Heard this in a call last week — a VP of Sales proudly said their team is "fully AI-enabled." When I asked three of their reps what that meant day-to-day, I got three completely different answers. One said Gong summaries. Another said ChatGPT for cold emails. The third said "I think we have some tool but I have not really used it." The gap between "leadership bought AI tools" and "the team actually knows how to use them for their specific workflow" seems to be where most orgs are stuck right now. Has anyone here found a good way to bridge that — especially for reps who are more skeptical or just busy?
I have a lot of thoughts on this. Where I've noticed the gap get closed is when reps see that the AI tools actually help them meet quota. That's their number 1 priority. If they already have a system that works, they don't want to take risks to change it. If they have a system that doesn't work, the one they want to switch to is the one already proven to be working. What this usually plays out to in practice is the top performers are early adopters getting real success out of the tool and it's a trickle down effect. I also think there's another path that's often overlooked. Executives can put into place agentic AI doing a lot of the heavy lifting for reps on the backend that makes their lives more efficient and easier to hit quota. Asking reps to build out and use projects in ChatGPT or skills in Claude, connecting MCPs, etc can seem daunting and become frustrating so many just don't do it. Increasingly so when the output isn't perfect and they have to go back and correct it anyway. For them the time invested doesn't seem worth the reward.
spot on about quota being the ultimate filter. if the tool doesn't clearly connect to hitting their number, it's just another tab they have to learn.
the trickle-down from top performers is real — but what I keep seeing is most orgs don't know *why* their top reps get more out of AI. it usually comes down to something subtle: better prompting instincts, knowing when to trust the output vs. when to sanity-check it, integrating it into their actual workflow instead of using it as a standalone thing. the rest of the team sees the results but can't replicate the process.
your point about backend agentic AI doing the heavy lifting is the most interesting to me though. that might be the actual path for the skeptical majority — make AI invisible so they get the benefits without the learning curve.
