How AI Is Killing Information Asymmetry in B2B Procurement

What happened

PYMNTS published an analysis arguing that artificial intelligence has fundamentally eliminated information asymmetry in B2B procurement — the structural advantage that sellers historically held over buyers through deeper knowledge of their own products, pricing structures, and market alternatives. The piece describes a B2B buying environment in which procurement teams now have access to aggregated market intelligence, real-time pricing benchmarks, peer reviews, and predictive analytics before ever engaging a vendor.

The core claim is not theoretical. According to PYMNTS Intelligence data produced in collaboration with Coupa, 75% of companies are now considering using AI in procurement. The article describes a shift toward what it calls "zero-touch" procurement, where AI enables faster, automated vendor assessments and buying decisions are increasingly finalized before a single sales call happens.

The article frames this as a structural inversion of the traditional B2B sales dynamic. Where vendors were once primary sources of insight — guiding and sometimes controlling the decision-making process through informational advantage — they are now, in PYMNTS' framing, "data points within a broader analytical framework." Procurement teams use tools that aggregate vendor performance data, simulate ROI scenarios, and flag implementation risks, embedding these capabilities into everyday workflows rather than relying on vendor-provided information.

Why it matters for practitioners

The PYMNTS analysis articulates a dynamic that competitive intelligence practitioners have been tracking through multiple data points — Gartner's rep-free buying research, G2's AI chatbot adoption data, Forrester's buyer journey studies — but frames it through the lens of procurement specifically. This framing matters because it moves the conversation from marketing and sales into the operational buying function, where vendor selection increasingly happens through systematic, AI-assisted evaluation rather than relationship-driven engagement.

1. The informational advantage that justified sales-led go-to-market is eroding. For decades, B2B vendors invested in large sales organizations partly because sellers possessed information that buyers couldn't easily access on their own: detailed product capabilities, competitive differentiation, pricing flexibility, implementation nuances. AI procurement tools eliminate this advantage by giving buyers access to the same information — aggregated across vendors, normalized for comparison, and available on demand. For CI teams, this means that competitive advantage can no longer be built on information control. It must be built on genuine product differentiation, verifiable outcomes, and the quality of structured data that AI procurement systems can access and evaluate.

2. Pricing transparency is accelerating faster than most vendors realize. The PYMNTS analysis emphasizes that AI gives buyers real-time pricing benchmarks that erode the seller's traditional advantage in price negotiations. When procurement teams can instantly access aggregated pricing data across a category, the vendor that shows up to a negotiation expecting information asymmetry to protect its margins is operating on outdated assumptions. For pricing intelligence teams, this means monitoring AI-accessible pricing data sources — aggregated benchmarks, public contract databases, crowd-sourced pricing platforms — has become as important as tracking individual competitor price changes. The buyer's AI system is synthesizing all of these inputs, and the vendor whose pricing is out of line with the synthesized benchmark faces immediate competitive pressure.

3. The declining volume of RFPs is a leading indicator. PYMNTS reports that procurement leaders are seeing a declining volume of formal requests for proposals, with vendor calls happening later in the process — if at all — and purchasing decisions frequently already made before the formal procurement process begins. This aligns with Gartner's finding that 67% of B2B buyers prefer a rep-free experience. For CI practitioners, the implication is that competitive wins and losses are increasingly determined in a phase that traditional CI processes don't monitor: the pre-RFP, AI-assisted research phase where buyers form preferences and eliminate vendors based on synthesized intelligence. Presenting competitive insights to sales teams remains important, but the insights must now also be embedded in the AI-accessible content that reaches buyers before they ever talk to a rep.

4. Vendors are becoming data inputs, not trusted advisors. The PYMNTS framing — vendors as "data points within a broader analytical framework" — is blunt but accurate for a growing share of B2B buying. When procurement teams use AI to aggregate vendor performance data, simulate ROI scenarios, and flag implementation risks, the vendor's own narrative about its product competes with AI-synthesized intelligence from multiple sources. For CI teams, this means ensuring that your company's competitive data — performance metrics, customer outcomes, implementation track record — is accurate, structured, and available in formats that AI procurement systems can access and evaluate. The vendor whose data is most machine-readable and verifiable has an advantage in an AI-mediated procurement process.

Key details

• Publisher: PYMNTS
• Topic: AI's elimination of information asymmetry in B2B procurement
• Key data point: 75% of companies now considering AI in procurement (PYMNTS Intelligence/Coupa)
• Core thesis: Buyers now have access to aggregated market intelligence, pricing benchmarks, and predictive analytics before engaging vendors
• Trend identified: "Zero-touch" procurement with AI-enabled automated vendor assessments
• Impact on RFPs: Declining volume; vendor calls happening later or not at all
• Vendor role shift: From primary sources of insight to data points in a broader analytical framework
• AI procurement capabilities cited: Aggregated vendor performance data, ROI simulation, implementation risk flagging, real-time pricing benchmarks

Market implications

The PYMNTS analysis captures a shift that is reshaping the entire B2B vendor-buyer relationship, not just the procurement function. When information asymmetry disappears, the competitive dynamics of a market change structurally. Vendors that historically won through superior sales execution — better presentations, more persuasive reps, faster follow-up — find that these advantages matter less when buyers have already made their decision using AI-synthesized intelligence.

For competitive intelligence teams, the most immediate market implication is that the definition of "competitive content" must expand. It is no longer sufficient to produce battlecards and competitive briefs for internal consumption. The competitive narrative must also exist in structured, verifiable, AI-accessible formats that reach buyers during the zero-touch procurement phase. This includes accurate product data on review platforms, well-structured comparison content on vendor websites, verified customer outcomes in formats that AI systems can cite, and pricing intelligence that reflects the reality of what buyers can discover through AI benchmarking tools.

The 75% figure — companies considering AI in procurement — represents a market that is still in early majority adoption. As AI procurement tools move from consideration to implementation, the pressure on vendors to ensure their competitive data is accurate and AI-accessible will intensify. CI teams that establish monitoring of how their company and competitors appear in AI procurement tool outputs — much as they monitor search engine results and analyst reports today — will be positioned to identify competitive threats earlier and respond faster.

The broader implication is that competitive advantage in B2B markets is shifting from narrative control to data quality. The vendor that tells the best story in a sales meeting is losing ground to the vendor whose structured data — performance metrics, pricing benchmarks, customer outcomes, implementation timelines — withstands AI-mediated scrutiny. For CI leaders, the practical takeaway is to audit your company's competitive data footprint: what does an AI procurement system see when it evaluates your company against competitors? The answer to that question is increasingly the answer to who wins the deal.

Related resources

• Competitive Intelligence — the discipline of monitoring, analyzing, and acting on competitive information across all channels, including AI-mediated procurement
• Pricing Intelligence — tracking and analyzing competitor pricing in an era of AI-enabled buyer transparency
• Competitive Advantage — how to build sustainable competitive advantages when information asymmetry no longer applies
• How to Present Competitive Insights — adapting competitive insight delivery for a world where buyers arrive pre-informed