92% of teams say AI works. Only 27% can back it up.
The gap between believing AI works and being able to prove it is wider than most teams realize. A new Metric Sherpa study produced with Sprinklr put numbers on the problem, and they are not flattering.
The Numbers
Among organizations with customer-facing AI in regular use, 92% said it met or exceeded expectations. Only 27% said they could show proof of that. That is a credibility gap of 65 percentage points.
The root cause is visible in the setup data. While 99% of respondents could name an intended outcome for their AI use, only 26% had defined success metrics before starting, and just 10% had also recorded a baseline.
The Accountability Gap
The governance side is just as thin. Only 17% said their organization names an owner for AI business outcomes. Only 28% said they use agreed criteria to decide whether to scale, change, or stop an AI application.
The study also found that 67% of people who said AI made work faster also said it reduced costs. Without baseline data and ownership, though, neither claim holds up to scrutiny.
The Operator Takeaway
If you’re deploying AI in any client-facing or revenue-touching workflow, define your success metric and record your baseline before you flip the switch. The teams that skip that step are the ones presenting vibes to a budget committee six months later. The fix costs almost nothing and takes an hour. Skipping it costs credibility when the numbers are called into question.
I’m founder of BizStack at Cagri Sarigoz LLC and a passionate advocate for entrepreneurs.
With over 14 years in tech, marketing, and AI, including my role as Head of SEO at CitizenShipper and co-founder of TaleBot at Intale AI, I’m dedicated to sharing genuine, useful product insights and tips.
At BizStack, I aim to cut through the digital noise to provide clear, actionable advice.
And more than all else, I’m a father to a (always) little girl and a husband.
Contact me at [email protected] for assistance.
