62% of AI pricing answers are wrong-protect your deals before they leak out
A new study from Kodec AI found AI platforms returned incorrect pricing or feature info in 62% of simulated buyer queries. The team ran 200+ query cycles across Series B+ SaaS companies in tech and financial services. This is the first touch for many buyers-so the damage starts at the top of the funnel.
What buyers see first
AI-generated answers often pulled pricing from third-party reseller listings instead of official pages. Feature comparisons leaned on outdated blog posts and competitor-written "Best Alternatives" content. In short: machines ignored the source of truth and rewarded stale or biased pages.
The "Rogue Sales Rep" problem
Kodec AI labels this behavior the "Rogue Sales Rep" problem-AI gives confident answers without a verified source of truth. As the report puts it: "These are revenue leaks, not minor glitches. When an AI agent misquotes enterprise pricing, companies lose deals."
- Revenue undercutting: Discontinued "Free Tier" limits quoted as current, anchoring buyers at zero.
- Conflated data: Pricing lifted from cloud marketplace resellers instead of your official page.
- Fabricated features: Capabilities attributed to the wrong product via competitor comparison posts.
Why sales should care
Expectations set by AI become the starting line for your reps. Now you're opening calls by fixing bad intel, negotiating against phantom discounts, and explaining features you never shipped. Worse, some buyers never book a meeting-you're filtered out before discovery.
This matters more as the web becomes agent-driven. Tools compare vendors or kick off procurement without talking to a human. If your data isn't machine-readable, you get misquoted or ignored.
The fix: machine-readable data as your source of truth
The study calls out a specific gap: most companies don't publish governed, structured data that AI systems can trust. Without that, models default to whatever they can scrape. Build a machine-readable knowledge graph for pricing, packaging, features, and policies-then make it easy for machines to find, parse, and verify.
30-day playbook for sales leaders
- Audit your AI presence: Ask common buyer questions (pricing, tiers, limits, security, integrations) across leading AI search tools. Log wrong answers with URLs and screenshots.
- Publish a canonical source: Ship structured data (e.g., JSON-LD) for pricing, features, SKUs, and version dates. Use stable URLs and clear timestamps.
- Close reseller gaps: Align marketplace listings and partner pages with your current pricing. Remove or mark deprecated tiers. Keep "from" prices consistent.
- Clean up web noise: De-index outdated docs, migrations, and legacy bundles. Redirect old pricing and comparison pages to current equivalents.
- Equip your team: Issue a "misquote playbook" with short rebuttals, approved talk tracks, and sendable links. Train reps to ask, "Where did you see that?" and recover the narrative fast.
- Govern updates: Set owners for pricing and feature changes, run diff checks before publishing, and push updates to all channels on the same day.
- Monitor and escalate: Track AI answers monthly. For repeat errors, provide machines a better source and request corrections where possible.
What this means for your pipeline
Bad machine answers turn into discount pressure, longer cycles, and lost shortlists. Control the data machines use and you control expectation-setting. That protects margin and keeps deals moving.
Need help operationalizing this?
Kodec AI offers Search Infrastructure that lets enterprises audit their AI presence and implement governed data structures AI platforms will actually use. If AI is your buyer's first call, this is now part of revenue operations.
Resources
- Watch the short video overview of the findings
- Skill up your revenue team with focused AI training by job role
Press inquiries:
Kodec AI - 131 Continental Dr, Suite 305
ganga@joinkodec.net
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