Most organizations do not suffer from a shortage
of AI ideas. They suffer from inconsistent intake.
A use case appears in one department, a
Copilot experiment starts in another, and leadership cannot
quickly see the data sensitivity, action level, source
readiness, owner, or approval path. Governance becomes a
debate instead of an operating process.
The intake begins with six practical fields: use
case, business goal, data sensitivity, action level, source
readiness, and business owner. An answer-only HR policy
assistant with approved sources and a named owner
scores as a reasonable mini-audit candidate. The assistant
does not approve it; it creates a consistent
packet for a human decision.
A customer email drafter introduces customer data, scattered
sources, and an owner who is not fully
confirmed. The recommendation changes from ready candidate to
needs shaping. A mini-audit can clarify sources, approval,
customer-facing boundaries, and ownership before implementation work begins.
Invoice approval automation combines financial transaction data, execution
authority, unclear sources, and no owner. The intake
correctly marks it high risk and recommends deferring
or redesigning. This is a crucial governance outcome:
a disciplined no can prevent a costly prototype
that was never ready to exist.
The operating model names the roles a real
review needs: business sponsor, workflow owner, IT or
security owner, source owner, and approver. It also
distinguishes what the assistant can do from what
leaders must decide. Governance becomes a queue with
ownership and evidence, not a policy document that
sits outside delivery.
Queue examples show the portfolio effect. Some ideas
are ready for a mini-audit, some need source
cleanup, and some should wait. The same intake
language makes proposals comparable and helps scarce technical
and governance capacity move toward narrow, owned, evidence-ready
use cases.
This demonstration uses synthetic use cases and a
lightweight scoring model. It is not legal, compliance,
privacy, or security certification. The value is a
practical governance front door that can be adapted
to company policy and used to select the
next safe, valuable experiment.
For CIOs and operating leaders, the value is
fewer random pilots, earlier risk visibility, clearer ownership,
and a faster path to the use cases
that are actually ready. Governance should reduce waste
and improve delivery quality, not merely add review
meetings.
If AI activity is already happening in pockets,
start with a one-week, three-thousand-five-hundred-dollar AI Governance Intake
Mini-Audit. We score one candidate workflow, inspect source
readiness, define ownership and boundaries, and return a
practical recommendation: proceed, reshape, or defer. Bring one
proposed use case. We will turn it into
a decision-ready governance packet.