Business leaders often assume their teams are independently adopting AI. In reality, employees are hesitant to admit they don't know how to use it effectively and are waiting for formal training and a clear strategy. The responsibility falls on leadership to initiate AI education.

An effective AI strategy pairs a central task force for enablement—handling approvals, compliance, and awareness—with empowerment of frontline staff. The best, most elegant applications of AI will be identified by those doing the day-to-day work.

Unlike previous tech waves that trickled down from large institutions, AI adoption is inverted. Individuals are the fastest adopters, followed by small businesses, with large corporations and governments lagging. This reverses the traditional power dynamic of technology access and creates new market opportunities.

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.

Previous technology shifts like mobile or client-server were often pushed by technologists onto a hesitant market. In contrast, the current AI trend is being pulled by customers who are actively demanding AI features in their products, creating unprecedented pressure on companies to integrate them quickly.

C-suites are more motivated to adopt AI for revenue-generating "front office" activities (like investment analysis) than for cost-saving "back office" automation. The direct, tangible impact on making more money overcomes the organizational inertia that often stalls efficiency-focused technology deployments.

Amplitude's CEO transformed his organization not by issuing a product roadmap, but by first focusing on internal education. An "AI week" and hackathons got the engineering team using AI tools like Cursor, building belief and capability before they were tasked with creating new AI features.

Leaders often misjudge their teams' enthusiasm for AI. The reality is that skepticism and resistance are more common than excitement. This requires framing AI adoption as a human-centric change management challenge, focusing on winning over doubters rather than simply deploying new technology.

A successful AI transformation isn't just about providing tools. It requires a dual approach: senior leadership must clearly communicate that AI adoption is a strategic priority, while simultaneously empowering individual employees with the tools and autonomy to innovate and transform their own workflows.