The AI Audit: What We Actually Look For in 2 Weeks

Before we run a 90-day transformation, we need to know where to aim. That’s what the 2-week AI audit is for. It’s our entry point with every company — low commitment, high signal. By the end, you have a prioritized plan for where AI will create the most value in your organization, and a realistic assessment of what it will take to get there.

Here’s what actually happens in those two weeks.

Week 1: Understanding How Work Actually Gets Done

Workflow mapping

We map the real workflows, not the ones on the process documents. Every company has a gap between how work is supposed to flow and how it actually flows. We sit with teams — engineering, product, marketing, support, operations — and trace how a piece of work moves from idea to completion.

Where are the handoffs? Where does work sit waiting for approval? Where do people context-switch between tools? Where is someone manually doing something a script could handle?

We’re not looking for “AI use cases” at this stage. We’re looking for friction. AI use cases emerge naturally once you understand where the friction lives.

Tool inventory

What tools does each team use? How do they overlap? Where is data trapped in one system that another team needs? Most companies we walk into have 3-4 tools doing roughly the same thing across different teams, with no data flowing between them.

The tool inventory isn’t about replacing software. It’s about understanding the information architecture — where data lives, how it moves (or doesn’t), and where AI could connect the gaps.

Bottleneck analysis

Every company has a primary bottleneck that constrains everything downstream. In engineering-heavy companies, it’s usually product — engineering can build faster than product can spec. In sales-driven companies, it’s often operations — deals close faster than the team can deliver.

We identify the bottleneck and trace its downstream effects. This matters because the highest-value AI intervention is almost never where people think it is. Teams usually want to optimize their own workflows. The real leverage is often in unblocking the constraint that’s holding the entire system back.

Week 1.5: Assessing Readiness

Quick win identification

While we’re mapping workflows, we’re also looking for quick wins — things we can ship in the first week of a transformation that prove the value immediately. These are stuck products, manual processes, or cost centers where AI can deliver an obvious result fast.

Quick wins aren’t the point of the transformation. They’re the proof that earns the mandate for deeper change. We need at least 2-3 high-confidence quick wins before we recommend proceeding.

Org readiness

This is the part most audits skip, and it’s the part that matters most. Technology readiness is table stakes. Org readiness determines whether a transformation will actually stick.

We assess:

Leadership appetite. Do the founders/CEO understand what AI transformation actually requires? Are they willing to restructure, not just optimize? Have they personally used AI tools, or is this an abstract initiative they’re delegating?
Middle management dynamics. Middle managers are where transformations go to die. They have the most to lose from restructuring and the most power to slow-walk adoption. We need to understand who will champion the change and who will resist it.
Team culture. Is this a company where people experiment and ship, or one where everything needs three approvals? AI transformation requires a tolerance for speed and imperfection that some cultures don’t have yet.
Technical foundation. Not “do you have the right tech stack” — more like “can your systems support the data flows that AI needs?” If everything lives in spreadsheets and email threads, we need to account for foundational work in the plan.

Week 2: Synthesis and Prioritization

Impact mapping

We take everything we’ve learned and map it to business impact. For each potential AI intervention, we estimate:

Value. What’s the measurable business outcome? Revenue, cost reduction, velocity, quality.
Feasibility. How hard is this to implement? What dependencies exist?
Time to value. How quickly will this deliver results? Days, weeks, months?
Org change required. Does this need workflow changes, role changes, or structural changes?

The 90-day plan

The output of the audit is a prioritized 90-day transformation plan. Not a slide deck of possibilities. A sequenced plan with:

Week 1 quick wins — the proof-of-value projects that earn the mandate
Phase 1 (weeks 1-4) — leadership conversion, engineering onboarding, first department-wide rollouts
Phase 2 (weeks 4-8) — cross-department extension, structural changes, measurement framework
Phase 3 (weeks 8-12) — org restructuring, consolidation, institutionalization
Dependencies and risks — what could go wrong, what needs to be true for this to work
Expected outcomes — specific, measurable targets for each phase

What the Audit Is Not

It’s not a technology assessment. We don’t evaluate your tech stack and recommend new tools. The tools are the easy part.

It’s not a strategy document. You won’t get 50 pages of analysis and recommendations that sit in a Google Drive folder. You get a plan that we’re prepared to execute starting the following Monday.

It’s not a sales pitch disguised as consulting. If we don’t see a path to 3-10x improvement, we’ll tell you. We’ve walked away from engagements where the org wasn’t ready or the opportunity wasn’t there. The audit exists to give both sides the information needed to make a good decision.

Who It’s For

The audit works best for companies with 50-500 people, a leadership team that’s genuinely curious about AI (not just checking a box), and at least one meaningful bottleneck that’s constraining growth. If you’re already shipping fine and just want marginal efficiency gains, this probably isn’t the right fit. We’re built for companies that need a step change.

Two weeks. A clear picture of where you are, where the leverage is, and what it takes to get there. Everything after that is a choice.