The Six Colors 2025 Apple in the Enterprise Report Card has sparked plenty of conversation about Apple’s direction, areas of growth, and continued challenges with enterprise products. Jason Snell, founding editor of Six Colors, and Weldon Dodd, Kandji’s SVP of Product Strategy, unpacked the report’s findings and what they mean for Apple device administrators on a recent MacAdmins Podcast episode.
Out of the many takeaways, one theme stands out: Apple Intelligence is promising, but enterprise IT isn’t quite sold yet. This is an especially interesting finding given the pace of AI adoption in general, and the scope of Apple’s continued investment in its Intelligence features.
So, what’s causing this perception, and is it accurate? What does the future hold? Most importantly, what practical steps can admins take to mitigate adoption risk and simplify management?
Let’s dig in.
Enterprises are Interested, Cautious, and a Bit Skeptical
The data from this year's enterprise report card tells a compelling story. Over 50% of surveyed Mac admins expressed openness to deploying AI tools, whether through on-device processing or Apple's Private Cloud Compute model. Almost two-thirds of admins are actively managing Apple Intelligence features on their devices. In fact, only 19% said they weren’t managing any features, and another 18% are undecided/unsure.
When asked about their comfort level with different AI deployment models, only a third of administrators would limit usage to on-device AI models exclusively. Nearly half indicated they'd be comfortable with both on-device processing and Apple's Private Cloud Compute, while just 18% would allow everything (including 3rd party tools).
This cautious approach to full adoption reflects deeper concerns about data sovereignty and compliance requirements. As one admin noted, "We need to understand exactly what data is being sent to third-party providers and have the ability to prevent it if necessary."
What’s holding organizations back from embracing Apple Intelligence more fully? Adoption challenges and compliance concerns are creating real roadblocks for organizations eager to embrace AI.
Adoption Challenges and Compliance Concerns Remain
The data from this year's enterprise report card tells a compelling story. Over 50% of surveyed Mac admins expressed openness to deploying AI tools, whether through on-device processing or Apple's Private Cloud Compute model. Almost two-thirds of admins are actively managing Apple Intelligence features on their devices. In fact, only 19% said they weren’t managing any features, and another 18% are undecided/unsure.
When asked about their comfort level with different AI deployment models, only a third of administrators would limit usage to on-device AI models exclusively. Nearly half indicated they'd be comfortable with both on-device processing and Apple's Private Cloud Compute, while just 18% would allow everything (including 3rd party tools).
This cautious approach to full adoption reflects deeper concerns about data sovereignty and compliance requirements. As one admin noted, "We need to understand exactly what data is being sent to third-party providers and have the ability to prevent it if necessary."
What’s holding organizations back from embracing Apple Intelligence more fully? Adoption challenges and compliance concerns are creating real roadblocks for organizations eager to embrace AI.
From Control to Documentation, Enterprises Want More
IT teams are looking for more than new features; they want clarity, consistency, and predictability for managing Apple Intelligence. Specifically, there are 4 main improvements admins want to see:
- Clear and consistent controls, including centralized management: There’s a strong demand for straightforward, centralized management of Apple Intelligence. As one admin noted, "an all-encompassing 'disable Apple Intelligence' MDM key". This would offer a simple, comprehensive control to allow organizations to make a clear policy decision rather than playing catch-up with evolving feature sets.
- Granular settings: Even with new MDM restrictions for specific Apple Intelligence features (e.g., Siri, Writing Tools, Image Playground, and ChatGPT integration) the controls remain fragmented. Admins are navigating a patchwork of settings that change with each minor OS release, making compliance and enforcement moving targets.
- Consistent, detailed documentation: Enterprises require detailed documentation that goes beyond feature descriptions to include practical implementation guidance and audit procedures. For companies under strict regulatory oversight, thorough technical documentation is key for demonstrating compliance and maintaining proper governance controls.
- Predictable release schedules: Enterprise environments require reliable update schedules that provide adequate time for internal testing, security evaluation, and compliance assessment. Organizations need early notification of upcoming changes to properly evaluate potential impacts on existing systems and regulatory requirements before deployment.
So, what can admins do today? Kandji mitigates some of the biggest challenges admins face, and provides the visibility and controls needed to make informed decisions about AI deployment.
Kandji Helps Admins Wrangle the Uncertainty
Kandji offers a clear view of macOS and software usage, and provides the ability to enforce OS versioning and policy restrictions. Through Kandji's restrictions library, administrators can access granular controls for Apple Intelligence features, located in a dedicated Apple Intelligence section. This centralized approach addresses the fragmentation concerns that administrators have raised about managing these features across different updates and device types.
Unlike traditional MDM solutions that require complex scoping logic and smart groups, Kandji's intelligent deployment automatically ensures that the right policy keys are delivered to the appropriate OS versions and device types.
Kai, Kandji’s AI agent, is designed with enterprise guardrails in place. Kai supports IT teams by harnessing the power of leading AI models to deliver insights, automate workflows, and help admins make strategic decisions. This is all done without ever accessing data outside your organization or acting without your direction. With Kai, IT can spend less time digging for data and more time acting on insights.
If you want even more insights on the findings in the Apple IT space, look out for more content on the Sequence or listen to the MacAdmins Podcast with Weldon Dodd and Jason Snell for expert perspectives on managing Apple in the enterprise.