Rebuild Your GTM Org Top-Down for AI, Before the Market Does It for You

Everyone is talking about whether AI is going to take jobs. It will, for some. It would be a disservice to pretend otherwise. But the bigger story is what this transformation looks like on the other side.

Organizations are changing shape fast, and whether your people make that jump is largely on you. The job is to run the shift on purpose, before the market runs it for you. Fifty-five percent of leaders who cut jobs and cited AI now say it was the wrong call, which tells you how costly it is to run this reactively.

Most leaders get the first move wrong. They point AI at automating tasks and workflows. They expect individuals to take action with AI. They ask ICs to do more with less. That's the bottoms-up approach.

I'm a big believer that the shift comes from the top down. Rethink the entire go-to-market motion with AI, then rebuild the roles and the expected outcomes around an AI-first organization. A bottoms-up approach makes yesterday's process slightly more efficient. Top-down moves the organization from a linear growth model to an exponential one. Bottoms-up drives efficiency gains at best. Top-down drives revenue. The AI-forward revenue orgs in ICONIQ's 2026 benchmarks are running a third leaner at the same revenue, and that gap is the top-down effect showing up in the data.

Start by reminding ourselves why the roles exist as they do today. We built everything in go-to-market around the limits of one human. A person can only do so much, know so much, be in so many places at once. So we split the work into roles: SDR, AE, sales engineer, CSM. Then we made the buyer bounce between all of them and called it a funnel. HubSpot's own CMO now says the funnel is over. AI doesn't have time, recall, or capacity limits.

AI can rewire those roles and meld them together, so that ultimately one human can take on the full journey. The result is a better buying experience.

I'm bullish on AI taking over a large part of the selling because the bar is low. Banking, medicine, and highly regulated industries demand deterministic perfection and can't afford a 5% error. In sales and GTM, humans have a 20%+ error rate. AI can recall and communicate better than a human.

AI's first job

The first place AI earns its seat is where you never had a business model to put a human in to begin with. You could never afford a sales engineer on every SDR call, a deeply technical CSM on every check-in, or a forward-deployed product engineer sitting with every customer showing them how to get value inside the product. The sales engineer shortage is already becoming a revenue problem for enterprise software, which is exactly the gap this closes. Now you can, and the buyer gets expert depth at the first touch instead of four handoffs later.

At 1mind, our Superhuman Mindy sources about 76% of our pipeline, with no marketing team behind her until recently. That isn't a human doing less. It's 24/7 coverage with the product, company, and sales acumen of our best rep, coverage that would never have been possible before. On first touch, buyers get empathy, solutions, and deep technical expertise instead of handoffs and forms. The result isn't just top of funnel. It's higher win rates and larger ACV. The faster you get in, the larger the prize. The customers you can't afford to talk to are precisely the ones AI was built for.

AI makes our jobs, and the buyer experience, better

The second thing AI takes away is the grind, and it improves the buyer experience while doing it. Reps used to burn the week on busywork, scripted qualification, and endless internal chasing that never once made a buyer feel understood. What buyers actually want is the part I see humans skimp on most, and it comes down to two things.

The first is depth. Not a passable answer, but the right one, in the moment, in every conversation across the funnel. Not just when the solutions expert happens to be on the call. You never know where a live call will go, so no human can pre-load the right slide. A Superhuman can. Alteryx keeps 10,000 case studies in its Superhuman's brain and surfaces the single most relevant one for whoever is in the room. No human, no matter how good, has perfect recall plus 10,000 slides and live demos ready to roll at any given moment. That's the extra mile. The buyer wants more than an answer. They want to feel heard in the moment.

The second is speed. "Let me get back to you" is a human latency problem, the deal cooling while a rep hunts for an answer that should have been instant. Or worse, never answers at all. AI ends the delay. It answers now. On a live call, AI gets about 200 milliseconds to sound human, and that reflex speed is the whole game.

We still have humans. We've just elevated them. Every role is given the support we could never budget for before.

Humans go back to being human

The big shift isn't automating the jobs to be done. The exciting change is that humans get to go back to their core job: being human. Empathy. Relationship-building. The connective tissue of a deal, rather than the transfer of information. Finding the real champion and knowing them inside out. The judgment call that saves the account. Sixty-nine percent of B2B buyers now use sales reps to validate their AI research, which points to exactly the accountable-judgment role humans move into.

