Jamf, which manages and secures Apple devices for over 70,000 customers worldwide, achieved 89% active usage of Claude Enterprise among licensed employees within eight weeks of a company-wide rollout. The software company's rapid adoption success offers a blueprint for how large organizations can integrate AI tools at scale without the typical friction of new technology deployments.

Rather than letting AI adoption happen organically across departments, Jamf's leadership built a deliberate, governed program from day one. The company paired its Claude Enterprise rollout with a governance framework that sorted use cases by risk and complexity, and a campaign that reframed AI adoption around what employees could reclaim rather than what they could optimize.

What Results Did Jamf Achieve in the First Two Months?

The numbers tell a compelling story about how quickly a well-executed AI program can scale. Beyond the 89% active usage rate, Jamf documented 285 use cases across all 16 departments, with 98 fully implemented. The company also expanded from 1,000 to 2,000 licenses in just two months, signaling strong demand from the workforce.

Perhaps most striking was the productivity impact. HR alone identified approximately 838 estimated hours saved per month from 21 implemented use cases, with 15 additional departments still completing documentation of their own time savings. The company also saw 208 employees actively creating and sharing reusable Claude Skills, custom tools built within the Claude ecosystem that other teams could leverage.

How Did Jamf Frame AI Adoption to Drive Employee Buy-In?

The key to Jamf's success lay in how the company communicated the purpose of AI to its workforce. Rather than positioning Claude as a tool to work faster or optimize existing tasks, Jamf asked a simple but powerful question: "What would our employees work on if the routine took care of itself?"

"Not all work is equal. Some work requires your full attention, judgment, and creativity. Some just fills your day. Our AI program exists to help every employee find that difference," said Melissa Dunham, Senior Director of Information Technology at Jamf.

Melissa Dunham, Senior Director of Information Technology at Jamf

This framing addressed a real problem Jamf had identified: as the company grew globally across service desk, infrastructure, and client platform engineering functions, skilled employees were spending significant hours on documentation, communications drafting, information synthesis, and policy navigation. That work was necessary, but it was crowding out the analytical depth and creative judgment that made these roles valuable in the first place.

Steps to Implement an Enterprise AI Program Like Jamf's

• Build a Governance Framework First: Sort use cases by risk and complexity before rollout to ensure responsible deployment and reduce adoption friction across departments.
• Reframe the Narrative: Position AI as a tool to reclaim time from routine work rather than as a way to optimize existing tasks, which helps employees see personal benefit.
• Enable Skill Creation and Sharing: Encourage employees to build reusable Claude Skills and share them across teams, creating a multiplier effect for adoption and innovation.
• Track and Document Use Cases: Systematically document implemented use cases across all departments to identify patterns, measure impact, and guide expansion decisions.
• Pair Rollout with Clear Communication: Launch a campaign that explains what employees can reclaim, not just what they can optimize, to drive engagement from day one.

Jamf's approach also included building an interactive AI Department Scorecard with Claude in roughly eight hours, which department leaders now review weekly. This real-time visibility into adoption and impact helped maintain momentum and allowed leadership to identify emerging use cases and bottlenecks.

The Jamf case study demonstrates that enterprise AI adoption doesn't require months of planning or extensive change management when the program is built around genuine employee needs. By focusing on what employees could reclaim rather than what they could optimize, and by providing a clear governance structure and tools for sharing solutions, Jamf achieved adoption rates that many organizations would consider exceptional. The company's experience suggests that the bottleneck for AI adoption in large organizations may not be the technology itself, but rather how it is framed and deployed.

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