Across B2B go-to-market (GTM) teams, the question is no longer whether to adopt AI, but how, where, and to what end.
To answer these questions, Scale teamed up with Benchmarkit to survey 278 GTM leaders and interviewed dozens more, and one thing is clear—everyone is using AI, and it’s working. Adoption is already widespread, with two-thirds of teams reporting using AI regularly. Moreover, the productivity impact has already been widely felt: roughly 85% of adopters are already seeing a boost, and we haven’t found a single team that, post-adoption, would choose to revert to a pre-AI era.
Still, many teams are wondering why their adoption hasn’t yet unlocked the department-wide impact they hoped for, and what use cases might enable them to do so going forward. The answer lies in understanding the two phases of GTM AI adoption. Most teams are just reaching the end of Phase 1 adoption, driven primarily by LLMs and focused on use cases that improve individual productivity. More advanced teams have started on Phase 2 use cases, which leverage more sophisticated workflows to directly move the functional metrics boards track: pipeline, conversion, win rates, etc.
In this report, we explain where we are now (Phase 1), where we are going (Phase 2), and how we will get there. Along the way, we cover the use cases that define each phase and establish how to move from one to the other, including which roles and functions should lead the charge, with a single goal in mind: helping you figure out how to best use AI.