GTM roles expand in breadth

Picture a GTM human who owns first human touch through to onboarding, support, and upsell. As crazy as that sounds, I am bullish it's the future. Break down the job. The tasks, we all agree, are getting eaten by AI. So is the transfer of information, whether that's the sales pitch or the support answer. AI will give demos and onboard customers with tools like our live in-browser agent. AI will answer the RFP, build the business case, and build the ROI calculator (shameless plug: we build those as branded assets inside our Superhuman, too).

So what's left is owning the customer. Face time, caring, listening. Once AI carries the depth and the context, the old lanes our teams have always stuck to stop making sense. That doesn't mean a smaller job. Each person becomes responsible for more, not less.

Where to start now

Start putting AI in the places you could never make a business model for a human. Nothing gets displaced, nobody has to be sold on it, and you're filling coverage you already wrote off as unaffordable.

Walk your funnel and list every place a buyer needed an expert and didn't get one. The technical question on a first call. The security review. Onboarding for the long tail of accounts your CSMs can't cover. The renewal nobody touched until 30 days out. Then list every "let me get back to you" in your organization. Those are latency, and they're measurable. Rank them by deal value and close the expensive ones first.

Deploy a teammate, not a tool. A workflow automation makes a step faster. A teammate owns an outcome and carries context across the whole journey. Give it a name, a scope, and a number it's accountable for, and review it in your pipeline meeting like you'd review a rep. Restraint matters here too: knowing when not to add another agent is becoming the core skill in building reliable AI.

Then fix the metrics before you fix the roles. Most GTM metrics measure human effort: calls made, demos held, meetings booked. Those stop meaning anything once an AI teammate is carrying the volume. Move to coverage, cycle time, win rate, expansion, revenue, and buyer experience at every stage.

How to think about org structure

Stop drawing the org around handoffs. Draw it around the buyer's journey, then ask what a human is uniquely for at each point.

The old chart split the customer into pieces because one human could only carry one piece. Give one person the whole relationship and let AI carry the depth underneath them. Every human gets a Superhuman teammate, not a license. Plan capacity by the coverage you owe every buyer, not by how many reps a pipeline number requires. And when a seat opens, don't backfill on autopilot. Ask whether that role should come back in the same shape. Most of the time it should come back with a wider scope.

Waiting is what holds your people back

This compounds somewhere most leaders don't look: hiring. The best people entering the market won't do the job the old way. They don't want to spend their days on manual, menial work a machine should be doing, and they can tell in one conversation whether you've built a company that respects their time. Replit's revenue chief says he would rather hire the AI native than the sales veteran, and that preference is spreading. Give your team real AI and you become the place the best people want to be. Resist, and your talent bar slips from the inside out while, under the radar, the best talent stops applying.

When the hours free up, point your people at the human work: judgment, relationships, the end-to-end ownership the role is becoming. And stop hiring for the org chart you already have. Hire for judgment and strategic range instead.

The most exciting part is a shift in what is valued

Step past go-to-market for a second.

As AI gets more capable every day, things are changing. That scares people. It doesn't scare me. I'm excited for a world that finally values the work only a human can do.

Right now, we don't. We pay people next to nothing to sit with the dying, to care for the sick, to hold a family together. I think that flips. When machines carry the tasks, the workflow, and the selling, the uniquely human work stops being what we overlook and becomes what we prize.

My oldest brother was a hustler and a CEO. Then one day he walked away from it to become a monk. Today he's a chaplain. He makes almost no money. He sits with people as they're dying in elderly care facilities and homeless camps and asks them, "Do you want to talk to someone? Do you know what's happening to you? Do you have a relationship with a higher power?" By every number our economy cares about, that work is worth nothing. By every measure that actually matters, it's some of the most important work there is.

I want a world that leans into that. And for the people like me who love to build, the door stays wide open too. I don't know exactly what my job looks like in three years. I do know the leaders who start moving now, and who tell the truth about it, are the ones who'll find out first. And that excites me.