Artificial intelligence has shifted to being the primary engine for market leadership. To compete, enterprises are shifting from general-purpose computing to AI factories, specialized infrastructures designed to manage the entire lifecycle of AI. However, this transition requires robust security without sacrificing performance and efficiency.

We are proud to announce that Palo Alto Networks Prisma^® AIRS™, accelerated on the NVIDIA BlueField data processing unit (DPU), is now part of the NVIDIA Enterprise AI Factory validated design.

The integrated solution embeds zero trust security directly into the AI infrastructure, providing comprehensive protection without impacting AI performance. By deploying Palo Alto Networks Prisma^® AIRS™ Network Intercept directly onto the NVIDIA BlueField and extending to the cloud, Prisma AIRS establishes an essential zero trust governance fabric for the AI factory, enabling enterprises to accelerate innovation while maintaining control.

This critical architectural shift enables optimal AI performance and infrastructure efficiency by offloading security processing to an isolated domain, while leveraging the DPU's hardware acceleration via NVIDIA DOCA to enforce security policies at line speed. The implementation also leverages real-time workload information captured using DOCA Argus, which is then passed to Cortex XSIAM^® where it is used for AI-driven responses using the Cortex XSOAR^® orchestration platform.

Rich Campagna, SVP Product Management, Palo Alto Networks said:

The AI Factory is the new engine for value creation, and securing it is a board-level imperative. The validation of Palo Alto Networks Prisma AIRS accelerated with NVIDIA BlueField within the NVIDIA Enterprise AI Factory enables a new security architecture for the AI era. We are embedding trust directly into the infrastructure, giving leaders the confidence to safeguard their proprietary intelligence and deploy AI bravely.

Kevin Deierling, senior vice president of Networking at NVIDIA said:

AI is transforming every industry and security must evolve to protect AI factories. To be scalable, security must be distributed and embedded within the AI infrastructure. This is achieved with NVIDIA BlueField running Palo Alto Networks Prisma AIRS to deliver robust, runtime security for the AI factory, with optimal AI performance and efficiency.

Deploy AI Bravely with a Future-Proof Foundation

The Future of Secure AI Factories

In addition to deploying Palo Alto Networks Prisma AIRS on NVIDIA BlueField in a distributed model, it’s essential to maintain a centralized Hyperscale Security Firewall (HSF) cluster at the ingress and egress points of the AI factory to enforce a defense-in-depth strategy. Beyond network segmentation, individual workloads can selectively route traffic through hyperscale clusters to detect advanced application-layer threats and prevent lateral movement. These hyperscale firewall clusters scale elastically with demand, delivering session resiliency and the high availability required for critical AI operations.

This architecture fundamentally improves the Total Cost of Ownership (TCO) for AI infrastructure. By isolating security functions on BlueField, enterprises enable 100% of host computing resources to be dedicated to AI applications. This elimination of resource contention allows the AI Factory to maximize token throughput and capital efficiency.

This validated design is the blueprint for immediate efficiency. It provides a seamless path for enterprises to shift from general-purpose clusters to secure AI factory infrastructure without costly overhauls. More importantly, this collaboration establishes an unparalleled roadmap for future-proofing your investment. By securing operations with the high-performance NVIDIA BlueField-3 today, the architecture is inherently ready for the next generation, NVIDIA BlueField-4. This forward compatibility helps AI factories immediately handle gigascale demands, scaling up to 6X the compute power and doubling the bandwidth when BlueField-4 becomes available.

The inclusion of the Palo Alto Networks Prisma AIRS platform in the NVIDIA Enterprise AI Factory Validated Design bolsters enterprise AI security. By establishing the zero trust governance fabric of Prisma AIRS runtime security on NVIDIA BlueField, organizations gain a comprehensive defense. Proprietary and sensitive data is secured throughout the entire stack, and models are protected from adversarial threats, such as prompt injection attacks. With Prisma AIRS, the world's most comprehensive AI security platform, leaders gain the confidence to innovate and deploy AI bravely. This validated design is the essential blueprint for securely accelerating your market leadership without compromising security.

Join our "How to Secure the AI Factory" breakout session at NVIDIA GTC 2026, March 16-19, in San Jose, CA to hear more about this transformative solution and accelerate your AI innovation securely.

The post Palo Alto Networks Announces Support for NVIDIA Enterprise AI Factory appeared first on Palo Alto Networks Blog.

The transformative potential of artificial intelligence (AI) across industries is undeniable. But realizing AI's true value hinges on three cybersecurity imperatives: Understanding the AI-cybersecurity nexus, harnessing AI to supercharge cyber defense, and embedding security into AI tools from the ground up through Secure AI by Design.

Nowhere is this convergence more urgent than in financial services. Sitting at the center of our global economy, financial institutions face a dual mandate: Embrace AI for cybersecurity and cybersecurity for AI.

