Jamf in the age of agentic IT: An interview with CEO Beth Tschida
Computerworld ·
Jamf was a pioneer in Apple device management when it began in 2002. The company was ahead of its time: its founders could see that Apple had a future in the enterprise, but not many others saw it. Jamf now runs 35.2 million devices from 78,000 organizations. And it’s still looking to the future. I spoke with Jamf CEO Beth Tschida, who joined me for a chat directly after her keynote speech at JNUC , Jamf’s big event for Mac admins, on September 23. The AI-driven ecosystem Tschida wasn’t there to rehash Jamf’s past for relevance in the present, but to share the company’s deep commitment to being where its customers are going to go. That means artificial intelligence, which in Jamf’s case involves weaving AI across its ecosystem of products, from setup to tech support, security, and beyond. It’s not a new vision — you could argue that some early signs of its intention were visible when the company acquired ZecOps in 2022 — but time moves forward and the company has coalesced around a firm philosophy of how to use AI, where to use AI, and how AI should be deployed in a human-centric way for the benefit of its customers. “AI runs better on Apple, and Apple runs better on Jamf,” Tschida told me. The next piece to that statement is to consider how AI can be effectively managed by IT, she added. “You have to be able to see it. You have to be able to govern it, and then you want to be able to harness it.” This points directly to shadow AI, one of the big-picture problems IT has with AI at the moment as employees feed confidential data to the cloud-based AI models. Jamf’s response has been to create new frameworks IT can use to monitor use of AI across their managed fleets. These tools let IT identify use, manage use, or even stop use altogether. “How can we look at that, see it, govern it, and harness it in the ways that AI is providing that opportunity, right at the endpoint?” Tschida said. Precision modeling The other component is pricing. Even when data is legitimately shared to AI, the cost of inferencing is high and getting higher. Jamf now offers tools to let IT monitor this use and the cost of it, enabling management to suggest lower cost or on-prem AI solutions for tasks where appropriate. After all, why would you pay for Fable when you can get your Apple device to help write that letter? Tschida explained that part of Jamf’s response to AI costs is the inclusion of granular model controls, which let admins assign different teams access to different models, the idea being to prevent what she called “overmodeling” — the use of expensive high-reasoning models for tasks that lightweight models can handle. “You have to understand what the need is. You must lay it out there in a governed way. Human in the loop and then you harness it,” she said. The Mac advantage But the Jamf vision doesn’t end with AI management; it extends to making active use of the tech. In this case the company has introduced AI-powered tech support for routine problems to free up staff time. There are two strands to this approach: More obviously, easy to access tech support should reduce time spent on routine problem solving, but another compelling aspect of this evolution is the move toward proactive device health. Traditionally, IT has been reactive: a user experiences slowness, they eventually file a ticket, and IT fixes it. But many users simply “endure” suboptimal performance without ever reporting it, Tschida explained. “A lot of times, users don’t even raise a ticket. They just endure.” That was then, but the future looks different. “We believe that we now have the right telemetry to look at device health,” Tschida said. “You’re really moving ahead of problems. Users don’t even raise a ticket… you can help them optimize it without them knowing it.” With over 35 million devices now managed using Jamf, the origin story of the company seems further ahead of its time now than ever. Apple’s enterprise product marketing lead, Jeremy Butcher, appeared at one point during Tschida’s keynote to talk about where Apple now is in the enterprise. He pointed to data that Macs generate 55% fewer help tickets than Windows systems. He confirmed that the MacBook Neo has accelerated enterprise growth for the platform, and pointed out that more Apple devices are purchased in enterprise than any other brand. With so much energy behind Apple’s platforms, what has Tschida been seeing? “We know that Anthropic and other companies, they tend to deploy for Mac first. The developers are mostly running Macs. That’s what they prefer to be on, and they’re at the forefront of agentic AI.” The thing about the growing enterprise Apple ecosystem is that no single company can build the perfect set of solutions for every enterprise. Part of Jamf’s response to this has been the creation of platform APIs, which customers and partners can use to extend the platform to meet their needs. “I love a good API because it allows you to run a road map way faster,” Tschida said. Former Jamf CEO Dean Hager used to say , “When Apple innovates, Jamf celebrates.” His successor echoes his point, with a focus on what Jamf can do for its customers. “Our job is to make sure that Apple runs better with Jamf,” she said. “We’re scaling it, we’re securing it, and we’re making sure that you can… first see it, and govern it, and then harness what you can get from it in a way that’s helpful for our customers.” Local intelligence, global scale A second aspect to governance is around sovereign, private, and/or on-premises AI. I asked Tschida what her customers are saying. “There will be some that look at the benefit if you can run at least some of your workflows locally,” she said. “There’s a tokenomics piece of it. There’s a privacy piece of it. There’s a sovereignty piece of it.” Whatever the motivation, for Jamf the question remains, “How can you determine what we can do and help you do, locally on device, and build that so you can run it at scale? That’s where we’re focused.” I walked away from the interview feeling a vision for Apple in the enterprise in which IT is augmented by smart tech infrastructure: Macs that request support before users know they need it, systems that self-identify bottlenecks or wasted resources such as over-generous token consumption and let IT take steps. A more intelligent enterprise infrastructure, equipped with real-time awareness, self-reliant with little to no cloud exposure. For Apple, Jamf, and certainly for the Mac, that seems like several giant steps since the foundation of Jamf in 2002. AI in IT is an accelerant, and Jamf is working with it. “We are doing our best to run at the speed of AI,” said Tschida. Now please subscribe to my daily, human-curated Apple-related news headline feed at The Core , or follow me on BlueSky , LinkedIn , or Mastodon .
