AI is no longer just influencing who wins the deal; it’s influencing the deal itself. Buyers are using it to prepare for negotiations, test concessions, challenge terms and negotiate what goes into the final contract.
In AI Revenue Institute (AIRI)’s survey of 521 B2B purchasers and purchasing influencers, 81 percent said their organizations are already using, testing or planning to use AI in vendor negotiations and contracting within the next 12 months.
That includes:
26 percent who are actively using AI in negotiations and contracting
Another 26 percent who are testing it in select deals
29 percent who plan to start within the next 12 months
Only 5 percent said they don’t expect to use it.
This doesn’t mean an AI chatbot will soon be closing four in five deals. It means B2B buyers are using AI to add speed and depth to work they already do to prepare for negotiations and contracting.
In short, AI gives them more firepower, faster. B2B buyers can use AI to analyze more of the deal, compare more alternatives and test more counterarguments in far less time. And they don’t have to wait until the formal negotiation or contract review begins. They can start organizing their position while they’re still evaluating vendors, so they arrive ready to negotiate not just price, but scope, service levels, risk, concessions and contract terms.
This raises the bar for your revenue team. If your buyers are coming to the table faster and better prepared, you need to be just as ready.
AI turns evaluation into negotiation prep
The same AI analysis buyers use to evaluate vendors can also prepare them to negotiate. A B2B buyer can compare competing proposals across price, features, scope, service levels, implementation commitments and other factors, identifying where each vendor is stronger, weaker or potentially open to challenge.
AIRI’s research found that:
54 percent of B2B buyers use AI to build side-by-side pricing or feature comparison matrices.
58 percent use it to learn or verify evaluation factors.
62 percent use it to fact-check sales claims against public sources.
Those activities can produce a better-informed negotiator, not just a better-informed buyer.
One AIRI survey respondent and B2B buyer described using AI to summarize vendor calls, compare proposals and benchmark pricing against market data. Another said they upload vendor quotes and analyze the options on a pros-and-cons basis.
Imagine what that might look like in practice. A B2B buyer asks AI to compare three finalists. It finds that your proposal includes stronger implementation support but costs more, a competitor offers more favorable service levels, and another has fewer restrictions in its standard contract.
The buyer can then use those differences to prepare its asks: Can you improve the service commitment? Can you remove this restriction? Can you include additional implementation support? What can you offer if we commit to a longer term?
The evaluation has now become negotiation prep. Buyers may not simply enter the conversation with general preferences. They may arrive with specific points to challenge, trade and negotiate.
It’s true that AI’s comparison may not be completely accurate or apples-to-apples. Deals differ in features, scope, service levels, implementation and contractual obligations, and public information can be incomplete. But whether AI’s comparison is right or wrong, your revenue team may still have to respond to it.
As a seller, you need to be able to put AI-generated comparisons into context: where offers actually differ, why those differences matter and how they affect value, risk and total cost. And that scrutiny doesn’t stop with the proposal. Once the buyer moves into contracting, AI can apply the same analysis to the agreement itself.
AI turns contract review into negotiation prep
Contract terms have always been negotiable, so what’s changed? AI changes the speed and scale of the review that happens before and during that negotiation. AIRI found that 65 percent of B2B buyers surveyed said they often or always use AI to review contract language and agreement terms for red flags.
Instead of relying solely on someone to notice a provision during manual review, B2B buyers can use AI to systematically flag terms such as:
Price escalators and renewal provisions
Termination rights and fees
Liability caps and indemnification
Service-level commitments and remedies
Payment terms
Data-use or security obligations
Exceptions, exclusions and other limitations
Let’s say a buyer uploads your agreement and asks AI to identify provisions that create financial, operational or legal risk. It flags the renewal language, a termination restriction and a liability provision. The buyer then asks: How do these terms compare with the alternatives? Which ones should we challenge? What language could we propose instead?
