91% of revenue leaders expect higher quotas in 2027. Only 8% say AI has raised attainment.

In a BCG survey of 398 CROs, sales leaders, chief commercial officers, and revenue operations leaders, published October 19, 91% said they expect quotas or productivity requirements per seller to rise next year. In the same survey, 8% said AI had led to higher quota attainment.

BCG’s Federico Fabbri described the gap in the release: “Those plans assume a productivity step-change that AI has not yet delivered.” We think 2027 quota plans should count only the AI lift a team has already measured, and treat the rest as upside a seller can earn.

What the survey found

Respondents come from 23 countries and five sectors. The release doesn’t say when the survey was fielded. Sixty-five percent expect headcount to grow over the next year, 72% expect sales and revenue budgets to increase, and 91% expect per-seller quotas or productivity requirements to rise.

AI use is close to universal: 90% report meaningful use in sales and revenue workflows, and 6% report autonomous AI completing end-to-end workflows. The most-cited impact was lower administrative workload (33%), followed by seller time saved (22%), and better coaching and forecast accuracy (18% each). Commercial outcomes come further down the list: 14% report improved conversion, 13% improved win rate, and 8% higher quota attainment.

Most reps already miss the current number

Bridge Group’s 2026 AE research, drawn from 158 B2B companies and published in June, found that 48% of reps achieved annual quota in 2026, down from 51% in 2024. Median quota is $960K. Ramp time reached 6.2 months, the longest in the research’s history.

So a 2027 increase starts from a quota that fewer than half of reps hit. Raising it because sellers save time assumes the saved hours turn into pipeline and closed deals, and that is the step most BCG respondents haven’t seen.

The evidence for AI lift is correlational

Bridge Group found that companies in the top third of its AI Engagement Score had 57% of reps at quota, compared with 39% in the bottom third. It calls this observational data and doesn’t claim causation. BCG found that its more AI-advanced organizations, those with more autonomous agents deployed, were twice as likely to name improved conversion as a top AI impact (23% versus 11%), more likely to be growing revenue at double-digit rates (69% versus 42%), and more likely to have formal AI adoption targets (67% versus 23%).

Companies that are already growing have more budget and slack to spend on AI, so the cause could run in either direction, and neither number predicts what your own team will get next year.

How we’d set 2027 quotas

• Build the base plan with no AI-driven lift. Start from this year’s attainment, ramp time, and capacity.
• Add only lift you’ve measured. If a workflow has run for at least a quarter and customer-facing output per rep went up (meetings held, opportunities created, cycle time), use that number. Hours saved don’t count until they show up there.
• Tie the rest to a trigger. Forma.ai, which sells quota planning software, suggested in July planning against scenarios that run from “no material AI-driven lift” to measurable capacity improvement, with quota and coverage decisions tied to observable triggers. A mid-year quota step that only happens if a throughput metric moves is one way to do it.
• Check by segment. Forma also flags uneven lift across roles and segments. A flat percentage increase can raise quota for reps whose work the tools barely touched.

What would change our mind

We’d back AI-based quota increases if a survey with a published method showed attainment holding or rising at companies that had already raised quotas on AI assumptions. A year of before-and-after output per rep, measured in meetings or opportunities rather than hours saved, would also persuade us.

If you’re setting 2027 quotas now, how much AI productivity is in the number, and what did you measure to justify it?