Building on previous IDC-commissioned AI PC research, AMD has debuted a new report displaying how enterprises are moving from evaluating AI PCs to active deployment.
Nearly all enterprises are at least in the planning stage of AI PC adoption
The report captures the growing momentum of AI PC adoption among organizations and what it means as they scale AI across their workforces.
The key findings from the report include:
- 60% percent of enterprises are actively deploying and piloting AI PCs.
- 81% of enterprises are now engaged across planning, piloting, and deploying AI PCs.
- 67% of organizations are expanding AI across their business, and 61% are working to integrate AI into their workflows.
- 70% percent expect agentic AI to impact their work within two years.
Expansion of AI adoption in 2026 brings tooling into more departments and functions
According to the report, respondents indicate that AI is being operationalized across departments and embedded into daily workflows.
A majority of respondents (67 percent) report expanding AI initiatives across departments, with 61 percent saying they are directly embedding AI into workflows.
Furthermore, 36 percent of respondents rely on third-party AI services for their organizations.
“The expansion of AI initiatives across departments creates practical demands around performance, security, privacy, and responsiveness that cannot always be met solely through centralized infrastructure,” the report says.
“As organizations embed AI into everyday processes, the endpoint becomes a more strategic component of the overall AI architecture.”
Endpoint strategy is evolving in parallel with AI as it scales across enterprises, as well. PCs are also increasingly seen as AI-capable devices that enable distributed processing, local inference, and tighter integration with evolving AI workflows, the report states.
How agentic AI is accelerating AI PCs’ role in the enterprise
There are near-term impacts for agentic AI, with 31 percent of respondents expecting it to affect end-user workflows within 12 months. Meanwhile, 39 percent believe it will be impactful within one to two years.
“This timeline suggests that enterprises do not view agentic AI as a distant concept,” the report states. “They expect it to influence employee workflows, task automation, knowledge management, resource management, and decision support in the short to medium term.”
Organizations must consider critical capabilities for enabling agentic AI on PCs to reinforce two roles: As the primary device through which employees interact with enterprise systems, the AI PC becomes the control center for cloud-based agents, as well as a location for secure on-device processing.
Among the capabilities organizations should consider for enabling agentic AI on PCs to reinforce that dual function include:
- High-performance NPUs: 59 percent cite new processing units (NPUs) as critical for providing the always-on, contextual awareness necessary for today’s persistent AI workloads and tomorrow’s agentic AI workflows.
- Continuous learning from user behavior: 48 percent
- Advanced connectivity (5G, Wi-Fi): 38 percent
- Local data recall integration: 35 percent
- Seamless interoperability with other AI-enabled devices: 34 percent
- Secure sandboxed agent environments: 31 percent
- Efficient power management: 30 percent
- Low-latency cloud coordination: 21 percent
“As AI systems evolve from assistive tools to autonomous agents, the AI PC will likely have an important role to play,” the report details. “The convergence of expanding AI initiatives, employee productivity gains, clear investment drivers, and accelerating expectation around agentic AI paints a consistent picture. Enterprises are embedding AI deeper into operations, and the AI PC is emerging as a foundational layer of that transformation.”
AI PC challenges and opportunities
The report identified two primary challenges as AI PCs move to enterprise scale.
These challenges include:
- Operational integration: Organizations will need to redesign processes, train employees, and update governance models to ensure AI enhances productivity rather than creating friction because embedding AI directly into workflows requires more than deploying new hardware. Obtaining the benefits of AI-enabled endpoints can remain uneven across departments without careful management.
- Governance and security complexity: AI raises questions surrounding data management, accountability, and policy enforcement. Organizations should ensure secure local execution while maintaining compliance and visibility, which will demand tighter coordination between IT, security, and business teams.
Enterprises view AI PCs as opportunities to increase productivity and flexibility
While these challenges present themselves as AI PCs move to enterprise scale, there are a pair of opportunities for organizations to consider.
The first is workforce acceleration. AI PCs can automate repetitive tasks, freeing employees to spend more time on higher-level strategic decision-making and more engaging work.
Second is architectural flexibility. Investing in AI PCs now allows companies to prepare their workforce for a future state in which the AI-enabled operating systems and applications are fully developed, while also preparing for an agentic AI future.
“AI is reshaping how businesses operate, and the PC is poised to play a central role in that transformation,” according to the report. “While most AI workloads today run in the cloud, for AI to truly scale, more of it will need to run on device. More importantly, organizations that invest in AI PCs today are positioning themselves for the agentic future ahead.”