AiThority Interview with Anand Pashupathy, Vice President & General Manager, Security Software & Services Division, Intel

Anand Pashupathy, Vice President & General Manager, Security Software & Services Division, Intel chats about the many ways in which AI is enabling better security workflows and protocols in this AiThority Interview:

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Tell us about yourself and more about your journey at Intel through the years…as a VP of Security Software, what does your role and a typical day at work look like?

I am Intel’s Vice President and General Manager of the Security Software & Services Division in the Software and Advanced Technology Group. I lead a team of senior executives to deliver security software technologies and services that activate and differentiate silicon security features while cultivating a high standard of security and operational and cultural excellence.

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I am also responsible for Intel’s confidential compute vision, strategy, and execution. Previously, I held many engineering and General Manager leadership roles across Intel – I’ve been here since the 1990s.

Personally, I am a strong advocate for women and underrepresented people in technology. I serve as the Executive Sponsor for an internal employee resource group focusing on diversity and inclusion.

We’d love to hear about some of Intel’s latest enhancements around security as well as how the team is using AI to drive better efforts here?

Intel is investing in the development of Confidential AI, along with industry partners, to help businesses prevent the exposure of sensitive information. As more and more companies embrace and begin to use AI, they’ve also become more aware of how much of this processing occurs in the cloud – a concern for businesses with stringent data protection policies. While this is often a roadblock for AI adoption, Intel is pioneering the convergence of AI and confidential computing to help businesses address these challenges.

Intel’s latest enhancements around Confidential AI utilize confidential computing principles and technologies to help protect data used to train LLMs, the output generated by these models and the proprietary models themselves while in use. Through vigorous isolation, encryption and attestation, confidential AI prevents malicious actors from accessing and exposing data, both inside and outside the chain of execution.

For businesses to trust in AI tools, technology must exist to protect these tools from exposure inputs, trained data, generative models and proprietary algorithms. Confidential AI helps make that happen.

Based on global security challenges and trends: how are you seeing AI influence the way tech and IT teams boost security workflows for their organizations? What should IT teams be wary of when deploying AI for sensitive security protocols?

AI is top of mind for many organizations right now – but the ability to secure AI models and algorithms is still a top concern for IT teams (86% of companies are concerned the AI model’s security won’t hold up to malicious attacks). IT teams should be cautious as AI adoption requires that security products integrate both data science models and frameworks, as well as the connected applications that operate in the real world.

Confidential AI can help tech and IT teams boost security workflows by increasing the security and privacy of their AI deployments. It can be used to help protect sensitive or regulated data from a security breach and strengthen their compliance posture under regulations like HIPAA, GDPR or the new EU AI Act.

What can organizations do to secure and store their data more effectively?

Throughout their life cycles, leaving AI models and their data training sets unmanaged, unmonitored, and unprotected can put an organization at risk for data theft, fines and more. A broad range of malicious attacks are now being directed at AI models, including training-data poisoning, AI model theft, adversarial sampling, and more. In the age of “AI Everywhere,” data is the most valuable asset. You should be able to confidently trust the systems that run it, put zero trust within reach, and get public cloud flexibility with private cloud security.

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By adopting Confidential AI capabilities, organizations can secure their entire AI pipeline, from data preparation and consolidation to training, inference and results delivery.  Each of these stages can be vulnerable to attack, theft or manipulation, and confidential AI can help bolster protections across the spectrum.

If you had to share a few endnotes and thoughts on the future of security and AI: what would you highlight?

Over the next few years, Confidential AI will be most important to industries that rely on storing and processing sensitive information, such as healthcare, government, finance, and retail. As governments around the world are issuing new regulations to help keep AI deployments secure and trustworthy, including the European Union’s AI Act, Intel is collaborating with technology leaders across the broader industry to make using AI more secure while helping businesses address critical privacy and regulatory concerns at scale.

Here at Intel, we are committed to advancing AI technology responsibly and the industry’s collective efforts, regulations, standards and the broader use of AI will ideally contribute to confidential AI becoming a default feature for every AI workload in the future.

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