Sales teams are adopting AI faster than they can prove it's working
Over a 13-month window, ZoomInfo’s data tracking from June 2025 through July 2026 logged 10 sales-department pain points that explicitly tied "measuring and proving ROI (return on investment)" or "tracking ROI and attribution" to an active artificial intelligence initiative. It's a small number in absolute terms, but a specific one: Companies that are naming ROI measurement, not whether to adopt AI tooling, as the open problem.
That gap between adoption and attribution shows up in outside research, too. A Gartner survey of 227 chief sales officers, fielded in August through September 2025, found that 31% cited difficulty proving the ROI of AI-driven tools as a top challenge to their 2026 sales objectives—a large enough share to suggest ZoomInfo's tracking isn't picking up an isolated quirk, but an early read on a broader pattern.
The pattern isn't unique to any one company
This isn't a story about a handful of laggards. Based on the breadth of the data tracking, it's the default state for a lot of sales organizations right now. Teams are moving fast on adoption, new AI tooling, new agent capability, new workflow changes, and moving much slower on building the measurement infrastructure that would let them say, with any confidence, which of those changes actually drove the result.
That's a predictable failure mode, not a mysterious one. Attribution in sales was already hard before AI tooling multiplied the number of touchpoints in a deal. Adding more tools without adding better measurement just compounds the problem it was supposed to solve.
Why this matters beyond one survey
The Gartner figure is about difficulty proving ROI broadly, not any single vendor or tool category, but the underlying problem is bigger than any one contract renewal. A sales org that can't attribute results to specific AI investments also can't make a confident case for where to invest next. It's stuck making the same bet again next quarter, on faith rather than evidence, which is a worse position than not having adopted the tooling at all, because at least that would have been a conscious choice.
What this means for sales leaders
The fix isn't more AI tooling but measurement discipline applied to the tooling already in place. Before adding the next tool, sales leaders are better served building a clear before/after baseline for the ones already running: What changed in close rate, cycle length, or rep productivity, and can that change actually be traced to the tool rather than to seasonality, head count changes, or a stronger pipeline that quarter?
The organizations that get ahead of this aren't necessarily the ones adopting AI fastest. They're the ones who can say, specifically, what the tools did, and based on what is being tracked across sales orgs right now, that's a much smaller group than the adoption numbers alone would suggest.
This story was produced by ZoomInfo and reviewed and distributed by Stacker.
