HP Sees AI PCs as Enterprise Cost, Security and Growth Catalyst

Key Points

• HP sees AI PCs becoming “personal intelligence devices” as AI agents, improved chips and local model capabilities reshape enterprise computing. Devices that process AI locally could offer stronger privacy, security and governance than cloud-only systems.
• HP is advocating a hybrid AI architecture that distributes workloads among PCs, on-premises systems and the cloud. The approach aims to control rapidly rising AI costs while addressing data sovereignty, security and workload-specific performance needs.
• Local AI could create PC premiumization and recurring-revenue opportunities for HP through software, management and security services. HP estimates basic local queries could save about $650,000 per 1,000 employees, potentially justifying higher-priced AI-capable devices.

HP NYSE: HPQ is positioning the personal computer as a “personal intelligence device” as enterprises evaluate where artificial intelligence workloads should run and how to manage the costs, governance and security of AI deployments.

Speaking during The Six Five Summit 2026, Ketan Patel, President of Personal Systems at HP, said the personal-computing market is moving beyond the traditional model of users issuing commands through clicks and typing. He said AI agents, more capable hardware and growing software investment are collectively changing the role of the PC.

“The world which we are now seeing is completely different in the world of personal computing and moving to personal intelligence,” Patel said.

Agents, local models and more capable PCs

Patel said three trends are driving the change: adoption of AI agents, the need for people and agents to work together under appropriate governance, and the increasing ability of PCs to run larger AI models locally.

He said nearly 72% of organizations are deploying or piloting agents, which he expects will increase the intelligence required on end-user devices. These agents could work autonomously as companions to users, rather than requiring users to provide every command, he said.

Patel also argued that the PC is suited to personalized AI because it can support the interaction, security and governance requirements that vary among users. New silicon and system architectures are bringing more data-center-like capabilities to devices, he said, adding that some architectures can host 120 billion-parameter models locally.

Ryan Shrout, President of Signal65, said AI PCs represent a real market shift, though he acknowledged that marketing is also part of the discussion. He said hardware assessments are increasingly considering memory capacity, data locality and the size of models that can run on a device, rather than focusing only on neural processing units or higher-end graphics processors.

Shrout said enterprises are increasingly aware of the potential security, privacy and cost advantages of local AI processing. However, he said software changes will be needed to support broader adoption.

Nick Patience, Vice President and Practice Lead of Artificial Intelligence Software and Tools at The Futurum Group, said enterprise IT policies have yet to fully catch up with device capabilities. In particular, organizations need frameworks for deciding which workloads should operate locally and which should run in the cloud, he said.

Hybrid AI and token economics

Patel described HP’s view of the future as a hybrid or distributed AI model, in which cloud infrastructure remains important for large-scale model training and deep-reasoning work, while inference workloads are distributed across devices, on-premises infrastructure and cloud services.

He said rising AI usage costs are making those architecture decisions a CFO-level concern. Patel cited feedback from a customer roundtable in which one company’s spending on model access for employees had risen from $20 million in the prior year to between $200 million and $300 million in the current year.

“This is about really from experimentation or pilots to maybe moving to profits,” Patel said, referring to the need for businesses to assess the return on investment from AI usage.

According to Patel, current laptops can host a 20 billion-parameter open-source model locally, while on-premises systems can host models with up to a trillion parameters. He said a hybrid system could allow enterprises to direct requests to device, on-premises or cloud models while balancing user experience, economics, security and governance.

Data sovereignty is another key factor, Patel said. Enterprises may want access to the latest AI capabilities while keeping proprietary information from becoming public or leaving their premises. Under a distributed approach, he said, certain data can remain on-premises while signals are sent to cloud services for processing.

HP’s role in enterprise AI deployment

Patel said HP’s approach centers on three layers:

• Intelligent devices, including PCs, printers, room systems, workstations and peripherals;
• A workplace ecosystem designed to help AI agents operate across connected devices and infrastructure; and
• An IT control plane for deploying, managing and securing devices and agents.

He said future PCs will offer more context awareness through audio, video and sensing capabilities, using the device’s combination of personal and professional context. HP also plans to rely on its Workforce Experience Platform and Wolf Security stack to help IT departments manage devices, security policies and agent governance.

Patel said IT organizations could eventually be responsible for managing millions of agents alongside hundreds of thousands of devices, increasing the need for unified management and security tools.

Potential for PC premiumization

Patel said agentic AI could expand the PC industry’s opportunity beyond hardware sales and transactional margins. He estimated the overall agent-based AI market could reach $6 trillion by 2028, while noting that the PC industry would address only a portion of that market.

He also pointed to potential savings from local AI workloads as a driver of higher-value PCs. Patel said HP has estimated that basic locally run queries could save roughly $650,000 per 1,000 employees, and that savings could rise as local models become more sophisticated.

If customers can save between $1,000 and $2,000 per PC user through agentic capabilities and local models, he said, they may be willing to pay more for devices with those capabilities. Patel said the shift could also create opportunities for new software solutions, recurring revenue and margin expansion across the PC ecosystem.

About HP (NYSE:HPQ)

HP Inc is an American multinational information technology company that designs, manufactures and sells personal computing devices, printers and related supplies and services. Its product portfolio spans consumer and commercial notebooks and desktops, workstations, displays and accessories, as well as an extensive line of printing hardware that includes home, office and production printers. HP also provides consumables such as ink and toner, managed print services, device deployment and lifecycle support, and software for device and print management.

Founded from the original Hewlett‑Packard Company, HP Inc became a separately traded public company in 2015 following a corporate split that created Hewlett Packard Enterprise to focus on enterprise hardware and services.

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