GenAI agreements are being signed faster than their market matures: token pricing that moves quarterly, seat commitments ahead of adoption, and contract terms written by vendors sprinting for land. Evidence and structure are the only anchors.
This engagement is bought by organizations committing real money to OpenAI, Anthropic, Microsoft Copilot, Gemini, or AI platform deals: token commitments, seat licenses, and enterprise agreements in a market where list prices move quarterly and lock in costs more than it appears.
It fits teams facing multi year AI commitments ahead of stable adoption data, and procurement leads who want flexibility, price protection, and exit terms in contracts the vendors wrote for a land grab.
GenAI deals carry risks the older vendor playbooks never had:
Usage evidence, flexible structures, and short commitment horizons are the anchors in a repricing market, and the negotiation pursues all three.
The engagement runs four workstreams: the position is baselined from what you own, deploy, and need, targets are benchmarked per deal element, the vendor's moves are anticipated with responses prepared, and the execution runs through signature.
| Deliverable | What it contains |
|---|---|
| Position baseline report | The spend and entitlement picture with your requirements, alternatives, and GenAI's predicted agenda. |
| Benchmark and target sheet | Target pricing and terms per deal element with walk away lines, measured against comparable agreements. |
| Negotiation playbook | Sequencing, fiscal timing, anticipated vendor moves, and scripted responses. |
| Written proposal assessments | Every proposal assessed against the targets with recommended responses through the cycle. |
| Final contract review | Pre signature confirmation that agreed positions are correctly reflected in the paper. |
The account team runs dozens of negotiations a year to your one, with institutional memory of what worked on customers like you. The gap is closed by preparation: a baseline the vendor cannot dispute, targets from deals the vendor knows exist, and timing that uses its own fiscal pressure against it.
The benchmark data comes from 500+ engagements across 11 enterprise vendors, held to current quarter reality rather than folklore. Every target we set is a number we have seen achieved by comparable customers.
Independence keeps the strategy honest: no reseller margin, no implementation revenue, no referral fees from this vendor or any other. When deferring, splitting a bundle, or walking a category is the right move, that is the recommendation.
The engagement runs fixed price, all inclusive, or on contingency at 25 percent of the savings we deliver: you keep 75 percent, and if we save you nothing, you pay nothing.
AI agreements on the record.
BBVA avoided a three year AI lock in and cut costs 28 percent.
✓ Published case studyA European insurance group rescoped its AI engagement for 30 percent savings.
✓ Published case studyA San Francisco financial institution gained flexibility and cut projected Azure OpenAI spend.
✓ Published case studyAn enterprise SaaS provider structured its OpenAI agreement for flexibility.
Any substantial commercial event with this vendor: renewals, new purchases, expansions, and restructures. The engagement builds positions per deal element, benchmarks them against comparable agreements, and supports execution through signature.
From benchmarked targets built on comparable agreements: discount thresholds, structural terms, and concessions actually achieved by customers of your profile. List price framing stops working when the reference point is real deals.
Two to three quarters out for full leverage build. The baseline and targets land within the first month, so even compressed timelines leave you negotiating from positions rather than reactions.
Your team keeps the chair and the relationship. We prepare every exchange: written assessments of each proposal, meeting preparation with anticipated tactics, and a final contract review before signature.
Because the market reprices underneath the contract: model economics improve quarterly, list prices fall, and capabilities shift between vendors. Multi year lock in at today's prices is expensive by default, and flexibility is worth more than discount.
From adoption and usage evidence, on short horizons, with expansion gated on measured value. A published BBVA engagement avoided a three year lock in and saved 28 percent by exactly this discipline.
OpenAI, Anthropic, Microsoft Copilot and Azure OpenAI, Google Gemini and Vertex AI, and the surrounding platform and credit structures. Vendor competition is real and current, and it is your leverage.
Fixed price, all inclusive, covering all four workstreams, up to four advisory calls, and email support, or contingency at 25 percent of the savings we deliver: you keep 75 percent, and if we save you nothing, you pay nothing.
Usage sized, price protected, exit preserved, and the vendors' own competition doing the discounting.
One letter a month. Negotiation moves, audit signals, and price book shifts.