Where to Start with AI: A Practical Guide for GTM Teams

"The pressure to adopt AI is real. But pressure without direction leads to experiments that don't stick, tools that don't get used, and teams that grow more skeptical. Why? Because AI output didn't lead to actual outcomes."

"Here's what I've learned from watching teams that succeed with AI: they don't start with AI. They start with a problem. A specific, painful, time-consuming part of their work that they want to fix. Then, they find the right AI use case to achieve that goal."

"As they see results, their confidence grows, and they explore other AI capabilities - again, tied to a clear goal. That's the approach I want to share. Not an exhaustive list of everything AI can do, but a practical guide to where marketing, sales, and service teams can get started and see real value with AI."

Business leaders face pressure to adopt AI but often lack clear direction, resulting in failed experiments and skeptical teams. The key to successful AI implementation is reversing the typical approach: start with a specific, painful business problem rather than exploring AI capabilities first. Teams that succeed identify concrete challenges in their workflows, then find appropriate AI solutions to address them. As results materialize, confidence grows and teams explore additional AI applications. This practical methodology focuses on achieving real business outcomes rather than implementing AI for its own sake. HubSpot categorizes AI use cases by maturity level—Established (reliable and repeatable), Emerging (available and improving), and Early (experimental)—to help teams choose appropriate starting points based on their readiness and risk tolerance.

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