Find out which AI projects are ready, and which aren't.
Before AI scales, the operating model has to hold. Most AI efforts stall for familiar reasons: unclear workflows, fragmented data, weak ownership, and governance that arrives after deployment. We help leadership teams assess whether the foundation is ready before new tools multiply old problems.
AI Readiness Review
Leadership teams considering automation or AI in the next 12 months who want the operating model checked before tools multiply old problems.
You receive
Written governance baseline
Decision rights, data-handling rules, and review gates, structured around the NIST AI Risk Management Framework and ready for leadership sign-off.
Mapped current-state workflows
The processes AI would touch, with friction points and ownership gaps called out.
Data-readiness assessment
Where the inputs are complete and consistent, and where data can't be traced back to a trusted source.
Prioritized 12-month roadmap
Sequenced fixes and AI use cases, scored on readiness, effort, and expected value, each marked proceed now, fix first, or not now.
Executive readout
A working session with leadership on what to fix first and what to leave alone.
Scope and your time
- In scope
- Up to 3 core workflows and the systems that feed them.
- Your team's time
- About 6 to 8 hours from leadership, plus a 60-minute interview with each process owner.
- Not included
- Tool selection, procurement, or building AI solutions. Those come after, and only if the review says to proceed.
Led personally by the founder. No handoff to a junior team.
Why AI Efforts Fail
- Broken workflows are automated instead of redesigned
- Conflicting source data weakens outputs and trust
- Ownership and review paths are unclear
- Governance, measurement, and controls arrive after rollout
What Readiness Looks Like
- Current-state workflows are mapped and exception paths are known
- Core data sources are trusted enough for operational use
- Decision rights and human review expectations are explicit
- Success measures and risk thresholds are documented before scale
How ready is your organization? Check in 2 minutes.
Ten questions across workflow, data, and governance. Your answers stay in your browser. Nothing is sent or stored.
0 of 10 answered
How We Assess It
We use a practical sequence that aligns strategy with operational reality: identify workflow friction, review data conditions, define oversight needs, and decide which use cases should proceed now, later, or not at all. The governance work follows the NIST AI Risk Management Framework's four functions (govern, map, measure, manage), so the baseline holds up to board, auditor, and insurer questions.
Decision Standard
An AI use case should not move forward simply because it is technically possible. It should move forward only when the process is stable enough, the data is good enough, and the governance is strong enough to make scale trustworthy.
What the roadmap looks like
Every candidate use case is checked against the same three gates. The decision follows from the gates, not from what the technology can do.
Draft first-pass grant reports
Fix first- Workflow
- Ready
- Data
- Gap
- Governance
- Ready
Program figures disagree across three sources. Consolidate before drafting from them.
Summarize inbound support tickets
Proceed now- Workflow
- Ready
- Data
- Ready
- Governance
- Ready
Stable process, clean ticket history, and a named reviewer for summaries.
Route invoices for approval
Fix first- Workflow
- Ready
- Data
- Ready
- Governance
- Gap
Approval thresholds are informal. Write them down before automating them.
Auto-respond to beneficiary eligibility questions
Not now- Workflow
- Gap
- Data
- Blocked
- Governance
- Blocked
High-risk output with no review path. Revisit after governance is in place.
Illustrative excerpt. Use cases and client details are changed.
What Good Looks Like
Clearer sequencing
Leadership can distinguish what should be fixed first from what is ready for governed rollout.
Weak points found early
Gaps in process, data, or controls surface before they are automated, not after.
More credible adoption
The resulting roadmap is grounded in operational readiness rather than pressure to deploy quickly.
Need to know whether the foundation is ready?
A 30-minute strategy call to talk through your workflows and plans. If a review isn't the right fit, we'll say so.