Survey findings revealed at
Northstar’26
Every revenue team has AI now.
Most still can’t act on it.
195 revenue leaders told us where AI stops working: it flags the problem, then waits for someone to act. Get the size of that gap, what it costs, and what the teams closing it did differently.
195 revenue leaders
VPs of Revenue Operations, CROs and VPs of Sales
SaaS & AI-native companies
Mid-market to enterprise
Emporia Research
Independent fielding, July–August 2026
Siva Rajamani, CEO, Everstage, Northstar’26
Revealed at Northstar’26
Two hours to build a forecast, every week.
Half build the weekly forecast inside that window.
7 in 8 build it by hand.
Participants from
What the report found
The gap between knowing and acting is costing revenue.
Meetings catch risk first
57% first learn a deal is at risk in a pipeline review or from a rep. Only 17% hear it from an automated alert. A review runs on a calendar, not on a signal.
Data arrives second
80% make revenue decisions before all the data arrives. More than half say the information already existed somewhere in the stack. The problem is routing.
Deals wait days
45% take 4 or more days to respond once a risk signal appears. 47% take 3 or more days to approve a pricing exception, with the buyer ready to sign.
Revenue pays the price
74% say the knowing-to-doing lag is costing them real revenue. The number was consistent across every function and company size, without comparing notes.
Full methodology and scoring are in the report.
The report shows the gap.
This is how you close it.
See how Everstage connects the chain from signal to quote to payout, so the handoff between ‘the system flagged it’ and ‘someone acted on it’ stops requiring a person in the middle.
