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.
Contrary to the impulse to automate busywork, leaders should focus their initial AI efforts on their most critical strategic challenges. Parkinson's Law dictates that low-value tasks will always expand to fill available time. Go straight to the highest-leverage applications to see immediate, significant results.
Business owners should view AI not as a tool for replacement, but for multiplication. Instead of trying to force AI to replace core human functions, they should use it to make existing processes more efficient and to complement human capabilities. This reframes AI from a threat into a powerful efficiency lever.
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.
Treat AI initiatives as two separate strategic pillars. Create one roadmap focused on internal efficiency gains and cost reduction (productivity). Maintain a separate roadmap for developing new, revenue-generating customer experiences (growth). This prevents conflating internal tools with external products.
When employees are 'too busy' to learn AI, don't just schedule more training. Instead, identify their most time-consuming task and build a specific AI tool (like a custom GPT) to solve it. This proves AI's value by giving them back time, creating the bandwidth and motivation needed for deeper learning.
Shifting the mindset from viewing AI as a simple tool to a 'digital worker' allows businesses to extract significantly more value. This involves onboarding, training, and managing the AI like a new hire, leading to deeper integration, better performance, and higher ROI.
Employees progress through three stages of AI adoption: 1) Fearing AI will take their job, 2) Fearing a person using AI will take their job, and 3) Realizing they cannot perform their job without AI. Leaders must actively guide their organization to this third level of indispensability.
To achieve employee buy-in for AI, position it as a tool that eliminates mundane tasks no one would put on a resume, like processing Salesforce cases. This frames AI as a career accelerator that frees up time for strategic, high-impact work, rather than as a job replacement.
To gain organizational buy-in for AI, start by asking teams to document their most draining, repetitive daily tasks. Building agents to eliminate these specific pain points creates immediate value, generates enthusiasm, and builds internal champions for broader strategic initiatives, making it an approachable path to adoption.