The buyer can enter the discussion with you, having identified the clause, articulated the concern and, in some cases, drafted alternative language. In turn, this can make the negotiation:
More specific: Buyers can challenge individual provisions instead of raising general concerns.
Broader: More clauses can be reviewed and questioned, not just the obvious ones.
Faster: Buyers can move from identifying an issue to proposing alternative language quickly.
Harder to handle reactively: Your revenue team needs clear positions, fallback language and approval paths ready before redlines start moving back and forth.
This pattern is showing up in broader contracting research. World Commerce & Contracting’s 2026 AI in Contracting report found commercial and contract-management professionals moving beyond uses such as contract summarization and clause extraction toward more strategic applications, including contract benchmarking, supplier evaluation and negotiation support.
The reason this matters is because AI can do more than find a clause; it can help put that clause in context against other contracts, suppliers or commercial options. As a result, a term that might once have passed without much discussion can become a specific point for comparison, challenge or trade-off.
Of course, not every AI-generated objection will be valid. Deals differ, contract language reflects different risk tolerances and AI may not understand the commercial or operational rationale behind a provision. But if the buyer raises an AI-flagged issue, you must respond by explaining the term, defending it or changing it.
This means your sales, legal and finance teams should know what’s standard, why those positions exist, where there’s flexibility and what trade-offs come with changing them.
Legal teams use AI, too
You might think AI is primarily riding shotgun with procurement teams as they compare offers and prepare their asks. But AI may be sitting with legal, too. New research reveals that in-house legal teams are using AI to review contracts, identify issues and prepare redlines, bringing another layer of AI-assisted analysis into the negotiation and contracting process.
A 2026 LegalOn and In-House Connect survey of 452 in-house legal professionals found that:
52 percent of legal teams are already using or evaluating AI for contract review.
87 percent say AI can benefit pre-signature contract review and redlining.
Significantly, AI doesn’t replace legal expertise, but it can expand it. An experienced attorney can use AI to review more language, surface potential issues faster and prepare revisions or alternatives before your team sees the redline.
Essentially, AI gives the buyer’s legal team more capacity to question terms, develop fallback positions and prepare proposed changes. As a result, they may enter the contract negotiation with more issues already identified and more alternatives already considered.
Your sales, legal and finance team need a shared view of:
Which contract positions are standard and why
Where there is room to negotiate
Which fallback positions are acceptable
What changes affect commercial terms, risk or profitability
Which concessions require additional approval
The buyer’s lawyer still applies the legal judgment, but AI can help that lawyer arrive with more of the work already done.
AI can help buyers rehearse negotiations
AI isn’t only helping buyers (and their lawyers) analyze your documents; it can also help them prepare what they will say in negotiations.
A July 2026 Supply Chain Management Review article on AI-enabled procurement negotiations describes AI being used to accelerate negotiation preparation by analyzing contracts, pricing data and supplier interactions. AI can also help buyers anticipate supplier responses, rehearse negotiation scenarios and prepare structured responses to supplier tactics.
Imagine a buyer preparing to ask for a change in price, scope, service levels or contract terms. Before talking to your team, the buyer can ask AI to play the vendor: How is the seller likely to respond? What arguments might it make? How should I counter those arguments? What could I offer in exchange for the concession I want?
The buyer can then run the conversation again with different variables. What happens if I offer a longer contract term? Give up one concession to get another? Push harder on service levels instead of price? AI makes it easier to test those scenarios before the actual negotiation begins.
That doesn’t mean AI knows which strategy will work. Negotiations still depend on the people involved, the relationship, your priorities and information the AI may not have. But the buyer or legal team can arrive having considered more possible moves and responses before your team makes its first one.
That said, there’s nothing stopping your revenue team from using AI in the same way. Your team can rehearse likely buyer objections, test proposed concessions and prepare responses before entering the negotiation.
