The key for go-to-market leaders to stay relevant is hands-on experience with AI. Instead of delegating, leaders should personally select an AI tool, ingest data, and go through the iterative training process. This firsthand knowledge is a rare and highly valuable skill.

AI is a 'hands-on revolution,' not a technological shift like the cloud that can be delegated to an IT department. To lead effectively, executives (including non-technical ones) must personally use AI tools. This direct experience is essential for understanding AI's potential and guiding teams through transformation.

For a critical new skill like AI, a leader should invest the time to learn it themselves first. Without foundational knowledge, you can't accurately judge the quality of the experts you hire, hindering your ability to make good decisions for years to come.

The most powerful use of AI for business owners isn't task automation, but leveraging it as an infinitely patient strategic advisor. The most advanced technique is asking AI what questions you should be asking about your business, turning it from a simple tool into a discovery engine for growth.

Simply buying an AI tool is insufficient for understanding its potential or deriving value. Leaders feeling behind in AI must actively participate in the deployment process—training the model, handling errors, and iterating daily. Passive ownership and delegation yield zero learning.

The biggest opportunity with AI isn't simply generating content or saving time on minor tasks. It is using AI as a sophisticated thought partner to challenge assumptions, surface non-obvious solutions, and ultimately raise the quality of your own strategic thinking.

Leading an AI transformation requires more than just delegation. Leaders must personally engage by building their own compounding AI 'stack'—a collection of skills, context files, and workflows. This hands-on experience is essential for developing intuition, understanding the technology's potential, and leading from the front.

Linear's COO argues that leaders cannot fully delegate AI exploration. To truly understand how new tools work and can be applied, executives must use them for their own tasks. This direct experience builds "native thinking" that is impossible to gain secondhand.

True AI leadership requires moving beyond superficial use, like treating LLMs as a better Google. To avoid being left behind, leaders must get their hands dirty with the underlying technology. This deeper understanding is what enables them to identify real business opportunities and drive meaningful adoption.