When reporting on AI experiments to the board, avoid using "learning" as a primary KPI, as it can sound like an excuse for failure. Instead, translate those learnings into tangible outcomes and demonstrable progress toward goals, showing what impact the learning has and promises.

Generic use cases fail to persuade leadership. To get genuine AI investment, build a custom tool that solves a specific, tangible pain point for an executive. An example is an 'AI board member' trained on past feedback to critique board decks before a meeting, making the value undeniable.

The quality of a leader's own AI usage directly impacts their team's success with the technology. When CEOs are the most adept users, they set realistic expectations, avoid under or over-estimating capabilities, and inspire more effective organizational adoption.

To drive genuine AI transformation, leaders cannot just delegate. Zapier's executive team holds "AI show and tell" sessions where each member presents their own hands-on AI use cases. This demonstrates commitment, builds practical knowledge of AI's limits, and ensures leadership's vision is authentic.

To get teams to embrace AI, leaders should ditch generic mandates like "use more AI." Instead, focus on specific business transformations and highlight the customer value they create. Using company-wide forums for "show and tell" sessions where teams demonstrate unarguable successes makes adoption organic and outcome-driven, not a top-down chore.

Unlike past IT projects delegated to a CIO, AI initiatives are now a top priority discussed by CEOs on earnings calls. This high-level visibility, coupled with executives admitting they aren't seeing results, creates intense internal pressure to prove the financial return on AI spending.

CEOs who merely issue an "adopt AI" mandate and delegate it down the hierarchy set teams up for failure. Leaders must actively participate in hackathons and create "play space" for experimentation to demystify AI and drive genuine adoption from the top down, avoiding what's called the "delegation trap."

The gap between CEOs' optimistic view of AI and the messy reality of implementation isn't new. It mirrors the long-standing challenge operations teams face in explaining the hidden complexity of their work to leadership. AI simply raises the stakes and expectations.

When leadership pays lip service to AI without committing resources, the root cause is a lack of understanding. Overcome this by empowering a small team to achieve a specific, measurable win (e.g., "we saved 150 hours and generated $1M in new revenue") and presenting it as a concise case study to prove value.