When boards pressure CEOs for AI, the result is often a centralized, consultant-led project disconnected from operations. These initiatives fail because they lack alignment and nobody understands how they work, creating skepticism for future efforts.

A critical error in AI integration is automating existing, often clunky, processes. Instead, companies should use AI as an opportunity to fundamentally rethink and redesign workflows from the ground up to achieve the desired outcome in a more efficient and customer-centric way.

Faced with an "AI mandate," many companies try to force-fit AI onto their current offerings, leading to failure. The correct first step is a fundamental assessment: is this problem even a good candidate for AI, or does the entire product need to be reimagined from the ground up?

Unlike traditional software, AI adoption is not about RFPs and licenses but a fundamental mindset shift. It requires leaders to champion curiosity and experimentation. Treating AI like a standard IT project ignores the necessary changes in workflow and thinking, guaranteeing failure.

Creating an "AI initiative" can be a mistake, as it encourages tool usage for its own sake. A better approach is to set the expectation that team members will deliver the best possible outcome, knowing AI exists, shifting the focus from process to high-quality results.

Simply giving AI tools to existing departments like legal or finance yields limited productivity gains. The real unlock is to reimagine and optimize end-to-end, cross-functional processes (e.g., 'onboarding a new supplier'). This requires shifting accountability from departmental silos to process owners who can apply AI holistically.

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.

Companies fail with AI when executives force it on employees without fostering grassroots adoption. Success requires creating an internal "tiger team" of excited employees who discover practical workflows, build best practices, and evangelize the technology from the bottom up.

To avoid issues like Amazon's AI-related outages, companies should highlight and incentivize early, enthusiastic adopters within the organization. Holding up their successful use cases fosters organic adoption and establishes best practices, which is more effective than forced, top-down mandates.