Principle 2: Think in Capabilities, Not Tools

Don’t adopt AI by defaulting to your vendor’s roadmap. Define the strategic capabilities your GTM needs to win, and build from there.  The biggest mistake teams make with AI is adopting fragmented features like auto-writing, enrichment, or call summaries, without asking what their GTM system actually needs to do better. The result is a stack full of tools and no real lift in pipeline or revenue.

Instead, start with outcomes. Ask:

What capabilities would materially improve how we go to market?

That might mean prioritizing accounts with more context, running faster tests on messaging, identifying pipeline risk earlier, or improving how buyers educate themselves post-demo.

Once you define those capabilities, you can design workflows around them, and use AI to power those workflows with scale, speed, or insight. Selecting the tool comes last.

Design Around Workflows, Not Features

AI can have the most impact on pipeline and revenue when embedded into a full process and not tacked onto isolated tasks. That means going beyond automating one-off actions and thinking in terms of full GTM motions.

For example, instead of “Let’s use AI to write better emails,” try to reframe your ask to be a capability:

“We want our outreach to be high-quality and personalized, without needing to spend hours on each interaction. Can we build a workflow that detects high-intent accounts, sends custom messaging, and adapts based on engagement?”

That’s a capability: intelligent outbound. It requires signal, content, automation, and feedback loops, all working together. When you design this way, you stop buying tools and start building systems.

Look Beyond Internal Automation

AI’s value isn’t limited to internal productivity. Some of the most impactful applications improve the buyer experience directly. A good place to start is by asking, “Where in our buyer journey do things break down?”

• Post-demo silence: Build a GPT to answer follow-up questions or summarize relevant content.
• Stalled economic buyers: Use AI to co-build business cases or ROI models.
• Repetitive objections: Train an assistant to surface proof points or competitor comparisons.

These aren’t productivity hacks. Built correctly, they can become strategic levers to increase velocity and conversion.

Empower Builders on the Front Lines

Waiting for your RevOps team to “own AI” is a bottleneck. Most ops teams are buried in dashboards, integration debt, and requests. Instead, look for the builders within your go-to-market team: the technical AE who hacks together tools, the growth marketer who understands systems.

Give them permission to experiment with small, high-impact use cases. When something works, operationalize and scale it. Bottom-up experimentation, when supported from the top, moves faster than centralized planning.