AI moves from coach to negotiator
In some organizations, AI is beginning to move from rehearsal partner to negotiation participant. BCG’s 2026 research on agentic AI in procurement describes three modes of deployment:
Assistive AI, which makes recommendations while people make the decisions
Low-level autonomy, where AI carries out work, but people approve significant decisions
High-level autonomy, where AI can decide and act within boundaries set by the organization
BCG found that most companies still keep humans in control, although autonomy tends to increase as organizations gain more experience with AI.
The latest data suggest some organizations are already moving beyond AI assistance. An October 2026 Icertis survey of 500 U.S. procurement leaders found that 40 percent already allow AI to negotiate supplier terms within defined parameters, and more than 60 percent trust AI with contracts valued at $1 million or more.
This doesn’t mean every strategic account will soon be negotiated by AI. Routine, repeatable purchases and relatively standardized terms are a more obvious starting point. Complex deals still require judgment about relationships, implementation, risk and long-term value.
How AI negotiates matters, too. An October 2025 experimental study in the “Journal of Purchasing and Supply Management” found that a “competitively prompted” buyer chatbot achieved larger price discounts, better payment terms and faster negotiations than a “collaboratively prompted” chatbot. But suppliers reported greater trust, outcome satisfaction and willingness to interact again with the collaborative bot.
This creates an important trade-off for B2B companies. AI may help optimize a particular negotiating outcome while creating consequences elsewhere in the relationship. The question isn’t simply how much negotiating authority to give AI. It’s what you want AI to optimize, what limits it should operate within and which decisions still require human judgment.
It would be easy to see all of this as the start of an AI arms race between buyers and sellers. Buyers use AI to analyze proposals, prepare negotiating positions and scrutinize contracts, so you respond by deploying more AI of your own. But matching every buyer use of AI with another AI tool isn’t the point. The goal is to prepare for a buyer whose analysis may already have been augmented by AI.
Prepare for AI-assisted negotiation and contracting
If buyers can use AI to compare proposals, rehearse objections and scrutinize contracts, your team can use it to test its own positions before negotiation and contracting begin. Start here:
Run a buyer-side negotiation rehearsal. Give an approved AI environment your proposal, standard terms and key contract positions. Ask it to identify objections and likely contract edits, compare alternatives, draft counters and test your answers. Check its assumptions and protect confidential information.
Equip your sales team to put comparisons in context. Document what differentiates the offer, including scope, service levels, implementation, support, security, risk allocation and measurable outcomes. Help them explain where seemingly similar offers differ and why those differences matter.
Preapprove concessions and trade-offs. Align sales, finance and legal on what can change across price, scope, service levels, risk and contract terms, what requires escalation and which positions are nonnegotiable. AI-assisted buyers can move quickly, so slow internal approvals can put your team at a disadvantage.
Define contract positions in advance. Review recurring objections to standard clauses. Explain unusual terms where appropriate and fix language that creates needless friction. Involve legal early in negotiation and contracting strategy.
Give your team its own AI support, with guardrails. Let AI help model scenarios and prepare responses, but require human review of benchmarks, legal advice, sensitive data and commitments before anything goes to a buyer. Define which actions require human approval and which, if any, AI may execute within approved boundaries.
Again, your goal as a seller isn’t to match buyers AI-for-AI; it’s to prepare for an AI-powered buyer and understand the types of analysis and concerns the buyer may bring to the table. By the time your team sees an objection, proposed concession or redline, the buyer may have used AI to compare alternatives, test trade-offs, draft language and rehearse responses.
The bottom line
The emergence of buyers using AI during negotiations changes what your revenue team can safely assume. You can’t assume buyers operate as they did historically under manual review, or that the objection you hear is the first one they considered, or that procurement or legal is working at the same speed or scale it once did.
The buyer still owns the business decision, but AI may have done a significant amount of the work leading up to it. You may never see AI at the negotiating table, but increasingly, you should assume it helped prepare the buyer sitting across from you.
Want to learn more about how buyers are using AI in the purchasing process? Download AIRI’s B2B AI Buying Behavior Survey Report, “The AI-Powered B2B Buyer Has Arrived.”