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On-Device AI Is Here: See How It Changes Productivity, Security, and Cost

Publish Date: 10-31-2025
 

Until now, most companies interested in artificial intelligence have adopted cloud-based AI. These are applications and large language models (LLMs) hosted in data centers, accessible through the internet. However, a new approach to using AI has gained popularity: on-device AI.

Instead of relying on the cloud, on-device AI runs locally on your PC or endpoint device. With the arrival of Copilot+ PCs, Dell AI-enabled systems, and edge-based intelligence, IT leaders now have a practical way to deliver smarter, faster, and more private AI tools directly to employees.

Learn what on-device AI works and why it will change enterprise AI innovation.

Dawn of On-Device Intelligence

On-device AI runs directly on your device rather than relying on data transmission to and from cloud servers. This type of AI is designed to be smaller, faster, and more energy-efficient, enabling it to deliver real-time intelligence without constant internet connectivity.

For enterprises, this means employees can utilize transcription, content generation, workflow automation, and other AI-driven features without the latency typically associated with cloud services. Moreover, sensitive information stays on the device. This gives people working in industries such as healthcare, finance, and law the confidence to use AI without fear of breaking compliance rules regarding privacy.

Several catalysts have made deploying AI on devices possible:

  • Machine learning frameworks like PyTorch Mobile and TensorFlow Lite support the deployment of AI models directly onto devices.
  • Graphics Processing Units (GPUs) can handle multiple operations and speed up AI processes on devices. Although they were originally designed for rendering graphics, GPUs are great at parallel processing. This means they can handle the vector and matrix calculations common in AI tasks.
  • Neural processing units (NPUs) are optimized to perform AI-related calculations efficiently.

On-Device vs. Cloud AI

In traditional cloud-based AI, devices send data to remote servers, where models perform inference (processing) and return results.

On-device AI, in contrast, keeps inference on the endpoint device itself. It uses specialized hardware, such as NPUs, to handle AI tasks efficiently.

Compared to the cloud, on-device AI offers several advantages:

  • Lower latency: Your results arrive in milliseconds, not seconds.
  • Offline functionality: This is essential for mobile employees and field workers.
  • Enhanced privacy: Sensitive data always stays on the device, lowering the risk of sensitive data exposure or data breaches.
  • Reduced bandwidth costs: On-device AI means less reliance on constant data transfer.
  • Stronger compliance controls: On-device AI gives IT teams greater control over data handling. This reduces exposure risks and limits dependence on third-party providers that may be vulnerable to breaches.

Revolutionizing Productivity

The biggest advantage of on-device AI is its power to reshape how work gets done. Dell Copilot, one of the leading providers of on-device AI, is leading this transformation. Here’s how enterprise PCs equipped with Dell Copilot and NPUs enable AI for productivity:

  • Instant access with Dell Copilot: With Copilot built into Dell’s AI PCs, there’s no lengthy setup or reliance on the cloud. The minute you turn on the computer, you can start drafting emails, generating meeting summaries, or pulling insights.
  • Seamless workflow integration: Copilot is directly embedded into apps employees already use, like Outlook, Teams, and Word. As such, they don’t have to waste time juggling or switching tools.
  • Enhanced communication: Thanks to Copilot’s Live Captions and real-time translations, teams can communicate easily across languages. That’s especially powerful for global SMBs and enterprises with distributed teams.
  • Improved content creation: Copilot can generate content quickly and securely without relying on external servers.
  • Streamlined operations: Voice commands and AI-driven navigation simplify everyday interactions. In industries like healthcare, logistics, or manufacturing, employees can go hands-free and focus on core tasks. Meanwhile, the system handles navigation.
  • Learning and skill development: Instead of generic training paths, Copilot can analyze work patterns to recommend upskilling opportunities tailored to each employee.

Fortifying Security and Privacy

Besides revolutionizing productivity, on-device AI can also strengthen security and privacy posture. Here’s how:

  • Data stays local: Since AI processing happens solely on the device, sensitive data like financial records, intellectual property, or patient files never leaves the endpoint.
  • Mitigating threats: By minimizing cloud dependency, organizations reduce attack surfaces like API calls or cross-network data transfers.
  • User control and compliance: With processing contained within managed endpoints, IT teams can better enforce compliance with frameworks like GDPR and HIPAA.
  • Dell’s Zero Trust framework: Dell Copilot+ PCs come with Dell’s enterprise-grade Zero Trust architecture. As such, IT leaders get a secure foundation for deploying AI without compromising compliance.

Lower Costs

On-device AI doesn’t just boost productivity and strengthen security and privacy. It can also help you save more in the following ways:

  • From operational to capital expenditure: Cloud AI often comes with ongoing subscription fees and compute costs, which can add up over time. In contrast, on-device AI typically only requires a one-time hardware investment, such as AI PCs equipped with NPUs. This means budgets are more predictable.
  • Comprehensive cost analysis: Because on-device AIs process data locally, organizations use less bandwidth and storage expenses. For enterprises with thousands of employees generating AI queries, these savings can add up significantly over time.
  • Indirect cost savings: On-device AI has faster response times than its cloud counterpart. This means projects move faster, errors decrease, and employees spend less time waiting for results. All of these, in turn, reduce hidden costs like overtime hours, delayed deliverables, and lost opportunities from stalled decision-making.
  • Energy efficiency: On-device AI relies on NPUs to run models locally rather than sending data back and forth to the cloud. Designed specifically for low-power AI workloads, NPUs can handle inference and automation tasks without draining the battery or incurring excessive energy consumption. As such, you’ll enjoy lower utility costs, longer device lifecycles, and AI performance that doesn’t come at the expense of power consumption.

Delve Deeper Into Productivity

On-device AI is a long-term investment that unlocks new productivity, improves security, and provides significant cost benefits.

If you’re curious how these tools work or how to deploy them across your organization, don’t miss Elevate User Community's four-part webinar series, AI PCs in Action. Episode 1, AI for Productivity, features in-depth demos of Copilot+ PCs and use cases. To start adopting on-device AI, check out our guide on choosing the right AI PC. It explains how to evaluate device options and simplify the refresh cycle with Dell and Verizon’s enterprise solutions.