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.

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.

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.

Pega's CTO warns leaders not to confuse managing AI with managing people. AI is software that is configured, coded, and tested. People require inspiration, development, and leadership. Treating AI like a human team member is a fundamental error that leads to poor management of both technology and people.

While AI-driven efficiency is an obvious first step, it often results in workforce reduction if company growth is flat. True differentiation and sustainable advantage come from using AI for innovation—creating new products, markets, and business models to fuel growth.

Enterprises often default to internal IT teams or large consulting firms for AI projects. These groups typically lack specialized skills and are mired in politics, resulting in failure. This contrasts with the much higher success rate observed when enterprises buy from focused AI startups.

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.

The most significant hurdle for businesses adopting revenue-driving AI is often internal resistance from senior leaders. Their fear, lack of understanding, or refusal to experiment can hold the entire organization back from crucial innovation.