The Decision
The precise moment of operational choice to optimise — stated as a binary or ranked selection, not a theme.
AI Use Case Framework
Is your idea an actionable AI use case — or a hypothesis?
Most enterprise AI stalls on hype-driven selection: loose metrics, vague scope, no data plan. Use the Use Case Sentence Formula and a weighted scoring model to pressure-test your project in two minutes — then download a ready-to-circulate implementation canvas.
39%of orgs see measurable EBIT impact
50%+of GenAI pilots abandoned on unclear value
40–60%compute cost cut with SEEMR routing
01
Scope it with the Use Case Sentence Formula
If you can’t fill these in, it isn’t fundable yet. Watch the sentence assemble as you type.
Scoped Initiative
02
Score it across value, feasibility, and risk
Rate each sub-component 1–5. We average within each dimension (the Microsoft approach) to neutralise optimism bias.
Unlock your prioritisation score
Enter your business email to reveal your score, recommended autonomy level, and a downloadable implementation canvas.
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0 / 100
Verdict —
Composite of business value (40%), feasibility (35%), and risk-adjusted score (25%).
Recommended autonomy target —
How the framework works
From thematic ambition to a fundable use case
A valid use case satisfies a strict four-part anatomy. If any part can’t be defined with empirical precision, classify it as a hypothesis — not an active initiative.
The Workflow
The sequence of actions, handoffs, and systems — including triggers, where output appears, and fallback behaviour.
The User
The specific role or system interface acting on the output, with its constraints, incentives, and interface context.
The Outcome
A defined operational KPI with an established baseline and a rigorous counterfactual measurement plan.
Set the right ceiling
Target autonomy level
Setting autonomy too high before controls exist is a top failure mode; too low leaves efficiency on the table.
Assist
System drafts, human drives
The system acts as a helper so a person works faster or with less cognitive strain — drafting communications or summarising cases. The human stays fully in control of the decision.
Augment
System recommends, human decides
The system provides recommendations, rankings, or scores that influence — but do not make — the human decision, such as claims triage or next-best-action guidance.
Automate
System executes under guardrails; exceptions route to humans
The system executes a decision or workflow step under predefined rules, and humans only handle the exceptions — for example automated routing of low-risk transactions.
Autonomize
Multi-agent dynamic execution across tools
The system plans and executes multi-step actions across tools, dynamically adapting to context and escalating only when constraints or risks are detected.
Browse 119 governed AI use cases — each tagged with its autonomy level, data triage, and ROI blueprint — or see how SEEMR routing cuts the compute cost of running them.
FAQ
AI use case framework — common questions
What is an AI use case framework?
An AI use case framework is a disciplined way to identify, scope, and prioritise AI projects before funding them. It forces every initiative to define a specific decision, workflow, user, and measurable outcome — replacing hype-driven selection with a defensible business case. VDF AI’s framework adds a target autonomy level, a Minimum Viable Data triage, and explicit economic sizing.
How do you prioritise and scope AI projects?
Score each candidate across business value, technical feasibility, and risk, then average the sub-components (the Microsoft approach) to avoid optimism bias. Anchor it to a pre-existing metric with a historical baseline, set the target autonomy level, and pass a data-readiness gate. This tool runs that scoring for you and returns a 0–100 prioritisation score with a Prioritise / Refine / Deprioritise verdict.
What is the Use Case Sentence Formula?
A one-sentence scoping standard: “For [User], improve [KPI] using [AI capability], so that [KPI] improves from [Baseline] to [Target] within [Timeline], while meeting [Constraints].” If any part cannot be stated with precision, the initiative is a hypothesis, not a fundable use case.
How does VDF AI reduce the cost of running AI use cases?
Licensing and tokens are only 20–35% of true total cost of ownership. VDF AI’s Self-Evolving Model Router (SEEMR) routes each task to the smallest capable model instead of one large public LLM, cutting compute cost 40–60%, while 100% on-premise / private-cloud deployment keeps data audit-ready for the EU AI Act, GDPR, and HIPAA.