The AI Business Review
Every quarter, we show up with the math. Hours saved, dollars in or out, what’s working, what’s not, what we’re doing next quarter.
Why this exists
The AI investments that get cancelled inside SMBs are rarely the bad ones. They are the ones that nobody measured. A workflow that saved an associate four hours a week for two quarters gets killed in a budget review because the CFO has no number in front of her, and the line item looks like discretionary spend. Meanwhile, a workflow that’s actively making errors limps along because no one is looking. The same gap, two opposite failure modes.
The Quarterly AI Business Review prevents both. It puts the numbers in front of leadership on a regular cadence, in a format they can defend in a board meeting or to a senior partner. It separates the AI investments that are working from the ones that aren’t, with evidence. And it surfaces what comes next — not as a feature wish list, but as a prioritized roadmap with effort estimates.
The full-format ABR is the meeting where the AI program becomes a line in your operating plan, not a curiosity in IT’s budget. That is the point.
What’s in it
The ABR is a written deliverable plus a 90-minute meeting. The deliverable is structured the same way every quarter, so you can compare across quarters cleanly. Sections:
- Hours saved by workflow. Each productized workflow — RFQ response, document review, knowledge interview, ERP query, whatever you’ve deployed — measured before-and-after with real users. We show the methodology. We show the sample size. We show the variance.
- $/output for productized workflows. Cost per proposal section, per RFQ response, per discovery memo, per ticket triaged. Includes labor, license, and our share. Lets you compare AI-assisted output against the alternative cost.
- License utilization vs. spend. Microsoft Copilot, ChatGPT Enterprise, your other AI vendors. Who has a license. Who is using it. What’s it costing per active user. Where to cut.
- Adoption by department. Number of users active by team. Trend. Where adoption is flat and what we recommend.
- Governance posture score and drift report. Where the policy and the practice agree, where they don’t, and what changed since last quarter.
- Risk reduction. DLP hits attributable to AI-context activity, shadow AI incidents detected, near-misses logged and resolved. Insurance-disclosure-ready.
- Roadmap for next quarter. Named workflows. Effort estimates. Dependencies. The thing leadership signs off on at the end of the meeting.
How we measure
We don’t run lab benchmarks. We measure real workflows with real users.
The methodology, in one paragraph: when we deploy a workflow, we measure the baseline time and accuracy with the team that’s about to use it — three to five people, three to five real cases each, before the workflow goes live. After deployment, we re-measure the same team on the same kind of work, at 30 days, 60 days, and quarterly. The numbers in the ABR are the actual operating-state measurements, not the pilot. We are honest about variance and sample size. If a number isn’t well-supported, we say so and tell you what we’re doing to firm it up. A bad measurement that overstates the win is worse for everyone than no measurement.
Sample ABR preview
Who gets the ABR
Full-format ABR is included in Operate and Strategic. Foundation clients get a compressed version — 45-minute meeting, two-page deliverable — that covers the same data with less depth.
Book an AI Readiness Assessment
Ready when you are.
Three weeks. Fixed fee. A real report and a 90-day roadmap. You keep it whether you hire us or not.