The case for an independent AI ROI analysis

Every AI vendor will give you a benefit case. It will be inflated. They will compare against fictional baselines, count benefits multiple times, and assume scale that has never been observed in any deployment of their product.

You know this. Your CFO knows this. Your board knows this. And yet most AI investment decisions get made on the vendor’s number, because nobody else in the room has the time or the analytical chops to produce a defensible alternative.

That’s the problem this post is about, and the fix is unsexy: hire someone independent to build the benefit case before you sign the contract, and re-quantify it after deployment. Not because vendors are dishonest. Because the structure of vendor benefit cases is structurally biased, and you need an analysis whose incentives are aligned with the integrity of the number, not the close of the deal.

Why vendor benefit cases are structurally wrong

Vendor benefit cases fail in three predictable ways.

1. The baseline is fictional.

A vendor will tell you their AI saves “30% of time spent on customer service tickets.” Compared to what baseline? Usually: an industry-average baseline pulled from a McKinsey paper, or a statistic from a different vendor’s customer who used the tool in a different way for a different ticket type.

Your actual baseline (your team’s real cycle time on real tickets, segmented by ticket type, weighted by complexity) does not appear anywhere in the calculation. The vendor is comparing their tool to an imaginary version of your operation.

2. The benefits are double-counted.

A common pattern: an AI tool claims to save time AND increase quality AND reduce headcount. So the benefit case adds up time savings (in dollars) PLUS quality improvements (in dollars) PLUS headcount reduction (in dollars).

But these are usually the same dollar three times. If you save time by using the AI to write the email faster, you cannot also count the headcount reduction that comes from needing fewer people to write emails. One or the other.

The vendor’s benefit case adds them anyway. Most procurement teams don’t catch it because the math is buried in a footnote.

3. The scale is unprecedented.

Vendor decks routinely show benefit projections that assume the AI will be used by 80% of the team for 80% of relevant tasks within 12 months. No deployment of any AI tool, ever, has hit that adoption curve in the first year.

Real adoption curves are slow, uneven, and front-loaded with the easy use cases. A defensible benefit case sizes the first 12 months (not the steady-state) and acknowledges that most of the projected benefit is back-loaded into year two and beyond.

What an independent analysis actually looks like

The deliverable from an independent ROI engagement isn’t “we agreed with the vendor” or “we disagreed with the vendor.” It’s a different document entirely.

It’s built from your operating data: actual cycle times, actual costs, actual ticket volumes. The assumptions are explicit and traceable. Every input has a source you can defend in a board meeting. There’s a side-by-side comparison: vendor claim versus our analysis, line by line, with the deltas explained.

There’s a risk-adjusted range, not a single point estimate. Best case, expected case, worst case. Single-number ROI estimates are a rhetorical move, not an analytical one. Yours will have honest bounds.

And critically: there’s a measurement plan for after you sign. What to track, on what cadence, who owns the report. So that 90 days post-deployment, you can answer “is it working?” with data instead of vibes.

Why post-deployment matters more than people expect

Most independent ROI work focuses on the pre-contract analysis. That’s half the value.

The other half is the re-quantification three months after deployment. Did the actuals match the projection? If not, where’s the gap? Adoption slower than expected? Use cases narrower than scoped? Quality of output below threshold?

The honest answer to “is this working?” three months in is the most valuable financial data you can have on an AI investment. It’s also the data nobody collects, because nobody set up the measurement plan upfront. The vendor doesn’t want it. The internal champion doesn’t want it. The procurement team has moved on to the next deal.

If you don’t measure, the original benefit case becomes mythology. It gets quoted in board decks for two years. The renewal happens on inertia. By the time someone notices the actuals don’t match, you’ve spent another year of license fees on a tool that’s underdelivering.

When this is worth doing

For AI contracts above $100K ARR, an independent analysis is cheap insurance. Two weeks of fixed-fee work pre-contract, a one-week refresh post-deployment. Total cost is a fraction of a percentage point of the contract value.

For contracts below $50K ARR, it’s probably overkill. The analytical overhead exceeds the risk-adjusted value of being right.

Between $50K and $100K ARR, it depends on visibility and stakes: if the contract decision is going to a board, or if the AI initiative is part of a larger investor narrative, the analysis pays for itself in defensibility alone.

What this is not

It’s not a vendor selection exercise. We’re not picking the right AI tool. That’s our AI Strategy engagement. The ROI analysis assumes you’ve already chosen the tool and are about to sign the contract.

It’s also not a procurement-led negotiation. The output isn’t “let’s get the vendor to lower their price.” The output is “here’s what this is actually worth, and here’s whether the contract terms reflect that value.”

The honest version

The honest version of every AI contract conversation goes like this: somebody believes the vendor’s number, somebody else suspects it’s wrong, nobody in the room has the bandwidth to produce a real alternative, and the deal closes anyway. Twelve months later, when the numbers don’t match the projection, everybody quietly stops talking about the original benefit case.

The fix isn’t more skepticism. It’s a structured analysis whose incentives are aligned with being right, not with closing.

If you have an AI contract on the table and the benefit case feels off, that’s the conversation we have on a discovery call. Email us at hello@antlerwing.com and tell us what you’re looking at.