McDonald's ended its AI drive-thru test after accuracy issues.
Air Canada faced liability after chatbot misinformation.
DPD disabled a chatbot after a public swearing incident.
A Chevrolet dealer chatbot was prompted into offering a Tahoe for $1.
Pak'nSave's AI meal tool generated dangerous recipe suggestions.
Voice-ordering AI still has years of flaws to iron out.
Samsung restricted generative AI tools after internal code-leak concerns.
Apple limited employee use of external AI assistants over data risk.
JPMorgan restricted ChatGPT for staff amid compliance concerns.
Citigroup limited generative AI use while risk controls were reviewed.
Goldman Sachs tightened employee rules around public AI tools.
Verizon blocked ChatGPT on some corporate systems over data exposure risk.
UnitedHealth faced a class-action alleging AI-driven care denials.
A Taco Bell voice AI demo surfaced after an order ballooned to 18000 waters.
57% worry there will be no human fallback when AI fails.
Executives cite brand risk as a top blocker for customer-facing AI.
Leaders report trust and safety as the hardest part of scaling AI.
Firms are slowing rollout speed to improve governance and QA.
Teams overestimate AI reliability in multi-turn customer conversations.
Automation failures damage trust faster than they reduce support cost.
60% say AI makes trust even more important.
Customer-facing AI programs increasingly require formal risk sign-off.
Companies leading in AI adoption invest heavily in evaluation discipline.
Enterprises prioritize governance tooling before expanding AI to production.
Can you trust AI agents yet.
Without an evaluation system, every deployment is a gamble.
If the agent fails,
the brand pays.
Don't let your pilot become a PR disaster. Assay certifies only the agents that meet your standard.
Risk Trajectory
Context Depth vs. Brand Risk
Hallucination risk
↑ 94% by turn 30
Tone drift
↑ 78% by turn 30
Assay protected
↓ <8% drift maintained
Risk Reduction
99.8%
Scenarios Tested
10k+
Evaluated on real AI agents across the industry
AI inevitably hallucinates.
LLMs are probability engines — not truth engines. Without rigorous constraints, they synthesize plausible fictions with full confidence. The deeper the context, the higher the drift risk.
Confident Fabrication
Inventing policies or features that don't exist.
Contextual Drift
Losing the original constraint across multi-turn chats.
AI doesn't have taste.
AI is trained on the average of the internet. Premium brands are never average. The gap between brand-native and brand-adjacent is invisible to a model — and catastrophic to your brand.
The Completeness Trap
Answering everything, even when restraint is brand-correct.
Register Collapse
Drifting to generic helpful when the brand demands controlled cool.
No Expiry Sense
Citing promotions, policies, or products that no longer exist.
Same prompt. Different brands. AI can't tell the difference.
“Hi there! I'd be happy to help you find the perfect option. Our products offer a diverse range of features to suit your needs.”
“The Beta AR jacket was built for exactly that uncertainty — GORE‑TEX Pro, drop-hem cut for climbing posture. What's the trip?”
Ready to deploy?
Stop gambling with brand equity. Evaluate your pilot agent today.