5 GTM Shifts We Saw Founders Get Right in 2025

What worked, what didn’t, and how the best teams actually put AI to work in GTM.

This year, nearly every founder I spoke with was experimenting with AI in their go-to-market motion.

Very few were doing it the same way.

Across the GTM AI articles I’ve written this year, a handful of clear patterns emerged. Not hype cycles or shiny tools, but practical shifts in how strong teams are building, operating, and scaling GTM.

Here are five that stood out.

1. GTM Is No Longer a Static Playbook

The most effective teams aren’t “setting the playbook and scaling it.”

They’re building GTM systems that adapt in real time by adjusting targeting, sequencing, and prioritization as signals change.

Teams like MedScout stood out this year, not because they automated everything, but because they used AI to continuously pressure-test their assumptions: which accounts mattered, which signals were meaningful, and where humans should stay involved.

The takeaway for founders is simple: Your GTM advantage comes from learning faster than your competitors, not documenting better slides.

2. The CRM Is Fading Into the Background

CRMs are still important, mostly as systems of record.

The work itself is increasingly happening elsewhere, with AI handling data capture, enrichment, routing, and follow-up in the background.

The strongest teams I saw this year weren’t asking, “How do we get reps to update the CRM?”
They were asking, “Why is a human doing this at all?”

It’s becoming table stakes to use a company like Momentum to get insights into your GTM strategy and pipeline by capturing all the data at the point of action, which alleviates the rep having to input it into the CRM. In this case, the data is being automatically transitioned to the CRM and the CRM has become a more accurate database.

For companies that want to take it a step further, Day AI, one of our Stage 2 portfolio companies, has created an AI-native CRM that provides instant pipeline visibility without manual input, proactive follow-up reminders, automatic meeting context, and daily sales briefings. Unlike traditional CRMs, Day AI is designed to effectively fade into the background, reducing the burden of admin while empowering companies with the information they need.

This shift alone is giving sales teams more time for selling, marketing, and decision-making all without having to add headcount.

3. The Front Door of the Funnel Has Moved

Buyers are no longer discovering companies in simple, predictable ways, like Google ads and organic search.

Between LLM-driven answers, AI search interfaces, and non-linear inbound paths, discovery is fragmented. It’s also a lot harder to measure with traditional tools.

Founders who adapted fastest treated inbound, SEO, and conversion not as discrete channels, but as one integrated problem: How do buyers find us, understand us, and decide to engage before they ever talk to sales?

Momentum is a great example of a company that is tackling this challenge head on in a number of creative ways, including a robust content marketing program.

Those who didn’t are already feeling the gap.

4. AI Works Best When Strategy Is Already Clear

One of the most consistent signals this year: AI amplifies clarity.

Teams with a sharp ICP, strong GTM judgment, and intentional sequencing saw real leverage from AI. Teams without those things found that AI can just create confusion.

Companies like QuotaPath show what’s possible when AI is used to support well-defined decisions (not replace them).

AI doesn’t fix fuzzy strategy. It exposes it.

5. Lean Teams Are Now Running Enterprise-Grade GTM

Perhaps the biggest shift this year: what small teams can execute.

With off-the-shelf AI tools, early-stage companies are now running outbound, inbound, and campaign motions that once required full SDR teams and dedicated ops functions.

Companies like Tofu are building technology where sophistication is no longer gated by headcount. And companies like Rally are creating enterprise-grade workflows with very small teams and just a few tools.

The bar has moved — and that’s good news for founders willing to design AI-native workflows early.

Looking Ahead

The teams that stood out this year weren’t chasing trends.

They were asking better questions about where humans add value, where AI can make an impact, and how GTM systems should evolve as markets change.

This mindset is what I expect to define the next phase of GTM as we go into 2026. Those that aren’t embracing that roles and systems are changing will be left behind.