Don't try to optimize your strongest departments with your first AI project. Instead, target 'layup roles'—areas where processes are broken or work isn't getting done. The bar for success is lower, making it easier to get a quick, impactful win.

To overcome employee fear of AI, don't provide a general-purpose tool. Instead, identify the tasks your team dislikes most—like writing performance reviews—and demonstrate a specific AI workflow to solve that pain point. This approach frames AI as a helpful assistant rather than a replacement.

AI's primary value isn't replacing employees, but accelerating the speed and quality of their work. To implement it effectively, companies must first analyze and improve their underlying business processes. AI can then be used to sift through data faster and automate refined workflows, acting as a powerful assistant.

Companies can either augment existing processes with AI for incremental efficiency (e.g., co-pilots) or completely redesign workflows. While augmentation is common, the most transformative value and disruptive business models will emerge from a clean-sheet redesign of how work is done.

Bill Glenn suggests a phased AI rollout for teams. Phase 1 focuses on efficiency and automating repeatable tasks to gain productivity. Phase 2 moves to strategic work, using AI for insights and decision-making assistance. This provides a clear, manageable roadmap for adoption.

The historical adoption of electricity in factories shows that true productivity gains came from redesigning the factory floor, not simply replacing steam engines. Similarly, companies must fundamentally re-engineer processes around AI to unlock its transformative potential.

The true power of AI is unlocked by adopting an "AI First" approach. This means completely redesigning workflows with AI at the core, rather than simply using AI to accelerate existing processes. This shifts employees' roles from performing tasks to managing the AI agents that do the work.

To get mainstream users to adopt AI, you can't ask them to learn a new workflow. The key is to integrate AI capabilities directly into the tools and processes they already use. AI should augment their current job, not feel like a separate, new task they have to perform.

Instead of leading with automation that breeds fear, companies should prioritize AI use cases that remove tedious work and enhance employee capabilities. This pragmatic, human-centric approach builds trust and accelerates adoption more effectively than a pure ROI focus.