Economic Impact of Securing AI
About This Session
As artificial intelligence (AI) becomes an increasingly integral part of global infrastructure, commerce, defense, and daily life, the imperative to secure these systems is no longer a technical concern alone—it is an economic necessity. This keynote explores the intersection of cybersecurity and AI through the lens of economic strategy, risk modeling, and incentive alignment, presenting a holistic framework for understanding and addressing the financial realities of securing AI.
Securing AI systems involves unique challenges: data poisoning, model inversion, adversarial attacks, and algorithmic manipulation. Unlike traditional software, AI models can be subverted not just through code exploits, but through the very data and feedback loops that drive their behavior. The existing investments we have for traditional Cyber Security do protect models - they provide only indirect protection at best. This misunderstanding of the existing controls can create a misalignment of not only spending but incentives among developers, users, regulators, and attackers, which traditional security economics already struggles to address.
In this talk, I will examine how context is key and cash is king. We will examine the existing controls in use in organizations and how those controls do not protect AI models from attacks. We will discuss financial materiality and material risk to help refine how to think about the incentives for companies to invest in AI security when the threats are diffuse and the benefits of prevention may be difficult to quantify. I will walk through how to construct an economic impact analysis for securing AI including how to evaluate various control options on total costs as well as sufficiency of control. I will also share recent trends in cyber security insurance and the lack of coverage benefits for AI models.
Drawing from my real-world experience as a former finance leader in addition to my years running security, this keynote offers a strategic view of AI security as an investment problem, a game-theoretic challenge, and a policy frontier which we all need to navigate to protect the promise of AI and avoid the perils that could occur. Attendees will leave with a deeper understanding of how economic impact and total cost models can inform the design of secure AI systems and influence corporate decision-making
By treating security not as just a cost but as a critical enabler of AI growth, we can move toward a future where AI systems are not only powerful, but are secure, resilient, and trustworthy.
Securing AI systems involves unique challenges: data poisoning, model inversion, adversarial attacks, and algorithmic manipulation. Unlike traditional software, AI models can be subverted not just through code exploits, but through the very data and feedback loops that drive their behavior. The existing investments we have for traditional Cyber Security do protect models - they provide only indirect protection at best. This misunderstanding of the existing controls can create a misalignment of not only spending but incentives among developers, users, regulators, and attackers, which traditional security economics already struggles to address.
In this talk, I will examine how context is key and cash is king. We will examine the existing controls in use in organizations and how those controls do not protect AI models from attacks. We will discuss financial materiality and material risk to help refine how to think about the incentives for companies to invest in AI security when the threats are diffuse and the benefits of prevention may be difficult to quantify. I will walk through how to construct an economic impact analysis for securing AI including how to evaluate various control options on total costs as well as sufficiency of control. I will also share recent trends in cyber security insurance and the lack of coverage benefits for AI models.
Drawing from my real-world experience as a former finance leader in addition to my years running security, this keynote offers a strategic view of AI security as an investment problem, a game-theoretic challenge, and a policy frontier which we all need to navigate to protect the promise of AI and avoid the perils that could occur. Attendees will leave with a deeper understanding of how economic impact and total cost models can inform the design of secure AI systems and influence corporate decision-making
By treating security not as just a cost but as a critical enabler of AI growth, we can move toward a future where AI systems are not only powerful, but are secure, resilient, and trustworthy.
Speaker
Malcolm Harkins
Chief Security and Trust Officer - HiddenLayer
Malcolm Harkins is Chief Security and Trust Officer at HiddenLayer. Harkins has more than two decades of experience in information security leadership roles at top technology companies, including Intel, Cylance, and others. He’s written multiple books on risk management, information security, and IT and earned awards from the RSA Conference, ISC2, Computerworld, and the Security Advisor Alliance. Harkins has testified before the Federal Trade Commission and U.S. Senate Committee on Commerce, Science, and Transportation. Harkins is a Fellow with the Institute for Critical Infrastructure Technology, a non-partisan think tank providing cybersecurity expertise to the House of Representatives, Senate, and various federal agencies.