Use-case definition & selection rationale
Clarify the business problem, intended users, affected people, expected benefit, and alternatives. Where several ideas are in scope, compare value, feasibility, and risk using explicit assumptions.
From business intent to a practical pilot plan
Turn an AI idea into
a plan worth executing.
Decide where AI can help, how it fits the human workflow, and what a pilot must demonstrate. Build a vendor-agnostic plan that connects business value, data readiness, delivery responsibilities, and governance.
Discuss your needs ↗Who it’s for
Business sponsors, transformation teams & delivery partners
Engagement format
Typically 2–4 weeks for one agreed use case
What you leave with
A decision-ready blueprint and bounded pilot plan
When to bring us in
There is enthusiasm for AI, but no shared definition of what success looks like.
- Vendor demonstrations are driving decisions before the business problem is defined.
- A growing list of AI ideas needs prioritization.
- A pilot is stuck between proof of concept and operational deployment.
- A delivery partner needs clear requirements and business-side ownership.
What you receive
Defined outputs.
Usable decisions.
Responsibilities made explicit, evidence connected to decisions, and work shaped around your operating needs.
Current & future workflow maps
Show the task, information flow, human decisions, review points, exception paths, and the proposed AI contribution. Identify where a person remains accountable.
Data & integration requirements
Document source data, access restrictions, quality questions, system dependencies, and ownership. Record readiness gaps that must be resolved before a pilot.
Options & business-case assumptions
Compare practical delivery approaches and vendor dependencies. Make estimated effort, benefits, costs, and uncertainty explicit rather than implying a guaranteed return.
Pilot charter & evaluation plan
Specify scope, baseline, success measures, evaluation responsibilities, safeguards, stop conditions, and evidence required for a release decision. Technical evaluation execution is separately scoped.
Implementation roadmap & handoff
Sequence the work, dependencies, governance decisions, and required roles. Provide a handoff package that a qualified implementation team can assess and use.
How the pieces connect
AI oversight continues
beyond the launch.
Explore a practical lifecycle. The engagement defines the applicable roles, evidence, and review gates for your use case.
What decision or task should AI improve?
A bounded use case, intended users, affected people, and a measurable business outcome.Monitor continuously. Revisit earlier stages as evidence changes.
COGNV’s illustrative engagement model. Actual roles and gates are tailored to the organization.
Illustrative scenario · not a client case study
The situation
An operations team is considering AI-assisted service-request triage.
The work
Map request types, escalation rules, data access, review responsibilities, and the baseline process. Define a bounded pilot with measurable accuracy, handling-time, and exception criteria.
The intended output
A pilot charter and workflow blueprint that make the proposed benefits, risks, human decisions, and release evidence explicit.
To make the work effective
What we need
from your team.
- A business sponsor, process owner, and access to people doing the work.
- The current workflow, relevant sample documentation, and available performance measures.
- Data and technology owners who can clarify access, integration, and implementation constraints.
Scope & assumptions
Agree the boundaries first.
The engagement produces an implementation blueprint. It does not include building software, training models, production deployment, or executing technical validation. Those activities require a separately agreed scope and qualified delivery resources.
After the initial engagement
Support that carries the plan forward.
Provide business-side implementation oversight, requirements clarification, decision facilitation, and pilot readiness reviews. Coordinate with your engineering and evaluation teams under a separate scope.
Before we begin
Questions, answered.
Do we need to choose a platform first?
No. Start with the business need and operating constraints. The blueprint can compare options before a platform decision or work within an existing technology environment.
Can you help prioritize multiple use cases?
Yes, when the portfolio size and comparison method are included in scope. A single-use-case blueprint does not imply an unlimited portfolio review.
Will this prove the AI system works?
The blueprint defines what must be evaluated and who is responsible. Performance and safety claims require actual testing and evidence; that technical validation is separately scoped.
A clear next step
Let’s put the right
problem on the table.
Discuss AI governance, an implementation idea, program recovery, a fractional executive mandate, board advisory, or a board appointment opportunity. Start with a 30-minute conversation to establish fit.
Request a conversation [email protected]+1 202 758 8900
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