What if the answer is that we are not ready?

Then we say so and set out what would have to change. That is a cheaper finding than discovering it nine months into a build.

Where do most companies start?

With a process that is high-volume, rule-bound and cheap to correct if wrong. Leading with a flagship customer-facing system is the most common way to stall.

Will this recommend replacing staff?

In our engagements the recommendation is removing repetitive work rather than roles, and we will name the processes we think should stay human.

Diagnostic Engagement

Find Out Whether You Are Ready Before You Spend

We assess your data, processes, governance and risk appetite, then rank AI use cases by return and feasibility — including the ones we recommend you avoid. A readiness assessment costs less than a failed pilot.

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A ranked use-case list instead of disconnected experiments
Explicit guidance on what not to automate
A governance position defensible to a regulator or client
A first project chosen for provable return, not visibility

Verified client outcome

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How ME Law Achieved 469% Organic Growth and Scaled Client Acquisition Through Digital Transformation

+469%
Google Organic Sessions
+535%
Bing Organic Sessions
+205%
Total Sessions
+23,700%
Key Events

ME Law · Results in 12 months · reported from client analytics

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Data & Process Readiness
Whether your data and workflows can…
Use-Case Ranking
Opportunities scored on value, feasibility and…
Governance Review
Review, access control and accountability —…
Implementation Roadmap
A sequence that starts where the…

Is this your situation?

Most AI initiatives stall between pilot and production

A promising demo meets real data, real edge cases and real accountability, and stops. The gap is rarely the model. It is that nobody decided who reviews output, what happens when the system is wrong, and how success would be measured — and software cannot supply a decision that was never made.

Data & Process Readiness
Whether your data and workflows can actually support automation, assessed rather than assumed.
Use-Case Ranking
Opportunities scored on value, feasibility and risk, with the ones to avoid named explicitly.
Governance Review
Review, access control and accountability — the gap that stalls deployments in regulated environments.
Implementation Roadmap
A sequence that starts where the return is provable, so early wins fund harder work.

How we work

A sequence, not a package

01DiscoverProcesses mapped and volume, variability and consequence-of-error measured for each.
02AssessData quality, process maturity and risk appetite evaluated against each candidate use case.
03RankUse cases ordered by return against feasibility, with explicit no-go recommendations.
04RoadmapA phased plan with governance defined before the first build.

Estimate your opportunity

Your numbers, your target. Nothing is assumed on your behalf.

Monthly visitors

Current conversion rate

Average customer value

Target conversion rate

Conversions now

150

At target rate

250

Difference

+100

Annualised value

$3,600,000

Illustrative arithmetic on the figures you entered — not a forecast, a benchmark, or a commitment. What ai readiness assessment can actually move depends on your starting position.

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Part of the Artlogic growth system

AI Readiness is not a silo

Each pillar compounds the others. Visibility without conversion wastes attention; conversion without authority never gets the chance. We build them as one system.

Explore the growth system →

What we measure