AIS Logo
← Back to Library
Promises and Perils of Generative AI in Cybersecurity
MIS Quarterly Executive (2025) AI Processed

Promises and Perils of Generative AI in Cybersecurity

Pratim Datta, Tom Acton
This paper presents a case study of a fictional insurance company, based on real-life events, to illustrate how generative artificial intelligence (GenAI) can be used for both offensive and defensive cybersecurity purposes. It explores the dual nature of GenAI as a tool for both attackers and defenders, presenting a significant dilemma for IT executives. The study provides actionable recommendations for developing a comprehensive cybersecurity strategy in the age of GenAI.

Problem With the rapid adoption of Generative AI by both cybersecurity defenders and malicious actors, IT leaders face a critical challenge. GenAI significantly enhances the capabilities of attackers to create sophisticated, large-scale, and automated cyberattacks, while also offering powerful new tools for defense. This creates a high-stakes 'AI arms race,' forcing organizations to decide how to strategically embrace GenAI for defense without being left vulnerable to adversaries armed with the same technology.

Outcome - GenAI is a double-edged sword, capable of both triggering and defending against sophisticated cyberattacks, requiring a proactive, not reactive, security posture.
- Organizations must integrate a 'Defense in Depth' (DiD) strategy that extends beyond technology to include processes, a security-first culture, and continuous employee education.
- Robust data governance is crucial to manage and protect data, the primary target of attacks, by classifying its value and implementing security controls accordingly.
- A culture of continuous improvement is essential, involving regular simulations of real-world attacks (red-team/blue-team exercises) and maintaining a zero-trust mindset.
- Companies must fortify defenses against AI-powered social engineering by combining advanced technical filtering with employee training focused on skepticism and verification.
- Businesses should embrace proactive, AI-driven defense mechanisms like AI-powered threat hunting and adaptive honeypots to anticipate and neutralize threats before they escalate.
Generative AI, Cybersecurity, Black-hat AI, White-hat AI, Threat Hunting, Social Engineering, Defense in Depth