"You've conquered the enthusiasts. Now comes the harder part: reaching everyone else. Employees using AI effectively save 5.4% of work time weekly -over two hours per 40-hour week. At a company of 5,000, if just half of employees achieve that efficiency gain, you've created the equivalent of 125 additional full-time employees without increasing headcount. The opportunity is massive. But scaling from early adoption to majority usage requires understanding why most people resist new technology-and what changes their minds."
"Geoffrey Moore's Crossing the Chasm [1] explains your AI adoption challenge precisely. Technology adoption follows a predictable curve: Innovators (2.5%) try new technology because it's interesting. Early Adopters (13.5%) see strategic advantage and tolerate imperfection. Then comes the chasm-the critical gap between enthusiasts and pragmatists. On the other side sit the Early Majority (34%), who need proven ROI and peer validation, the Late Majority (34%), who adopt only under pressure, and Laggards (16%), who resist until forced."
Organizations often have a few hundred AI users despite thousands of licenses; significant efficiency gains are possible if the majority adopt. Adoption follows Moore's technology adoption curve with a chasm between early adopters and the majority who need proven ROI and peer validation. The tipping point emerges when social proof makes adoption organic. Majority users require practice-focused, role-specific workflows, clear ROI, and integrated tools rather than information-based eLearning. Scaling requires playbooks, manager incentives, safety guardrails, and measurement to embed AI into day-to-day processes and convert enthusiasts into mainstream users.
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