Service · Diagnostic

AI readiness assessment

Two weeks. Fixed fee. A costed roadmap that tells you which AI opportunities are worth funding, which are traps, and what has to be fixed in your data before either question matters.

Most mid-market companies do not have an AI strategy problem. They have a sequencing problem — several plausible ideas, no shared way of comparing them, and no honest view of whether the underlying data can support any of them.

The assessment exists to end that argument with evidence rather than opinion. It is deliberately small: two weeks, a fixed price, and a scope tight enough that you can approve it without assembling a steering committee. What you get back is yours whether or not we ever work together again.

25%
of companies have moved more than 40% of their AI pilots into production
Deloitte, 2026
84%
have deployed AI without redesigning any of the work around it
Deloitte, 2026
60%
of organisations generate no material value from AI at all
BCG, 2025

What the assessment covers

1. Workflow mapping

We sit with the people doing the work — not only the people who manage it — and document where time actually goes. Review queues, rekeying between systems, documents read by hand, decisions that wait on one person's availability. This is where the real opportunities are, and they rarely match the ones on the leadership team's list.

2. Use-case scoring

Every candidate is scored on the same four axes: business value, implementation effort, data availability, and risk exposure. The output is a ranked list with the reasoning attached, so your team can re-run the exercise on new ideas after we've gone.

DO FIRST High value, low effort SEQUENCE Worth doing — after the data work FILL-IN Only if capacity allows DECLINE Say no explicitly, in writing Compliance review triage 11-day queue · data already structured IMPLEMENTATION EFFORT → BUSINESS VALUE → Bubble size = data readiness Blocked on data or governance work Below the line
Candidates are plotted, not listed. Position gives value against effort; bubble size gives data readiness, which is what most often moves a promising use case from "do first" into "sequence later". The scoring logic is documented so your team can plot new ideas after we've gone.

3. Data and systems readiness

Data quality is where mid-market AI projects most often die quietly. We assess whether the data that a proposed use case depends on actually exists, is accessible, is accurate enough, and can be used lawfully for the purpose you have in mind.

4. Governance gap analysis

For regulated businesses this is the section that determines whether anything ships. We assess current practice against recognised frameworks — the NIST AI Risk Management Framework and ISO 42001 among them — and identify the specific policies, controls and documentation you would need before a model touches a customer decision.

5. Capability and adoption readiness

Who in the organisation can maintain what gets built. Where the internal champions are. Where the scepticism is concentrated and whether it is well-founded. A technically sound system that nobody trusts is a failed project with good documentation.

What you receive

  • A prioritised opportunity map with scoring rationale your team can extend
  • A costed implementation roadmap, sequenced by dependency rather than enthusiasm
  • A data and systems readiness report naming specific gaps and remediation
  • A governance gap analysis against NIST AI RMF and ISO 42001 control areas
  • A written recommendation on what to do first — including, where it applies, the recommendation to do nothing yet

Every artefact is written in a format your team can read, edit and extend without us. Nothing depends on a proprietary platform we own.

What it costs

For context, here is what the same diagnostic scope costs across the market:

Fixed fee
TechVisory — two-week scoped assessment, priced at the lower end of the boutique range
$25k–$75k
Typical senior-led boutique diagnostic and roadmap engagement
$150k+
Big 4 and global strategy firms, frequently reaching $400k for multi-division scope

We quote a specific number once we know the size of the organisation and how many business units are in scope. There is no charge for that conversation.

Not sure whether you need one yet?

A 30-minute call is usually enough to tell. If the answer is that you don't, we'll say so.

Book a conversation →

Who this is for

Companies roughly between 50 and 1,000 people, or in the $50M to $2B revenue band, where someone has been asked to produce an AI plan and does not want to spend a quarter and a six-figure fee arriving at a slide deck.

It is a particularly good fit if you operate under regulatory supervision — financial services, insurance, healthcare — because the governance work is built into the diagnostic rather than sold as a separate follow-on engagement.

Who it isn't for

If your requirement is deploying a vendor tool at scale in a stable environment, a certified implementation partner will do it faster and cheaper. If you need a multi-country programme with in-country legal coverage, you need a firm with that bench. We would rather say so at the first call than three weeks into a contract.

Then what

The assessment is designed to make the next decision obvious

01

Assessment

2 weeks · fixed fee

You end with a ranked roadmap and an honest view of what your data and governance can currently support.

02

Pilot build

6–8 weeks

One use case into production with the guardrails and evaluation that make its output safe to rely on. See architecture services →

03

Scale and enable

Ongoing

Further use cases and your people trained to own delivery. See enablement →

Start here

Tell us what you're trying to fix.

A short description of the organisation and the problem is enough for us to say whether an assessment is the right next step — or whether something smaller is.