principal EU AI Act signals.
- 02
Deepen the assessment
In the workspace, examine ten exposure areas spanning rights, data, fairness, reliability, security, oversight, transparency, suppliers, operation and classification routing.
- 03
Record human decisions
Resolve material findings, link risks or evidence work, record rationale and require owner or administrator approval.
- 04
Govern what follows
Treat suggested risks as hypotheses, assign controls and owners, set review dates and reassess after material change.
In this scenario
A recruitment plug-in described as ‘just productivity software’
A people team wants to add an AI plug-in that ranks applications before a recruiter reviews them.
The free screen asks about the decision influenced and the people affected, not merely whether a human remains somewhere in the process.
The workspace assessment then examines fairness testing, reversibility, human intervention, protected data, supplier evidence, complaints, monitoring and foreseeable misuse. Credible concerns enter the risk register as unapproved hypotheses.
The team can see the initial signal, the deeper findings, the decisions made and the work still required. It does not yet have a final legal conclusion—and the interface says so.
What is retained
Keep the answer trail behind the exposure result.
The free check can email this record or carry it into a workspace assessment.
- Dated public-screen answers
- Versioned workspace exposure map
- Finding resolutions, rationale and approval
- Suggested risk hypotheses selected for formal review
- Review date, history and material-change trigger
Source basis
The official material behind the workflow.
Source review updated 31 August 2026. Read our editorial and regulatory review policy, check the current source and obtain qualified advice for your circumstances.
- Regulation (EU) 2024/1689
The official consolidated legal text, including the 2026 amendments, and starting point for every assessment.
- Article 6 and Annex III
Official classification rules for high-risk AI systems and the documented-assessment requirement.
- Article 50 transparency guidance
Commission guidance on transparency obligations applying from 2 August 2026.
Next step
Start proportionately, then deepen where the facts lead.
Run the free screen, keep your answers and use the workspace to turn material exposure into reviewable decisions and owned work.
Start the exposure check