Post by RevOps Co-op

There’s a pattern showing up across RevOps teams right now: AI demos look great. AI pilots show promise. But very little of it actually changes how revenue teams operate. Not because AI can’t do the work. Because the system around it isn’t built yet. Our friends at Openprise get into that gap in a very real way. 👉 Download the white paper here: https://lnkd.in/gPcAfgXz A few things that landed: ⚙️ AI doesn’t eliminate complexity, it shifts it From manual work → to managing outputs, risk, and trust 🧩 Fully autonomous AI isn’t the answer (yet) The best results come from hybrid systems: AI + deterministic workflows 📊 “Good enough” has to be defined AI performance isn’t binary. It has to be measured, monitored, and improved 🔐 Trust is the gating factor Until outputs are validated and governed, AI stays stuck in “interesting experiment” mode The takeaway: AI isn’t a feature you add. It’s a layer you have to design for. If you’re responsible for making AI actually work in your GTM motion, not just testing it, this is a solid read.