The Sales Org of 2028 Will Look Nothing Like Today's
I've spent more than 25 years building and scaling go-to-market organizations, from three-person sales teams to global operations of 85 and 100 people at companies like Tipalti and Coupa. I've watched the function change in meaningful ways over that time. But what I'm seeing right now, in 2026, feels different. The pace is faster, the stakes are higher, and the leaders who don't get ahead of this shift are going to find themselves managing a model that's already obsolete.
Here's what I'm observing directly: AI is beginning to collapse the traditional separation between data gathering and decision-making. For most of my career, sales leaders spent an enormous share of their time finding information, building forecasts in spreadsheets, reviewing pipeline in CRM systems, and trying to stitch together signals from disconnected tools. That work is starting to disappear. Not slow down. Disappear. The organizations I'm working with today are beginning to automate the assembly of that information entirely, which means the job of the revenue leader is shifting toward interpretation and action, not collection.
I lived through a version of this transition at Coupa. When we were scaling from under $1 million to $100 million in ARR, the biggest constraint on growth wasn't talent or product. It was our ability to make fast, accurate decisions with incomplete information. We built manual systems to compensate: forecasting calls, pipeline reviews, territory models. Those systems worked, but they were slow and dependent on the judgment of a handful of experienced people. What I see now is AI beginning to do that foundational work at a fraction of the time and cost, which changes the entire design of a go-to-market organization.
The change I'm most focused on is this: the ratio of quota-carrying reps to revenue operations and analytics support is going to shift dramatically. Today, most scaling SaaS companies carry a large ops and enablement infrastructure to support their sellers. As AI handles more of the data work, that infrastructure shrinks, and the sellers who remain need to be more analytical, more strategic, and more skilled at judgment-based conversations with buyers. The average enterprise buyer is already more informed than ever. They don't need a rep to explain features. They need a peer who can connect product capability to business outcome.
I want to be direct about something, though. The market right now is full of AI noise. Every vendor claims to be AI-powered, and most of what's being sold is dressed-up automation with a language model on top. When I evaluate technology for the companies I work with, I push past the demo and ask one question: where does this create measurable business value? Not productivity theater. Not a dashboard that looks smart. Actual, traceable business outcomes. The gap between AI that passes that test and AI that doesn't is significant, and leaders who can't tell the difference are going to make expensive mistakes.
What this means for team building is real and immediate. I'm already thinking differently about the profiles I recruit for. The best sellers I want on a team in 2028 will need to be comfortable working alongside AI-generated insights, able to assess their quality, and confident enough to override them when the situation calls for it. That last part matters. AI surfaces patterns. People still provide judgment. The sales leaders who treat AI as a replacement for human thinking will underperform. The ones who treat it as a multiplier will pull away from the field fast.
One concrete shift I've already made in how I advise go-to-market teams: I'm pushing for AI literacy as a baseline competency in hiring and onboarding, the same way I'd push for product knowledge or objection handling. It's not about being a technical expert. It's about understanding what the tools can and can't do, and being able to ask the right questions of the data they produce. That skill didn't exist as a formal requirement three years ago. It's becoming a must-have.
The revenue organizations that will win over the next five years won't be the ones that adopted the most tools. They'll be the ones that built a culture of sharp, fast, evidence-based decisions and backed it with the right technology. That's where I'm focused, and it's the direction I see the whole field heading.