What Is Possible Today, What IT Managers Need to Know – and Why Modern Device Fleets Are Becoming a Strategic Requirement
Artificial intelligence (AI) is no longer an isolated tool that has to be consciously launched. Today, it is an integral part of modern smartphones and tablets — embedded directly into operating systems, standard applications, and assistant features.
For IT managers, this fundamentally changes the starting point:
AI is no longer something that needs to be introduced — it is already here. And it is increasingly being used in mobile, context-aware, and performance-dependent ways.
The key question is therefore no longer whether AI should be used, but rather how employees can be enabled to use these new possibilities productively without sacrificing security, control, and digital sovereignty.
AI Is Going Mobile — A Quiet but Profound Development
Over the past few years, AI has rapidly evolved from specialized applications into everyday functionality. Studies by McKinsey & Company show that generative AI is already being used in more than 60% of companies — often initially in informal and decentralized ways. The entry point is increasingly the mobile device. Translations, text suggestions, automatic summaries, and image analysis are now used on the go — quickly, situationally, and often without a deliberate decision “to use AI.”
Mobile devices are therefore becoming the place where AI becomes tangibly real in day-to-day business operations.
Which AI Technologies Are Already Standard — and What Is Coming Next
A large portion of AI usage today no longer happens through separately installed tools, but through integrated features. Modern operating systems already include AI capabilities embedded into: email applications, note-taking tools, camera systems, and search functions. This type of AI is “silent” — it operates in the background without employees necessarily perceiving it as a standalone technology.
Alongside this, consciously used AI applications still exist. These are usually cloud-based, use separate user accounts, and enable highly powerful — but also more sensitive — use cases.
For businesses, this distinction is crucial:
Not every use of AI is visible — but every use has an impact.
On-Device or Cloud? Why Device Performance Suddenly Matters
One major trend described by Gartner is the increasing shift of AI functionality directly onto the endpoint device.
The reason is simple:
On-device AI enables faster responses, reduces dependency on cloud services, and — when implemented correctly — can provide data protection advantages.
At the same time, cloud-based AI remains important wherever extremely high computing power or rapid model updates are required.
In practice, a hybrid model is emerging. What matters most is this:
The more modern the device, the more AI functions can be used locally and securely.
Which Devices Are Already Reaching Their Limits
Realistically, a clear trend is already visible today:
- Current AI capabilities require powerful processors, dedicated AI hardware, and long-term operating system support.
- Devices with limited update support or without dedicated AI components will continue to function — but they will no longer offer the full range of features.
As a general guideline:
- Within the Apple ecosystem, AI capabilities unfold their full potential primarily on newer device generations, particularly from the iPhone 16 generation onward.
- For Android devices, the situation is similar: AI capability depends heavily on processor architecture, manufacturer support, and OS version — not simply on device age.
The point is not that “everything old is obsolete.”
The point is that AI capability is increasingly becoming a defining characteristic of modern mobile devices.
Digital Sovereignty Comes Through Enablement — Not Avoidance
Digital sovereignty does not mean avoiding technology. It means understanding, evaluating, and using technology securely.
Employees who can use AI features effectively tend to work:
- faster,
- more efficiently,
- and often with higher quality results.
Studies by Deloitte show that the technological relevance of workplace equipment directly influences productivity and innovation capacity. Outdated devices do not just limit technical possibilities — they also hinder the development of employee competencies.
Opportunities and Risks Exist Side by Side
AI assistants can provide enormous value: support for writing, summarization, research, and preparation tasks.
At the same time, risks arise when company information is unintentionally entered into external AI services or when private AI accounts are used for business purposes.
European Union Agency for Cybersecurity explicitly warns that uncontrolled AI usage — especially on mobile devices — is becoming an increasing risk for data protection and information security.
The risk does not lie in AI itself, but in the lack of transparency and missing guardrails.
Governance Instead of Prohibition — What This Means in Practice
A blanket ban on AI is hardly enforceable in a mobile-first environment — and is often counterproductive.
Successful IT organizations instead pursue a differentiated approach:
They define clear guardrails for which AI scenarios are useful and permitted, create transparency around usage, and raise employee awareness regarding risks.
Governance means:
- deliberate enablement strategies,
- clear communication instead of gray areas,
- and modern, high-performance devices as a secure foundation.
Digital sovereignty emerges where employees understand what they are allowed to do, what they should avoid, and why.
Conclusion: AI as a Productivity Multiplier — with the Right Foundation
Artificial intelligence is one of the most significant productivity amplifiers of recent years — especially on mobile devices.
However, it must not come at the expense of security, data protection, or control.
Modern device fleets are therefore a key prerequisite. They enable:
- up-to-date AI capabilities,
- modern security mechanisms,
- and long-term digital sovereignty.
Device as a Service (DaaS) directly supports this approach:
Companies avoid tying up capital, remain upgrade-ready, and ensure that employees always work with modern, high-performance devices that keep pace with technological progress.
Not every innovation needs to be used immediately.
But it should always be possible
Studies
McKinsey – The State of AI, Gartner – AI in Devices, Gartner – Edge AI, Gartner – Hybrid Ai & Edge Processing, Deloitte – Digital Workplace, Deloitte – Productivity, McKinsey – Generative AI, McKinsey – Productivity, ENISA – AI Threat Landscape, BSI – Mobile Endgeräte, BSI – Stand der Technologie, Apple – Software Support Lifecycle, Google – Update- & Security-Zyklen, Android – Update- & Security-Zyklen
Editorial Note
The cited studies and sources serve to contextualize current technological developments. Their specific relevance always depends on the type of end device, the operating system version, and the individual company situation.