Enterprise AI Control and Value Scorecard
A single scorecard for evaluating any AI initiative on both what it's worth and how well it's controlled — business benefit, data rights, risk tier, agent permissions, operating cost, and measurable outcomes in one view.
Value and control get reviewed separately — and rarely agree.
Most organizations run two separate reviews for a new AI initiative: a value review in the business, and a risk review in legal, security, or data governance. The two rarely talk to each other. The result is either promising AI work stuck behind a generic risk process, or a genuinely risky agent approved because no one in the value conversation was equipped to flag the exposure.
AI initiatives get scored for ROI without a clear view of data rights or risk exposure
Agent permissions get granted ad hoc, initiative by initiative, with no consistent standard
Business and governance teams score the same initiative differently, using entirely different criteria
Six dimensions, one shared verdict.
The Scorecard rates any AI initiative — a pilot, an agent, a production model — across six dimensions spanning value and control, so approval, scaling, and retirement decisions all rest on the same evidence.
Business Benefit
The value case: what this initiative is actually expected to deliver, and how confidently that estimate is held.
Data Rights
Whether the data behind the initiative is licensed, consented, and permitted for this specific use — not just accessible.
Risk Tier
A consistent classification of the initiative's risk level, from a low-stakes internal tool to a high-stakes customer-facing decision.
Agent Permissions
What the AI agent is actually allowed to do — read, write, transact, or act autonomously — and within what limits.
Operating Cost
The full running cost, not just the build cost, including monitoring, oversight, and model or usage fees.
Measurable Outcomes
Whether success criteria were defined before launch, and whether they're actually being tracked since.
Built for the people who own this problem
Needing one shared view to approve, scale, or hold an AI initiative.
Evaluating data rights and agent permissioning before anything goes live.
Classifying initiatives by risk tier and reviewing what an agent is actually allowed to do.
Wanting the value case represented alongside control requirements, not overridden by them.
Three steps to put it to work
Score all six dimensions
Use the guided rubric to rate each initiative on both value and control criteria.
Set the composite verdict
Combine the two sides into a single read: approve, approve with conditions, or hold.
Re-score at each stage gate
Risk tier and permissions often change as an initiative moves from pilot to production — score again at each gate.
Score your next AI initiative on both value and control.
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