An AI use case has no defined success measure.
WORK
Assess the task, data readiness, feasibility and evaluation criteria.
OUTPUT
Use-case assessment and evaluation plan.
Build AI. Govern AI. Secure AI.
AI that has a defined job inside a real workflow.
Design AI-enabled functionality around a business task, connect it to data and applications, and define evaluation, human review and operational controls.
01 /STARTING SITUATIONS
Start with the actual situation.
AI needs to work inside an existing process.
WORK
Design APIs, access, approvals, exceptions and human review.
OUTPUT
Integration and review flow.
The solution must be governed after launch.
WORK
Define monitoring, risk controls and operating responsibilities.
OUTPUT
Governance and operating guidance.
02 /THE WORK
Defined work, reviewable outputs.
Solution design
Define the task, success criteria, data and feasibility before selecting technology.
- Use-case discovery
- Data readiness
- Evaluation criteria
AI applications
Build AI-enabled business functionality with explicit inputs, outputs and review points.
- AI-enabled applications
- Decision support
- Data analysis
Workflow integration
Connect AI with enterprise systems, APIs, approvals, exceptions and feedback.
- Workflow automation
- Enterprise integration
- Human review
Governance & security
Build access, validation, risk and evidence requirements into the solution from the beginning.
- AI governance
- AI security
- Operational monitoring
03 /REVIEWABLE OUTPUTS
Outputs tied to the agreed scope.
- 01Use-case and feasibility assessment
- 02Solution prototype and evaluation criteria
- 03Integration and access design
- 04Human review and exception flow
- 05Governance and operating guidance
NEXT STEP
Define the right first engagement.
The first discussion defines the objective, scope and expected outputs.
Discuss the work