Adrian G.

Hi everyone, really appreciate all the input here. This was super helpful. What I’m taking away is that it’s not really about more or less personalization. It’s about being relevant and clear. When personalization connects to a real problem, it works. When it feels forced or off, it hurts. In my world, since this is what I do, it often feels very individual. It’s actually hard for me to step back and have a high-level view. I end up looking at what each rep sends and what turns into real conversations, and then building from there. There’s no single best way just what works for that rep, with that buyer, at that moment. Thanks again everyone, great discussion.

Totally agree and from what I’ve seen and read so far, that’s actually where the risk starts to show up. AI doesn’t seem to reduce revenue performance immediately. It tends to create the appearance of progress first. Activity goes up, outputs look cleaner, dashboards improve but the underlying signal quality can start to weaken. So it’s less about AI directly hurting revenue and more about it masking early indicators of decline. By the time it shows up in core KPIs, you’re already reacting late. So this makes me want to know how are teams distinguishing between AI that’s actually improving outcomes vs AI that’s just making activity look better?

I'm curious on where have they seen AI reduce revenue performance in real GTM teams and what was the underlying cause that leaders initially missed?

I’ve worked with a lot of founders and early teams, and I think there’s a piece missing in the build vs. use debate. A lot of teams don’t actually understand their product, buyer, and motion deeply enough yet. So the agent ends up being as generic as the person configuring it. The real skill isn’t building or using it’s knowing how to connect the product to the buyer, their context, and the right action. If you can’t do that, the agent just scales bad assumptions faster. The teams that win won’t be the best builders, they’ll be the ones who actually understand what they’re trying to build.

I think we’re missing a generational lens in this conversation. I think the real question isn’t “can AI replace outbound?” It’s “which buyers are comfortable buying without talking to a human?” We already do this in our daily lives booking travel, buying software, even making big purchases without speaking to anyone. As new generations move into decision-making roles, that comfort will increase. So AI won’t flip a switch and take over. It will expand as buyer behavior changes. The closer you are to trust, risk, and complexity, the longer humans stay involved.

Hi Nandini, the teams I'm working with aren’t asking “replace or not.” They track “time-to-next-action.” When AI reduces the gap between touches (research to message to follow-up) below 24 hours, pipeline jumps. So most large sales orgs don’t replace SDRs they are starting to pair 1 rep with 3–5 agents and measure “Did speed increase without hurting reply quality?” Speed + relevance—not automation—is where I'm seeing AI win.

Hi Ashley, this may sound odd, I'm a 20+ year Senior Sales Trainer. Go where SDRs fail out of AE roles. Many good SDRs get promoted too early, struggle, and quietly look to step back. Search LinkedIn for “AE to SDR” or “Account Executive (open to work)” These people already know pipeline, not just prospecting. They ramp fast and need far less training.

Hey Jiya that’s great. Since the problem is getting interviews, maybe try showing how you would do the job. Pick a few companies you want to work for, choose one of their target customers, and write a short outreach example. Then record a quick 1–2 minute video explaining your thinking and send it to the hiring manager. I've seen this work. Good luck.

Hey Raj this is a great problem to be working on. Most teams are still stuck in that exact tradeoff between volume and relevance, so you’re pointing at something real. The part I’d be careful with isn’t a specific task like writing the hook or building sequences, it’s decision quality upstream of the message. In outbound, the biggest failure point isn’t usually the email itself. It’s choosing the wrong problem to lead with, misjudging how urgent that problem is for that specific buyer, or connecting a feature to a pain that doesn’t actually drive action. That judgment layer is where most reps still struggle and where AI can sound convincing but be directionally off. So if I were “terrified” of anything being fully offloaded, it would be problem selection and prioritization per account. Because once that’s wrong, even a perfectly written message won’t convert. Happy to take a look at the workflow if you’re open to it this is a really interesting direction.