What an AI readiness assessment actually looks like

Not a survey. Not a scorecard. A real walkthrough of your tools, your workflows, and where AI actually fits. Here's the process.

Most AI readiness assessments are surveys dressed up as strategy. You answer 40 questions, get a score, and receive a PDF telling you you're at "Level 2" on a maturity model that someone invented.

That's not how we do it. A useful readiness assessment is a working session, not a questionnaire. Here's what it actually looks like.

Step 1: Stack audit

We start by cataloging every tool your team uses regularly. Not just the official tech stack, but the actual one: the spreadsheets, the ad-hoc tools, the things people are doing manually that nobody talks about. This usually takes an hour and always surfaces surprises.

Step 2: Workflow mapping

For each major business function (marketing, operations, client work, reporting), we map out the actual workflows step by step. Where is time going? Where are the handoffs? Where are people doing the same thing repeatedly?

This is where AI opportunities become visible. Not in the abstract, but in specific workflows where automation or AI assistance would reduce time or improve quality.

Step 3: Gap analysis

We look at what's missing: data that's not being captured, integrations that aren't in place, manual processes that have no digital equivalent. Some of these gaps matter for AI. Most don't. We focus on the ones that do.

Step 4: Prioritized recommendations

The output isn't a maturity score. It's a short list of specific, prioritized opportunities with clear rationale: what to do first, what to hold off on, and what's not worth pursuing given your current constraints.

Most of our clients leave with three to five concrete actions. Some of them involve AI tools. Some involve cleaning up existing data. Some involve process changes with no technology component at all.

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We work with mid-market and SMB teams on AI strategy, MarTech implementation, and the messy gap between the two.