How smart leaders modernize: Insights to transform work with AI-enabled endpoints

AI-enabled endpoints are here, expanding what employees can do — and what attackers can target. Today’s IT leaders face the dual pressure to keep up: move fast to capture AI-driven productivity gains, yet also move responsibly to avoid expanding attack surfaces and operational risk.

Artificial intelligence embedded at the endpoint is fundamentally reshaping performance, risk, and workflows. Modernization must be approached by designing outcomes with governance baked in. As discussed at the recent SHI Summit, this shift marks a growing imperative for IT and security leaders.

How can you accelerate workplace transformation and securely manage endpoints in the AI PC era? Explore our expert insights to help you modernize responsibly.

The era of the endpoint

“AI is now running on the device — and that changes everything,” said guest keynote Jon McNeill, CEO and Co-Founder of DVx Ventures, former President of Tesla, and former COO of Lyft.

With AI, endpoints now enable smarter workflows, real-time decision‑making, and lower latency. The benefits of deploying AI at the endpoint include faster threat detection, response times, behavioral analysis and anomaly detection, and integration with enterprise security. AI-powered endpoints can also deliver:

Enhanced data privacy: AI-enabled data loss prevention (DLP) platforms can analyze data locally using neural processing units (NPUs), flagging and tagging sensitive information such as personally identifiable information (PII) in real time, and preventing unauthorized sharing or movement of data.

Improved security telemetry: Local AI processing allows endpoints to generate and analyze security signals independently of cloud-based solutions, empowering real-time detection of anomalous behavior and reducing reliance on external platforms. 

Cost optimization: Processing AI workloads locally on endpoints reduces cloud usage and related costs, as organizations can leverage local hardware like NPUs and graphics processing units (GPUs) for AI inference, lowering operational expenses.

Better user experience: AI agents on endpoints can automate tasks such as summarizing emails and meetings, adapting to user needs, and providing a more personalized and efficient daily workflow across various devices.

As Jon noted, AI acts like an exoskeleton — amplifying human capability and redefining how work is performed. The performance gap organizations face isn’t between people, but between how effectively they work with intelligent systems.

Capturing AI productivity gains

AI‑driven digital employee experience (DEX) and proactive endpoint management can generate measurable, compounding returns. This translates to fewer tickets, shorter mean time to resolution, lower helpdesk costs, and higher employee satisfaction.

Key enablers of that speed include:

• Unified endpoint management that supports diverse devices and work styles.
• Zero‑touch provisioning and automated remediation that reduce friction for both users and IT.
• Intelligent refresh strategies, driven by real usage and performance data rather than fixed replacement cycles — especially critical as memory costs and supply constraints fluctuate.

Improved end-user productivity is the most commonly cited realized or expected benefit of deploying AI-enabled endpoints (45%), followed by faster data processing and analysis (41%), and improved search capabilities (40%), found this TechTarget Enterprise Strategy Group research study.

The smartest organizations are aligning platforms, workflows, and endpoints to design and support outcomes at scale.

Modernizing while managing risk

Speed comes with risk. As AI moves to the edge, security leaders are increasingly concerned it introduces visibility and governance gaps that traditional models weren’t built to address.

An emerging challenge is shadow AI, which includes AI-enabled browsers and unmanaged local models operating outside of formal controls. Another concern is the limited ability to audit how on-device AI processes data and makes decisions. Additionally, security and support frameworks are still optimized for legacy systems or SaaS-only environments, while AI software now runs continuously and autonomously.

As one session explained, your endpoint is now “warm” 24/7. Your support model was built for legacy and cloud software — agentic AI changes that equation, breaking older assumptions about total cost of ownership, refresh cycles, and risk exposure.

“Modernization without governance is just buying expensive risk,” said Rob Forbes, Stratascale Field CISO.

Responsible modernization doesn’t mean slowing down innovation, but instead extending existing governance muscles to cover these new realities. Treat AI agents and AI‑enabled software less like tools and more like digital employees. You should apply familiar principles — such as identity, compliance, oversight, and accountability — to both humans and machines doing the work.

Instead of inventing entirely new operating models, organizations can adapt what already works by asking foundational questions:

• Who (human or agentic AI) is performing the task?
• What data is processed locally, and under what controls?
• How are decisions logged, audited, and governed over time?

This approach allows your organization to move boldly while maintaining trust, compliance, and operational stability.

Turning AI‑enabled endpoints into a strategic advantage

When designed intentionally, AI‑enabled endpoints can actively reduce risk. The key is integration. Endpoint security, DEX insights, and management platforms must function as a coordinated system, rather than in silos. Unified visibility strengthens both employee experience and security posture, helping organizations reduce friction and improve ROI.

From evaluating AI‑ready endpoints to designing governance‑ready operating models, SHI supports modernization that balances innovation with responsibility. Our experts can guide you through our managed services and extensive AI, cybersecurity, and modern workplace solutions. Discover our Next-Gen Device Lab, enabling organizations to test new devices and benchmark their performance and value before large-scale deployment. Find your breakthrough without the risk in SHI’s AI & Cyber Labs; here we provide a safe, scalable, and cutting-edge environment for testing, building, and deploying AI and cybersecurity solutions.

The organizations that thrive will modernize with intent, ensuring security, compliance, and lifecycle decisions scale alongside AI.

“The winners in 2026 won’t make perfect decisions,” said guest keynote Shawn Kanungo, Innovation Strategist. “They will make decisions designed to adapt. Are you willing to disrupt yourself?”

NEXT STEPS

Stay tuned for more SHI Summit insights. To learn more about navigating AI at the endpoint and how to modernize responsibly, connect with SHI’s experts to shape your IT strategy.