I was honored to cover these key principals in my testimony before the House Committee on Financial Services, led by Chairman French Hill. The hearing, entitled “From Principles to Policy: Enabling 21st Century AI Innovation in Financial Services” convened witnesses from Palo Alto Networks, Google, NASDAQ, Zillow and Public Citizen. Together, we examined AI use cases in the financial services and housing sectors, including those specific to cybersecurity. We assessed how existing laws and frameworks apply in the age of AI.

The Defense Advantage Is AI-Powered Security Operations

Attacks have become faster, with the time from compromise to data exfiltration now 100 times faster than four years ago. The financial sector bears disproportionate risk, given the value of its data and interconnected systems, while firms contend with evolving regulatory expectations, talent shortages and the persistent tendency to elevate cybersecurity only after an incident.

Generative and agentic AI intensify these pressures by accelerating every phase of the attack chain, from deepfake-driven fraud to tailored spear phishing campaigns. Our researchers at Unit 42^® have found that agentic AI, autonomous systems that can reason and act without human intervention, can compress what was once a multiday ransomware campaign into roughly 25 minutes.

To keep pace, financial institutions must pivot to AI-driven defenses that operate at machine speed.

Security operations centers (SOC) have long been overwhelmed by traditional alerts and fragmented data. Security teams, forced into manual triage across dozens of disparate tools, face an inefficient model that leaves vulnerabilities exposed, burns out analysts and makes it impossible to operate at the speed necessary to outpace modern attacks.

The average enterprise SOC ingests data from 83 security solutions across 29 vendors. In 75% of breaches, logging existed that should have flagged anomalous behavior, but critical signals were buried. With 90% of SOCs still relying on manual processes, adversaries have the clear advantage.

AI-driven SOCs flip this paradigm, acting as a force multiplier to substantially reduce detection and response times. To illustrate the scale of this necessity, consider our own security operations. Palo Alto Networks SOC analyzes over 90 billion events daily. Without AI, this would be an impossible task for human analysts. But by applying AI, we distill that down to a single actionable incident.

Financial institutions migrating to AI-driven SOC platforms are seeing transformative results:

• One customer reduced the Mean Time to Respond (MTTR) from one day to 14 minutes.
• Another prevented 22,831 threats and processed 113,271 threat indicators in less than 5 seconds.
• A large bank saved 180 hours per year by automating security information and event management reporting; 500 hours through automated data collection; 360 hours by automating four Chief Technology Officer playbooks; and 240 hours with automated threat intelligence enrichment.

These improvements are critical to stopping threat actors. But none of this would be possible without AI.

Securing the New AI Attack Surface

As AI adoption grows, it will further expand the attack surface, creating new vectors targeting training data and model environments. AI's rapid growth is outpacing the adoption of security measures designed to protect it. Nearly three-quarters of S&P 500 companies now flag AI as a material risk in their public disclosures, up from just 12% in 2023.

Traditional security tools rely on static rules that miss advanced attacks, like multistep prompt injections or adversarial manipulations. Autonomous AI agents can take unpredictable actions that are difficult to monitor with legacy methods.

Rapid AI adoption has exposed organizations' infrastructure, data, models, applications and agents to unique threats. Unlike traditional cyber exploits that target software vulnerabilities, AI-specific attacks can manipulate the foundation of how an AI system learns and operates.

A Secure AI by Design

Even with an understanding of the risks, many organizations struggle with the lack of clarity on what effective AI security looks like in practice. Recognizing the gap between intent and execution, Palo Alto Networks developed a Secure AI by Design policy roadmap that provides organizations with a comprehensive roadmap that integrates security throughout the entire AI lifecycle.

A proactive stance ensures security is a feature, not an afterthought, crucial for building trust, maintaining compliance and mitigating risks. The approach addresses four imperatives organizations most pressingly face in AI adoption:

1. Secure the use of external AI tools.

2. Secure the underlying AI infrastructure and data.

3. Safely build and deploy AI applications.

4. Monitor and control AI agents.

The Path Forward

For financial institutions, Secure AI by Design must be anchored in enterprise governance. Institutions should maintain risk-tiered AI inventories, enforce strict access controls and implement testing commensurate with risk. Governance structures should enable board oversight and align with established model risk practices.

Policymakers also have a critical role to play in promoting AI-driven security operations, championing voluntary Secure AI by Design frameworks, ensuring policies safeguard innovation, enabling controlled experimentation and strengthening public-private collaboration.

Ultimately, the financial institutions that will thrive will recognize cybersecurity as the foundation that makes innovation possible. By embracing AI-driven defenses and securing AI systems from the ground up, the sector can confidently unlock AI's transformative potential while safeguarding the trust and stability that underpin the global economy.

Read the full testimony to learn more about how cybersecurity can enable AI innovation in financial services.

The post From the Hill: The AI-Cybersecurity Imperative in Financial Services appeared first on Palo Alto Networks Blog.