Jamf was a pioneer in Apple device management when it began in 2002. The company was ahead of its time: its founders could see that Apple had a future in the enterprise, but not many others saw it. Jamf now runs 35.2 million devices from 78,000 organizations. And it’s still looking to the future. I spoke with Jamf CEO Beth Tschida, who joined me for a chat directly after her keynote speech at JNUC , Jamf’s big event for Mac admins, on September 23. The AI-driven ecosystem Tschida wasn’t there to rehash Jamf’s past for relevance in the present, but to share the company’s deep commitment to being where its customers are going to go. That means artificial intelligence, which in Jamf’s case involves weaving AI across its ecosystem of products, from setup to tech support, security, and beyond. It’s not a new vision — you could argue that some early signs of its intention were visible when the company acquired ZecOps in 2022 — but time moves forward and the company has coalesced around a firm philosophy of how to use AI, where to use AI, and how AI should be deployed in a human-centric way for the benefit of its customers. “AI runs better on Apple, and Apple runs better on Jamf,” Tschida told me. The next piece to that statement is to consider how AI can be effectively managed by IT, she added. “You have to be able to see it. You have to be able to govern it, and then you want to be able to harness it.” This points directly to shadow AI, one of the big-picture problems IT has with AI at the moment as employees feed confidential data to the cloud-based AI models. Jamf’s response has been to create new frameworks IT can use to monitor use of AI across their managed fleets. These tools let IT identify use, manage use, or even stop use altogether. “How can we look at that, see it, govern it, and harness it in the ways that AI is providing that opportunity, right at the endpoint?” Tschida said. Precision modeling The other component is pricing. Even when data is legitimately shared to AI, the cost of inferencing is high and getting higher. Jamf now offers tools to let IT monitor this use and the cost of it, enabling management to suggest lower cost or on-prem AI solutions for tasks where appropriate. After all, why would you pay for Fable when you can get your Apple device to help write that letter? Tschida explained that part of Jamf’s response to AI costs is the inclusion of granular model controls, which let admins assign different teams access to different models, the idea being to prevent what she called “overmodeling” — the use of expensive high-reasoning models for tasks that lightweight models can handle. “You have to understand what the need is. You must lay it out there in a governed way. Human in the loop and then you harness it,” she said. The Mac advantage But the Jamf vision doesn’t end with AI management; it extends to making active use of the tech. In this case the company has introduced AI-powered tech support for routine problems to free up staff time. There are two strands to this approach: More obviously, easy to access tech support should reduce time spent on routine problem solving, but another compelling aspect of this evolution is the move toward proactive device health. Traditionally, IT has been reactive: a user experiences slowness, they eventually file a ticket, and IT fixes it. But many users simply “endure” suboptimal performance without ever reporting it, Tschida explained. “A lot of times, users don’t even raise a ticket. They just endure.” That was then, but the future looks different. “We believe that we now have the right telemetry to look at device health,” Tschida said. “You’re really moving ahead of problems. Users don’t even raise a ticket… you can help them optimize it without them knowing it.” With over 35 million devices now managed using Jamf, the origin story of the company seems further ahead of its time now than ever. Apple’s enterprise product marketing lead, Jeremy Butcher, appeared at one point during Tschida’s keynote to talk about where Apple now is in the enterprise. He pointed to data that Macs generate 55% fewer help tickets than Windows systems. He confirmed that the MacBook Neo has accelerated enterprise growth for the platform, and pointed out that more Apple devices are purchased in enterprise than any other brand. With so much energy behind Apple’s platforms, what has Tschida been seeing? “We know that Anthropic and other companies, they tend to deploy for Mac first. The developers are mostly running Macs. That’s what they prefer to be on, and they’re at the forefront of agentic AI.” The thing about the growing enterprise Apple ecosystem is that no single company can build the perfect set of solutions for every enterprise. Part of Jamf’s response to this has been the creation of platform APIs, which customers and partners can use to extend the platform to meet their needs. “I love a good API because it allows you to run a road map way faster,” Tschida said. Former Jamf CEO Dean Hager used to say , “When Apple innovates, Jamf celebrates.” His successor echoes his point, with a focus on what Jamf can do for its customers. “Our job is to make sure that Apple runs better with Jamf,” she said. “We’re scaling it, we’re securing it, and we’re making sure that you can… first see it, and govern it, and then harness what you can get from it in a way that’s helpful for our customers.” Local intelligence, global scale A second aspect to governance is around sovereign, private, and/or on-premises AI. I asked Tschida what her customers are saying. “There will be some that look at the benefit if you can run at least some of your workflows locally,” she said. “There’s a tokenomics piece of it. There’s a privacy piece of it. There’s a sovereignty piece of it.” Whatever the motivation, for Jamf the question remains, “How can you determine what we can do and help you do, locally on device, and build that so you can run it at scale? That’s where we’re focused.” I walked away from the interview feeling a vision for Apple in the enterprise in which IT is augmented by smart tech infrastructure: Macs that request support before users know they need it, systems that self-identify bottlenecks or wasted resources such as over-generous token consumption and let IT take steps. A more intelligent enterprise infrastructure, equipped with real-time awareness, self-reliant with little to no cloud exposure. For Apple, Jamf, and certainly for the Mac, that seems like several giant steps since the foundation of Jamf in 2002. AI in IT is an accelerant, and Jamf is working with it. “We are doing our best to run at the speed of AI,” said Tschida. Now please subscribe to my daily, human-curated Apple-related news headline feed at The Core , or follow me on BlueSky , LinkedIn , or Mastodon .