August 21, 2025

Hot Take: Most companies are adopting AI to check boxes, not solve real problems

Sean Hiss

Sean Hiss, a GTM Strategy Advisor, shares his perspective on AI Implementation. With nearly two decades scaling GTM function across companies from hypergrowth startups to Fortune 500 enterprises—Sean has been on the front lines of implementing new technologies and operational frameworks. Having guided organizations through scaling challenges and technology adoptions, he has unique insight into the gap between AI's transformative potential and the checkbox-driven implementations that often fall short of meaningful business impact.

🌶️ Hot Take: Most companies are adopting AI to check boxes, not solve real problems

The AI Elephant in the Room: Breaking Free from Checkbox Implementation to Drive Real Growth

AI is transforming GTM operations with predictive lead scoring, personalized content generation, and intelligent account prioritization. The potential is undeniable.

But there's an elephant in the room: the pressure to adopt AI tools to check boxes rather than solve real business problems.

The Checkbox Trap

Every board meeting has the implicit question: "What AI tools did you implement?" Teams rush to deploy AI sales coaching platforms nobody uses, content generators producing generic output or people with seven fingers, and prospecting tools automating bad processes.

However, recent market research suggests that only about a quarter of GTM leaders see meaningful ROI from AI investments. The gap isn't necessarily in AI's capabilities, but rather it's in implementation strategy.

The Hidden Implementation Reality

AI implementations require first and foremost a “real” business need or opportunity to do something. From there, its data cleanup, workflow redesign, and team enablement. However, when driven by external pressure rather than strategy, teams tend to underestimate these requirements, leading to “check the box” results.

The Strategic Opportunity

Winning companies are going to use AI to create unreplicable capabilities—hyper-personalized account research, predictive stack recommendations, composable software discovery, among any number of other use cases.

This requires "AI-smart" thinking: Is there a meaningful business, process or capability gap here and can AI truly create a competitive advantage?

The Framework for AI Success

Before any AI implementation, focus on strategic fit:

  1. What specific business outcome will this drive?
  2. Are we enhancing human capabilities or replacing broken processes?
  3. How will we define and measure success beyond adoption metrics?
  4. Do we have the organizational capacity to implement thoughtfully?

The most successful AI implementations start with clear problems and measurable goals, then find the right technology to solve them—not the other way around.

The Real Competitive Advantage

AI's transformative potential is real, but it requires strategic and operational discipline to unlock. The teams that resist checkbox pressure and focus on meaningful implementation will build competitive advantage while others chase AI trends.

Your investors want to see AI driving differentiated growth, not just operational efficiency. Give them both by being intentional about where and how you deploy this powerful technology.