AI • IOT • NETWORK EDGE

AI has proven extremely valuable across industries. In manufacturing, it enhances predictive maintenance, worker safety, and operations. In retail, it provides deeper customer insights and aids in loss prevention. And in healthcare, AI helps medical professionals diagnose and treat patients more efficiently.

These examples are just a subset of how AI provides new business value to organizations worldwide. But with the introduction of new technologies also come new vulnerabilities that threaten an organization’s ability to move forward.

AI is useful only if its underlying algorithms can be trusted—making it essential for organizations to adopt technologies and partnerships that prioritize protecting their networks and systems. As AI collects intellectual property, business-critical, or regulated data to perform actions and make insights, that data must be always protected.

That’s why Intel products and technologies ensure end-to-end protection, providing security practically anywhere AI occurs. This is extremely important as the next generation of AI emerges with new demands, new capabilities, and new threats.

Next-Generation AI Sparks Demand for Deeper Protection

For example, the evolution of AI workloads demands significant investments in computational and network infrastructure. This is because large language models traditionally use cloud-based processing. To enable cost-efficiency, AI workloads are shifting to client-side computing—leading to emergence of AI PCs. Long term, the AI PC promises to unlock new use cases and business value. But the hybrid nature of AI workloads, spanning from the cloud to on-premises data centers and the network edge, introduces new attack surfaces.

To address these concerns, Intel launched its AI PC earlier this year with Intel^® Core^™ Ultra processors to optimize AI software efficiency. More important, it includes Intel^® Threat Detection Technology (Intel^® TDT) to provide endpoint protection and defend against AI-related threats. Leveraging Intel CPU telemetry and Intel AI models running on an integrated Intel GPU, Intel TDT scans for threats and ransom attacks. It also offers a layered approach with deeper protection through partner integrations like Microsoft Defender, optimizing client-side AI hardware. This provides a cost-effective alternative to public cloud AI.

#AI is useful only if its underlying algorithms can be trusted—making it essential for organizations to adopt #technologies and partnerships that prioritize protecting their networks and systems. @Intel via @insightdottech

AI security must also be applied throughout the entire lifecycle, from model development and deployment to algorithms, data, and devices. Intel^® Xeon^® Scalable processors support widely deployed AI inference workloads with secure features like Intel^® Software Guard Extensions (Intel^® SGX) and Intel^® Trust Domain Extensions (Intel^® TDX), enabling data and virtual machine isolation through secure enclaves and trusted domains.

For added protection, Intel^® Tiber Trust Services offer real-time attestation, enabling secure collaboration and trust verification for hybrid and multi-cloud deployments. These services align with NIST Zero Trust principles, supporting confidentiality and uptime with high security standards.

But Intel’s AI security efforts don’t stop just at its technology. The company has fostered a secure AI ecosystem with partnerships and collaborations across the industry.

Strategic Partnerships Safely Unlock AI’s Potential

As AI models increasingly rely on data for learning and inferencing, there is a heightened risk from data manipulation and Distributed Denial of Service (DDoS) attacks to IP theft. Intel partnered with Dell and F5 Networks to tackle this type of AI model vulnerability. F5 Networks and Dell’s PowerEdge R760 with the Intel^® Infrastructure Processing Unit (Intel^® IPU) Adapter E2100 offer a distinct approach, using dedicated resources for security functions like encryption and DDoS mitigation. This setup separates security tasks from AI model processing, reducing latency, and improving model protection—ultimately enabling companies to focus on maximizing AI’s business value securely.

Another example of Intel’s partnerships is in smart manufacturing environments, where growing cybersecurity threats are emerging as OT networks become increasingly connected to IT systems. NEXCOM leverages Intel technology to secure OT networks with its ISA 140 industrial security appliance. Powered by Intel Atom^® processors, the ISA 140 is compact in size and comes with multi-ports and remote management features to create a micro-segmented OT network that isolates and protects valuable assets even in the harshest factory conditions.

Beyond manufacturing, there are other industries where the protection of confidential information is imperative, such as healthcare and finance. This is where Intel’s confidential computing technologies like Intel SGX and TDX can take center stage. Typically, organizations have tried to protect information by anonymizing the data. But full anonymization is difficult to achieve and even if data is encrypted at rest or in transit, it remains decrypted and unprotected during data processing. Confidential computing protects data at all stages, offering a Zero Trust architecture to data handling. The Fortanix Confidential Computing Manager combines Intel SGX, Intel TDX, and 4th Gen Intel^® Xeon^® Scalable processors to protect data in a trusted execution environment.

Zscaler also leverages Intel technology to offer a Zero Trust architecture to its users. As cyber threats continue to evolve, Zero Trust ensures continuous validation of users, systems, and devices—ensuring no access is granted without rigorous decks. By partnering with Intel, Zscaler can leverage Intel Xeon Scalable processors for secure edge-to-cloud protection. This collaboration ensures data and applications are always protected, regardless of location or device, reinforcing the importance of partnerships in achieving robust cybersecurity across complex environments.

Protecting Against Future Advancements

As AI continues to transform the enterprise landscape, its value lies not only in its innovations but in the intellectual property and regulated data their models contain. Protecting these assets requires a multifaceted approach that addresses data at rest, in motion, and in use, ensuring continuous refinement and accuracy over time.

Equally critical is the need for robust defense mechanisms to counter AI-enriched attacks, which can exploit vulnerabilities across workload runtimes. This dual approach—leveraging AI to strengthen security while securing AI itself—ensures comprehensive, end-to-end protection.

By prioritizing these safeguards, organizations can confidently harness the power of AI, unlocking transformative advancements while minimizing risk. In doing so, they position themselves not just to survive but to thrive in an increasingly AI-driven future.

This article was edited by Georganne Benesch, Editorial Director for insight.tech.