When AI SDRs fail, teams don't go looking for a better version. Our data shows zero switch to a competing tool. Instead, half go back to manual and half go hybrid, but neither group tries a different AI SDR. The trust break is never vendor-specific. Once a team decides AI SDRs don’t work, they exit the category entirely. This report covers what creates that moment, what it costs, and what the teams that never hit it do differently in the weeks after launch.

Earlier this year, we published the State of AI SDR Industry report, which covered the market side of AI in sales: adoption, benchmarks, vendor landscape, and more. But what it couldn't answer was what the work sounds like once you've launched. Market data helps you choose a vendor, but it doesn't help you run one. So we went back and listened. We talked to teams running AI SDRs and asked them what the workflow felt like from inside. The same problem spots kept coming up, and the patterns that emerged from those conversations are what this report breaks down. If you're about to run or already running an AI SDR, this is the part of the picture the first report couldn't give you. Happy to answer questions in the thread.