AI-enabled endpoints are now here, expanding what employees can do — and what attackers can target. Today’s IT leaders face two pressures to keep pace: move quickly to achieve AI-driven productivity improvements, but also move responsibly to avoid expanding attack surfaces and operational risks.
Artificial intelligence embedded in endpoints is fundamentally reshaping performance, risk, and workflow. Modernization must be approached by designing outcomes that take governance into account. As discussed at the recent SHI Summit, this change marks increasing importance for IT and security leaders.
How can you accelerate workplace transformation and securely manage endpoints in the PC AI era? Explore our expert insights to help you modernize responsibly.
Endpoint era
“AI now runs on devices – and that changes everything,” said key guest 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 implementing AI on endpoints include faster threat detection, response time, behavioral analysis and anomaly detection, and integration with enterprise security. AI-powered endpoints can also provide:
Enhanced data privacy: AI-enabled data loss prevention (DLP) platforms can analyze data locally using neural processing units (NPUs), tag and flag sensitive information such as personally identifiable information (PII) in real-time, and prevent unauthorized sharing or movement of data.
Enhanced security telemetry: Local AI processing enables endpoints to generate and analyze security signals independently of cloud-based solutions, empowering real-time detection of anomalous behavior and reducing dependency on external platforms.
Cost optimization: Processing AI workloads locally on endpoints reduces cloud usage and associated costs, as organizations can leverage local hardware such as NPUs and graphics processing units (GPUs) for AI inference, thereby lowering operational costs.
Better user experience: AI agents on endpoints can automate tasks such as summarizing emails and meetings, adapting to user needs, and providing more personalized and efficient daily workflows across devices.
As Jon says, AI acts like an exoskeleton – amplifying human capabilities and redefining how work is done. The performance gap that organizations face lies not in their human resources, but in how effectively they work with intelligent systems.
Capture AI productivity improvements
AI-driven digital employee experience (DEX) and proactive endpoint management can deliver measurable and multiple benefits. This means fewer tickets, shorter resolution times, lower help desk costs, and higher employee satisfaction.
The main supporting factors for this speed include:
Increased end-user productivity is the most frequently realized or expected benefit from deploying AI-enabled endpoints (45%), followed by faster data processing and analysis (41%), and improved search capabilities (40%), a TechTarget Enterprise Strategy Group research study found.
The smartest organizations align platforms, workflows, and endpoints to design and support outcomes at scale.
Modernize while managing risk
Speed comes with risk. As AI advances, security leaders are increasingly concerned that AI will create 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 operate outside 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 optimized for legacy systems or SaaS-only environments, while AI software now runs continuously and autonomously.
As explained in one of the sessions, your endpoints are now “hot” 24/7. Your support model is built for legacy software and the cloud — agent AI changes the equation, breaking down old 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 does not mean slowing down innovation, but rather expanding existing governance powers to encompass these new realities. Treat AI agents and AI-enabled software less like tools and more like digital employees. You must apply familiar principles — such as identity, compliance, oversight, and accountability — to both the humans and the machines doing the work.
Rather than creating a completely new operating model, organizations can adapt what’s already working by asking fundamental questions:
- Who (human AI or agent) performs the task?
- What data is processed locally, and under what control?
- How are decisions recorded, audited, and managed over time?
This approach allows your organization to move boldly while maintaining trust, compliance, and operational stability.
Turn AI-powered endpoints into a strategic advantage
If 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, not separately. Unified visibility strengthens employee experience and security posture, helping organizations reduce friction and increase ROI.
From evaluating AI-ready endpoints to designing governance-ready operating models, SHI supports modernization that balances innovation and responsibility. Our experts can guide you through our managed services and extensive AI, cybersecurity, and modern workplace solutions. Discover our Next Generation Device Lab, which allows organizations to test new devices and measure their performance and value before large-scale deployment. Find your breakthrough without risk at SHI’s AI & Cyber Labs; here we provide a secure, scalable, and cutting-edge environment for testing, building, and deploying AI and cybersecurity solutions.
Thriving organizations will modernize with intention, ensuring security, compliance, and decision-making throughout the lifecycle are aligned with AI.
“The winners in 2026 will not make perfect decisions,” said lead guest Shawn Kanungo, Innovation Strategist. “They will make decisions designed to adapt. Are you willing to disrupt yourself?”
NEXT STEP
Stay tuned for more SHI Summit insights. To learn more about navigating AI at the endpoint and how to modernize responsibly, contact a SHI expert to shape your IT strategy.
PakarPBN
A Private Blog Network (PBN) is a collection of websites that are controlled by a single individual or organization and used primarily to build backlinks to a “money site” in order to influence its ranking in search engines such as Google. The core idea behind a PBN is based on the importance of backlinks in Google’s ranking algorithm. Since Google views backlinks as signals of authority and trust, some website owners attempt to artificially create these signals through a controlled network of sites.
In a typical PBN setup, the owner acquires expired or aged domains that already have existing authority, backlinks, and history. These domains are rebuilt with new content and hosted separately, often using different IP addresses, hosting providers, themes, and ownership details to make them appear unrelated. Within the content published on these sites, links are strategically placed that point to the main website the owner wants to rank higher. By doing this, the owner attempts to pass link equity (also known as “link juice”) from the PBN sites to the target website.
The purpose of a PBN is to give the impression that the target website is naturally earning links from multiple independent sources. If done effectively, this can temporarily improve keyword rankings, increase organic visibility, and drive more traffic from search results.