A new generation of AI-enabled PCs is entering the workplace, bringing with it the promise of personalized automation, faster decision-making, and stronger security. But for IT buyers under pressure to prove value, one of the most important questions is where these devices will deliver measurable return on investment (ROI).
From knowledge worker productivity and secure remote operations to edge-based analytics in the field, AI PCs are beginning to redefine what’s possible across roles, business departments, and industries. We asked enterprise IT leaders, practitioners, and influencers from Foundry’s CIO Experts Network to identify the use cases for AI-enabled PCs that promise the highest returns. Their responses reveal a clear shift in how modern devices are viewed: not as commodity endpoints, but as intelligent agents of productivity and protection.
Productivity and workflow automation: A measurable efficiency boost
The strongest business case for AI PCs may lie in how well they streamline knowledge work: automating tasks, summarizing content, and managing information flows in real time.
“The use cases with the highest return on investment for AI PCs in the workplace will be automation, productivity, and decision intelligence,” says Vivek Singh, senior vice president of IT and strategic planning at PALNAR. “Real-time document summarization, AI-powered meeting insights, and automated email and workflow management to cut down on manual tasks are important areas.”
That time savings adds up fast. As Singh notes, “Employees will be able to process complex datasets locally more quickly and privately thanks to embedded genAI copilots,” creating a ripple effect that accelerates analytics and decision-making across departments.
Joan Goodchild, founder of CyberSavvy Media, echoes this view. “The most compelling ROI from AI PCs will come from use cases that pair performance gains with cost savings,” she says. “On-device AI can accelerate everyday productivity tasks like summarizing documents, drafting emails, or translating content without sending sensitive data to the cloud.”
That local processing power reduces latency while preserving privacy, delivering business value in both time and risk mitigation. “For knowledge workers,” Goodchild adds, “generative AI copilots built into productivity suites will streamline workflows and reduce time spent on repetitive tasks.”
Kumar Srivastava, CTO at Turing Labs, sees even more potential in personalized AI experiences. “Custom AI fine-tuned and personalized to each PC and its user is the future,” he says. “AI PCs should enable context engineering personalized to each user to create a tiered LLM invocation to provide high-quality, context AI-powered summarization, data processing, and automation.”
Real-time decisioning and data analysis: From bottleneck to advantage
While automation reduces friction in day-to-day work, AI PCs are also enabling faster, more informed decisions at scale. By bringing inference and analysis directly to the device, AI PCs enable people to make sense of complex data without relying on cloud processing.
“As AI PCs start to enter the workplace, the leading use cases are knowledge worker augmentation and real-time data analysis,” says Arsalan Khan (@ArsalanAKhan), a technology advisor and speaker. But that vision hinges on infrastructure readiness. “To unlock this, data must be secure, searchable, and observable — not just within server-based applications, but across AI-powered endpoints, including AI PCs,” Khan explains. “When done right, leaders and teams will be able to extract insights instantly from complex reports, dashboards, and code.”
In data-intensive sectors like healthcare and scientific research, local AI compute can mean the difference between weeks and hours. Peter Nichol, data and analytics leader at Nestlé Health Science, gives an example from the genomics field:
“Each genome contains highly sensitive genetic markers that, if exposed, could compromise a patient’s entire biological identity,” he says. “Analyzing these sequences often means running Python or R-based models to detect mutations, a process that requires handling 100 to 200 gigabytes of data per patient.”
That volume of data is both costly and risky to move to the cloud. “By leveraging AI-enabled PCs with GPU acceleration,” Nichol adds, “organizations can give their data scientists HPC-like performance directly in the lab — protecting sensitive information, reducing compliance risk, and accelerating time-to-insight.”
Even beyond labs and boardrooms, real-time data analysis at the edge is transforming field-based roles. Whether it’s a site supervisor reviewing drone footage, a utility inspector analyzing infrastructure video, or an agricultural scientist monitoring soil health with handheld imagery, AI PCs bring high-performance computing[LG1] (HPC)-level analysis directly to the source, Nichol says. The benefits: reduced dependence on connectivity, faster insights, and stronger data sovereignty.
Built-in security: Faster threat detection, lower compliance risk
The third pillar of AI PC ROI lies in security. As remote and hybrid work environments increase the complexity of threat landscapes, businesses are turning to hardware-based AI to preemptively detect issues and enforce protection without adding operational friction.
“From a cybersecurity business perspective, the biggest advantages of AI PCs are saving time and reducing risk,” says Scott Schober (@ScottBVS), president and CEO of Berkeley Varitronics Systems. “The AI built into the device handles tasks such as meeting notes, report drafts, and data analysis. This allows teams to focus on the big-picture challenges.”
But it’s the security layer that delivers long-term ROI, he says. “The AI also provides a significant security upgrade,” Schober explains. “It can catch phishing or unusual behavior instantly, protecting the business from problems before they begin. The most valuable AI features are those that make the team more productive and more secure.”
Goodchild adds that security is one of the most cost-effective use cases for AI at the device level. “AI PCs can run continuous, on-device threat detection and biometric verification,” she says. “This strengthens protection without adding friction.” And because the processing happens locally, it reduces reliance on cloud-based security analytics — cutting costs while improving data privacy.
Investing in the intelligent edge
AI PCs are more than just faster laptops — they’re intelligent edge devices designed to empower every employee with personalized performance, secure autonomy, and real-time decision support. For IT buyers seeking quantifiable returns, the clearest value lies in automating repetitive tasks, accelerating data analysis, and reducing risk.
As the capabilities of AI PCs mature, the business case for upgrading endpoint infrastructure is shifting from “if” to “when.” And for organizations that move early, the ROI will extend beyond cost savings into a smarter, faster, and more secure workforce.
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