AI-enabled endpoints are here, expanding what employees can do and what attackers can target. Today’s IT leaders face dual pressures to keep up: act quickly to reap AI-driven productivity gains, while also acting responsibly to avoid expanded attack surfaces and operational risks.
Artificial intelligence embedded in endpoints is fundamentally reshaping performance, risk and workflow. Modernization must be achieved by designing outcomes that are embedded in governance. As discussed at the recent SHI Summit, this shift signals an urgent need for IT and security leaders.
How to accelerate workplace transformation and securely manage endpoints in the AI PC era? Explore our expert insights to help you modernize responsibly.
endpoint era
“AI is now running on devices, and that changes everything,” said Jon McNeill, CEO and co-founder of DVx Ventures, former president of Tesla and former COO of Lyft.
With artificial intelligence, endpoints can now enable smarter workflows, real-time decision-making and lower latency. Benefits of deploying AI on endpoints include faster threat detection, response times, behavioral analysis and anomaly detection, and integration with enterprise security. AI-driven endpoints can also provide:
Enhanced data privacy: AI-enabled data loss prevention (DLP) platforms can analyze data locally using neural processing units (NPUs), tag sensitive information such as personally identifiable information (PII) in real time, and prevent unauthorized data sharing or movement.
Improved security telemetry: Local AI processing allows endpoints to generate and analyze security signals independently of cloud-based solutions, enabling the detection of anomalous behavior in real-time and reducing reliance on external platforms.
Cost optimization: Processing AI workloads locally on endpoints can reduce cloud usage and associated costs because organizations can leverage local hardware such as NPUs and graphics processing units (GPUs) for AI inference, thereby lowering operational expenses.
Better user experience: AI agents on endpoints can automate tasks such as summarizing emails and meetings, adapting to user needs and delivering more personalized and efficient daily workflows across various devices.
As Jon points out, AI is like an exoskeleton—augmenting human capabilities and redefining how work is performed. The performance gap organizations face is not a gap between people, but a gap between how effectively they work with intelligent systems.
Get AI productivity boosts
AI-driven digital employee experience (DEX) and proactive endpoint management can generate measurable compound returns. This means fewer tickets, lower average resolution time, lower help desk costs, and higher employee satisfaction.
Key drivers of this speed include:
This study from TechTarget Enterprise Strategy Group found that the most commonly cited realized or anticipated benefit of deploying AI-enabled endpoints is increased end-user productivity (45%), followed by faster data processing and analysis (41%) and improved search capabilities (40%).
The smartest organizations are adapting platforms, workflows, and endpoints to design and support outcomes at scale.
Modernize while managing risk
With speed comes risk. As AI moves toward the edge, security leaders are increasingly concerned that it introduces visibility and governance gaps that traditional models cannot address.
An emerging challenge is shadow AI, which includes AI-enabled browsers and unmanaged local models that run outside of formal control. Another concern is the limited ability to audit how on-device AI processes data and makes decisions. Additionally, security and support frameworks are still being optimized for legacy systems or pure SaaS environments, while AI software can now run continuously and autonomously.
As one session explained, your endpoints are now in a “warm” state 24/7. Your support model is built for legacy and cloud software – agent AI changes the equation, breaking old assumptions about total cost of ownership, refresh cycles and risk exposure.
“Modernization without governance only creates costly risks,” said Rob Forbes, chief information security officer at Stratascale Field.
Responsible modernization does not mean slowing down innovation, but expanding existing governance forces to cope with these new realities. Don’t think of AI agents and AI-enabled software as tools, but as digital workers. You should apply familiar principles such as identity, compliance, oversight and accountability to the people and machines doing the work.
Rather than inventing entirely new operating models, organizations can adapt what is already working by asking fundamental questions:
- Who (human or agent AI) is performing the task?
- What data is processed locally and under what controls?
- How will decisions be recorded, reviewed, and managed over time?
This approach empowers your organization to act boldly while maintaining trust, compliance, and operational stability.
Turn AI-enabled endpoints into strategic advantage
If designed intentionally, AI-enabled endpoints can proactively reduce risk. The key is integration. Endpoint security, DEX insights, and management platforms must function as a coordinated system rather than exist in silos. Unified visibility enhances employee experience and security posture, helping organizations reduce friction and increase ROI.
From assessing AI-ready endpoints to designing governance-ready operating models, SHI supports modernization that balances innovation and accountability. Our experts can guide you through our managed services and wide range of artificial intelligence, cybersecurity and modern workplace solutions. Learn about our next-generation device labs, which enable organizations to test new devices and benchmark their performance and value before large-scale deployment. Find breakthroughs risk-free in SHI’s AI and Cyber Labs, where we provide a secure, scalable, and cutting-edge environment for testing, building, and deploying AI and cybersecurity solutions.
Organizations that thrive will modernize with purpose, ensuring security, compliance and lifecycle decisions scale with AI.
“The winners in 2026 are not going to make perfect decisions,” said guest speaker Shawn Kanungo, innovation strategist. “They make decisions designed to adapt. Are you willing to disrupt yourself?”
Next step
Stay tuned for more insights from the SHI Summit. To learn more about navigating endpoint AI and how to modernize responsibly, contact SHI’s experts to develop your IT strategy.
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