AI + GTM

5 flavors of AI for GTM, value vs volume, quality vs quantity

Everyone's talking about AI in sales and marketing, but most teams are doing it backwards. I see two common issues:

1. Buying AI tools first, then trying to figure out strategy. We saw this movie in last gen ABM and didn’t like the ending.

2. Thinking AI is a volume multiplier, instead of a value multiplier. Beware of the spam cannon 3.0 with “personalization.”

The AI for GTM space has gotten complicated fast. RevOps and marketing ops teams are drowning in options. We've gone from "AI as a feature" to a sea of "AI-Native" players and "AI Agents" that all sound similar but come in very different flavors.

AI FOMO is real and dangerous.

Before we talk strategy, let’s look at the different AI deployment models that RevOps teams are using…

The Stack: 5 Types of AI for GTM Teams

I think it's helpful to breakdown the different types of AI apps and platforms into five categories. Each has a very different pitch and engagement model for RevOps.

1. AI Co-Pilots - Assistants that help your reps work faster and better. You handle process and relationships. Think Lavender, Fathom, Common Room, Docket.

2. AI Solutions - Purpose-built intelligence that solves specific GTM problems end-to-end. You focus on strategy and enablement. Think Keyplay, Consensus, Mutiny.

3. AI Workers - Hire a digital employee instead of a human. You handle management and quality control. Think 11x, AISDR, Artisan.

4. AI Workflow Builders - Platforms to build your own AI-driven workflows. You become the GTM engineer. Think Clay, Zapier, n8n.

5. DIY on LLMs - Build directly with model APIs. You handle the software engineering. Think OpenAI, Anthropic APIs, LangChain.

Most ops teams will use all five, picking different approaches for different jobs within their stack. The key is matching the right model to each specific use case.

This understanding is a good step in avoiding AI FOMO.

But having a framework for the tools doesn't solve the backwards approach

The Bigger Question: Amplify Quality or Multiply Quantity?

Even if they are grasping the tools, many teams lose track of the strategy.

The trap: Thinking AI is a volume multiplier, instead of a value multiplier.

It’s natural to gravitate toward quantity — more activity, more sends, more content is the easy lever. AI today reminds me of the early days in marketing automation or sales engagement. Lots of spray and pray thinking.

It’s tempting to crank out tons of "personalized" emails and generic content. Sure, you might get a few meetings. But you're also training buyers to ignore you.

I think Kieran Flanagan nailed the framing:

In the AI era, you win by creating more value for a more targeted group of people.

Source: Kieran Flanagan

Whether it’s outbound or inbound, ABM or PLG, enterprise or SMB, the idea holds. Principled GTM leaders have always made the case for quality over quantity. But AI gives us next-level leverage to make the dream come true on both sides of the equation. Here’s how…

More Value: Create stuff people actually want

Taste and customer understanding is paramount in this world. Anyone can copy your features, but they can't copy your unique perspective.

• Stop making AI-generated "ultimate guides" that say nothing new.

• Use AI to make your content deeper and more relevant to specific problems.

• Focus on insights only you can provide (from your data, customers, experience).

More Targeted: Get specific and relevant

ICP Targeting has entered a third generation of possibility. You don’t need to use the same generic data as your competitors. AI Agents for research and account intelligence unlock hyper specific ICPs and segments. This can be your differentiator.

• Move past basic firmographics when selecting accounts, territories, and plays (i.e. it’s not "SaaS companies with 50-2000 employees").

• Use AI to research accounts deeply and continuously - like having your best AE assess every potential customer.

• Look for "vibe signals" - does this company actually care about what you solve?

The bottom line: AI should make you more valuable and more precise, not louder. The companies winning with AI aren't the ones sending 10x more emails. They're the ones their prospects actually want to hear from.

The Choice Ahead

We're at an inflection point. The AI tooling landscape will only get more complex. But the winners won't be determined by who has the most sophisticated stack.

The companies that figure out how to use AI for deeper value creation and more precise targeting will pull away from the pack. Those that use it as a volume multiplier for mediocre strategies will get left behind.

The fundamentals haven't changed. You still need to create value for the right customers at the right time. But AI is giving us more leverage.

The question isn't whether to embrace AI in your GTM motion, or even which tools to pick first. It's whether you'll use this leverage to race to the bottom or climb to the top.