AI readiness assessment
Most institutions are stuck between experimentation and scale. The AI readiness assessment is the paid diagnostic that tells you exactly where you are ready and where you are not, and hands you the sequenced plan to move from pilots to production.
Who it is for
Leadership teams and boards that have run AI pilots but cannot get them to production, or that want a clear-eyed baseline before they invest.
What you get
- A readiness baseline across strategy, data, talent, governance, and infrastructure
- The specific gaps between where you are and production-scale AI
- A sequenced, prioritized roadmap to close them
- A board-ready read of risk, opportunity, and what to do first
How it works
- Assess readiness across the dimensions that decide success
- Find the real gaps, not the comfortable ones
- Sequence the fixes by leverage
- Hand you a plan you can act on immediately
Questions
Why start with an assessment?
What do I walk away with?
Common questions
Can someone give us an independent read on our AI readiness before we take this to the board?
Yes. That is what a readiness assessment is for. An outside, unsentimental view of your data, systems, processes, skills, and governance, measured against the outcomes you actually want. You get a plain statement of what is feasible now, what has to be fixed first, what it will take to run, and what I would not attempt in your environment yet. Boards tend to trust that more than a vendor proposal, because it names constraints instead of selling around them.
Our core systems are fifteen years old. Can AI do anything for us before we replace them?
Usually yes. Old systems are a constraint, not a veto. A lot of value sits in the layer around them: document and case handling, reconciliation, exception review, reporting, and customer response. Those can be automated without touching the core, which is also the lower risk way to build internal confidence before a larger program. What I check first is whether data can be pulled out reliably and results put back in. If that works, there is worthwhile work to do now.
How long does a readiness assessment take and what do we get at the end?
It starts with a working session on the outcome and moves quickly, because the goal is a decision rather than a document. You get a ranked set of opportunities with feasibility and effort, the gaps that must close first, an honest read on data quality, a governance and risk view, and a sequence you can defend to a board. Timelines depend on the size of the estate and how much is already known internally. Pricing is scoped to the engagement.
We have a small team drowning in manual review while volume keeps growing. How do we find out what can be automated?
Measure the queue before buying anything. Sample a few weeks of the work, classify it by type, and see what share is repetitive and rule bound, what needs judgment, and what is genuinely exceptional. In most review functions the repetitive share is large, and that is where automation pays without touching the judgment calls. Then design so the system triages and prioritizes while your people decide. That protects throughput and accountability at the same time.
Discuss the scope
Discuss a strategic decision.
Share your objective, the decision you face, and your timeline. We can discuss the relevant work, the deliverables, and whether the engagement fits.
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