AI PC: The future is local

What does AI PC mean?

AI PC is the latest in a string of technological promises. Microsoft and Apple have launched new computers with built-in local AI and custom-designed chips – but what does the term actually cover?

And what does it mean for those of you who work with endpoint management and security?

We may be on the threshold of a future where IT departments no longer primarily have to install software – but instead ensure that users’ local AI assistants perform their tasks correctly, are properly configured, and are deactivated when necessary.

But what does it really mean when our endpoints suddenly run powerful language models directly on the chip?

  • What security requirements does this pose?
  • How do we control what users have access to?
  • And how do we centrally manage and restrict it – without stifling the user experience?

Both Microsoft and Apple have joined the fray – and although the solutions are different, they both point in the same direction:

We are moving away from AI as a cloud-only solution and towards a hybrid model where AI moves closer to the user – directly onto the device.

But what exactly is an AI PC?

An AI PC differs from your “regular” PC by having:

  • A dedicated NPU (Neural Processing Units) to run AI models locally
  • Optimized chips from Apple (M-series), Qualcomm (Snapdragon X), AMD and Intel
  • Built-in support for AI features such as Recall, Live Captions, AI Resume, local image understanding, summarize my day, etc.

Why local AI?

It’s not just hype – there are good technical and practical reasons to run AI locally:

  • Privacy: Sensitive data never leaves the device – ideal for regulated environments and confidential communications.
  • Latency: Instant response – without waiting for cloud services.
  • Performance: Today’s AI PCs are equipped with NPUs that can run AI workloads efficiently.
  • Local context understanding: Local AI can understand and interact with the apps you’re working in – and suggest actions that fit your workflow.
  • Offline mode: AI assistants can work even when you’re offline – making them particularly valuable in environments with limited network access, such as in the field, during transport or in closed networks of government agencies and critical infrastructure.

When it comes to intelligent user experiences and compliance, local AI is not just a smart feature – it’s a crucial tool.

So what? We’re still in the early stages. The features are new, the hardware requirements are high, and the software integrations are not quite as mature as we could have hoped.

But: the AI ​​PC is not science fiction. It has arrived.

The question is no longer whether it will come – but how we as IT organizations prepare for it.

What does local AI mean for client security?

When AI moves into the client itself, the threat landscape changes – and this places new demands on endpoint governance.

Here are some of the considerations that you as an IT manager should start to make:

  • New attack surfaces AI agents that have access to the user’s data and apps become a potential target for attack themselves. Can they be abused? Can they be fooled?
  • Model behavior and control How do we control which models are allowed to run? What actions are they allowed to perform? And how do we log it?
  • Data leakage from prompts If a user accidentally feeds their local AI with sensitive information – how do we ensure that they do not leave the machine?
  • Compliance and classification Can we ensure that AI only works with data that is correctly classified? And that corporate data is not mixed with personal data in AI processes
  • Policy-based management of AI features Intune and MDM tools will have to evolve – we need to be able to turn AI features on and off centrally, just as we currently control cameras, Bluetooth and USB.

Local AI on endpoints is not just a feature – it is a new runtime that you have to deal with.

Antivirus became standard. EDR became a requirement. Now we are at the same place with AI – and governance is the next natural step in endpoint management.

Those who start early will be the strongest in the shift that is already underway!