GTM Leaders Must Get Hands-On With AI Tools to Drive Strategy
AI can basically analyze customers' words, actions, and what's in the CRM and say, 'These accounts are worth 10 times more than these accounts.' Hugely valuable for the go-to-market organization, but the CRO needs to know to ask these types of questions.
I asked Claude Code to go help me solve this problem. I took all of the emails in their TAM and submitted 110,000 password reset emails, and I found all of the actual users of their competitor software. That is diabolical.
I think that one of the hard things is every job now needs to be unbundled, which is you need to kind of figure out what are the series of tasks that everyone has, where tasks that shouldn't exist, they should be doing more of or... job descriptions need to now be, sort of, what an AI job looks like.
- The best go-to-market teams are using AI to win, but many C-suite AI mandates are hollow because leaders don't understand how to implement AI or what it truly means for their strategy.
- Go-to-market leaders need to be hands-on with AI tools like Claude Code to develop an intuition for what's possible and effectively unbundle existing job roles to leverage AI capabilities.
- Many C-suite leaders issue AI mandates without understanding what it means or how to implement it, expecting their teams to figure it out, which is an absurd proposal.
- AI can uncover every single user of a given SaaS product, including their subscription tiers, by processing large datasets like email lists, which is a task humans would never be assigned.
- The core thesis for AI adoption in GTM is that organizations were built around human capabilities, but AI capabilities are different and rarely overlap perfectly with human jobs, requiring a re-evaluation of roles.
- A significant portion (likely 10-20%) of revenue leaders are familiar enough with AI tools to think strategically about their application, but many others feel existential dread about needing to learn them.
- AI allows for rapid iteration and testing of sales campaigns, enabling teams to eliminate entire market segments that won't convert and refine targeting within days, leading to a 2x advantage over competitors.
- The definition of 'work' for GTM teams is shifting from meeting and delegating to hands-on experimentation and rapid iteration with AI tools, which requires a change in prioritization and skill sets.
- 110,000 password reset emails (Submitted to a competitor's site to identify all actual users and their subscription tiers.)
- 100-200 calls per day (Number of calls a cold caller makes daily to test sales hypotheses.)
- 10x more valuable (AI can identify accounts that are 10 times more valuable than others based on customer words and actions.)
- 2x average rep retention (Competitors' comp plans led to 2x higher rep retention compared to a client's plan.)
- 38% leaner (AI-adopting go-to-market teams were found to be 38% leaner than previous eras.)
- 20% of revenue (For fast-growing AI companies, 20% of their revenue comes from self-serve channels, with the rest being sales-led.)
- $300 billion globally (Total venture capital raised in Q1 of the current year.)
- $55 billion (Total liquidity gained by employees through tenders in 2025.)
RevBots.ai View:
- AI Sprinkler teams bolt on AI features without transforming workflows.
- ARM organizations re-engineer roles around AI capabilities for leaner teams.
- SaaS Hoarder leaders issue hollow AI mandates without hands-on experience.
- Tab Hopper founders lack the scale to justify AI investments.
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