For years, founders could grab a “standard” go-to-market playbook: hire a demand gen lead, spin up paid channels, build an SDR pod, run events, iterate. At TechCrunch Disrupt 2025, leaders from OpenAI, Google Cloud, and GTMfund made one thing clear: that playbook is being rewritten in real time by AI.
You can now do more with less, test more ideas faster, and personalize at a level that was impossible even two years ago. But you still can’t outsource strategy or fundamentals to a model.
From fixed playbooks to adaptive GTM systems
Historically, GTM strategy meant:
- Specialist-heavy teams (paid, lifecycle, brand, ops)
- Long planning cycles
- Manual experimentation and reporting
Now, AI tools sit in the middle of the stack, automating tasks that used to consume headcount and calendar time: research, list building, copy variations, and first-pass sales outreach.
The result is not “GTM with no team.” It is GTM as an adaptive system: fewer people, faster loops, tighter feedback.
AI doesn’t replace marketing craft – it amplifies it
Leaders from both Google Cloud and GTMfund keep coming back to the same point: the fundamentals still matter. Positioning, segmentation, messaging, pricing and narrative are non-negotiable.
You still need people who understand customer insight, research and what “great creative” looks like. AI is powerful, but without a clear brief and strong taste, you just generate more noise, faster.
Key insight: AI is leverage on good strategy, not a substitute for it. If your ICP, offer and message are fuzzy, AI will simply help you ship more fuzzy content.
What modern GTM teams look like
The next-generation GTM team is smaller, more technical and a lot more curious.
Instead of hiring narrowly defined specialists, companies are starting to prioritize:
- Generalists with AI fluency – people who can move between creative, data and tools.
- “Tool stack” operators – marketers and RevOps who can wire together LLMs, automation platforms and data sources.
- Domain experts with copilots – product marketers, PMs and sales leaders who keep the narrative honest and use AI to stress-test it.
The hiring spec shifts from “5+ years managing paid search in B2B SaaS” to “strong marketing fundamentals, high curiosity and the ability to learn and wield new AI tools.”
AI’s edge: personalization and signal-following at scale
Serious teams are not using AI just to cut costs. They are using it to sharpen focus.
AI is now used to:
- Build deeply segmented audiences and prioritize the right accounts
- Generate tailored messaging by persona, industry and stage
- Monitor behavior and “follow the signal” instead of blasting generic campaigns
Done right, your funnel becomes less about volume and more about orchestrating high-relevance touches across fewer, better opportunities.
How founders should rethink their GTM playbook
If you are building or refreshing GTM in this AI era, it helps to think in four steps.
1. Lock the fundamentals, then layer AI
Clarify ICP, jobs-to-be-done, value prop and core narrative first. Use AI to pressure-test that story (generate objections, competitor comparisons or alternative positioning), but don’t let the model decide who you are.
2. Redesign workflows, not just tools
Inject AI where you have bottlenecks:
- Research and list building
- Copy testing and localization
- Sales enablement content
- Reporting and insight generation
The goal is to shorten cycles and free humans for high-judgment work, not to bolt a chatbot onto every screen.
3. Change hiring criteria
Look for people who can explain why a campaign worked, not just what they did. Prioritize marketers and operators who are comfortable building in AI CRMs, orchestration platforms and LLM-based copilots, and who have a track record of experimentation.
4. Treat AI as a continuous experiment
The best teams define a few high-impact use cases, measure rigorously and keep a running backlog of what to scale, what to kill and what to revisit. AI becomes a permanent experiment layer inside the GTM engine, not a one-off project.
What this means for the next wave of AI-native GTM
The fundamentals of go-to-market have not disappeared, but the shape of execution has changed:
- Same strategy, radically different tempo
- Smaller teams, more leverage
- Less manual ops, more creative and strategic energy
The real risk is not missing one magic AI tool. It is clinging to a linear, headcount-heavy GTM model while competitors build compounding advantage through AI-driven experimentation and personalization.
If you can pair strong marketing craft with an AI-literate team and a willingness to redesign workflows, you are not just adopting new tools. You are building a GTM engine that gets sharper every cycle while the old playbook crowd stands still.
