AI is already at work. Who is accountable for what it does?
Pilots multiply. The decisions needed to release them stay unresolved.
Give the next AI project rules people can actually use.
Choose a use case worth taking beyond the demo
Compare value, effort, data readiness and risk before investing.
Set boundaries before business data enters the tool
Define permitted data, access, actions and decisions that remain with people.
Define what must pass before release
Agree representative tests and acceptance criteria for the intended use.
Keep someone accountable after launch
Establish monitoring, issue handling, change approval and cost review.
Questions before approving the next AI project
Do we need this before every AI project?
Every project needs proportionate ownership and controls. A simple use case may need a small review; a consequential one needs deeper evaluation.
Will you recommend tools?
Where useful, after defining the use case, data, users and constraints.
Can you assess an existing pilot?
Yes. We can review purpose, access, quality, cost, failures and readiness for wider use.
Do you provide legal compliance certification?
No. We support implementation and evidence. Your qualified legal, privacy and security advisers retain the relevant approval roles.
Can you help write practical policies?
Yes. The emphasis is usable guidance tied to real workflows, permissions and escalation.
Can we proceed with a small pilot?
Yes, when its purpose, data, boundaries and acceptance criteria are clear.
Who needs to be involved?
A business owner, relevant users and the people responsible for data, technology and any applicable risk decisions.