For executives to truly drive AI adoption, simply using the tools isn't enough. They must model three key behaviors: publicly setting a clear vision for AI's role, actively participating in company-wide learning initiatives like hackathons, and empowering employees with the autonomy to experiment.

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.

While empowering employees to experiment with AI is crucial, Snowflake found it's ineffective without an executive mandate. If the CEO doesn't frame AI as a top strategic initiative, employees will treat it as optional, hindering real adoption. Success requires combining top-down leadership with bottom-up innovation.

To drive AI adoption, CMO Laura Kneebush avoids appointing a single expert and instead makes experimentation "everybody's job." She encourages her team to start by simply playing with AI for personal productivity and hobbies, lowering the barrier to entry and fostering organic learning.

Simply instructing engineers to "build AI" is ineffective. Leaders must develop hands-on proficiency with no-code tools to understand AI's capabilities and limitations. This direct experience provides the necessary context to guide technical teams, make bolder decisions, and avoid being misled.

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.

According to Techstars' CEO David Cohen, standout AI companies are defined by their leadership. The CEO must personally embody an "AI-first" mindset, constantly thinking about leverage and efficiency from day one. It's not enough to simply lead a team of engineers who understand AI; the strategic vision must originate from the top.

Organizations fail when they push teams directly into using AI for business outcomes ("architect mode"). Instead, they must first provide dedicated time and resources for unstructured play ("sandbox mode"). This experimentation phase is essential for building the skills and comfort needed to apply AI effectively to strategic goals.

While senior leaders are trained to delegate execution, AI is an exception. Direct, hands-on use is non-negotiable for leadership. It demystifies the technology, reveals its counterintuitive flaws, and builds the empathy required to understand team challenges. Leaders who remain hands-off will be unable to guide strategy effectively.