By Vinita Vijay (’24SPS, Technology Management)
“The question is not whether AI will reshape cybersecurity—it already has. The question is, how can we lead this transformation to a new age in cybersecurity responsibly and effectively?”
This was the key topic at a panel on cybersecurity in the age of AI, hosted by Columbia’s M.S. in Technology Management (TMGT) program. Through the exploration of relevant frameworks, strategies, and tools, TMGT students develop the ability to consider technology challenges posed by advancements in AI through courses including Cybersecurity, Digital Transformation, and Essentials for Technology Management and Leadership. This event brought together leaders from the tech industry to discuss today’s most pressing issues regarding information and network security. As cyberattacks become more sophisticated and AI’s capabilities continue to accelerate, the traditional paradigms of defense, risk governance, and leadership are being redefined.
Panelists included Shahryar Shaghaghi, director of the TMGT program; Lauren Goodwin, founder and CEO of Mission Ops; Daniel Wallance, senior expert in cybersecurity and tech risk at McKinsey; and Shima Mousavi, senior manager of cybersecurity strategy at Deloitte.
Here are key insights from the panel.
Reframing the Battlefield: AI on Both Sides of the Line
AI has become a game changer in cybersecurity. On the defensive front, machine learning enables early threat detection and real-time automation, and improves anomaly spotting. Yet malicious actors now use the same tools, leveraging generative AI to create polymorphic malware, simulate legitimate communications, and scale attacks with alarming speed.
Panelists shared examples of both sides at work. For example, predictive maintenance systems in the energy sector are reducing downtime by more than 30 percent, but ransomware groups are using autonomous decision-making to bypass traditional defenses. As the line between offense and defense blurs, cybersecurity is becoming a battle of intelligent systems.
Rethinking Risk: Governance for an AI-Driven Future
With the adoption of AI technologies moving faster than regulation, risk governance is under intense pressure to keep up. Panelists pointed to frameworks such as the NIST’s AI Risk Management Framework and Google’s Secure AI Framework (SAIF) as emerging standards for the responsible implementation of AI.
Risk is no longer confined to data loss or perimeter breaches. It must now be evaluated across the entire AI pipeline, from data quality and model robustness to operational monitoring and third-party integrations. The rise of “shadow AI”—unregulated use of AI tools by employees—and open-source tools within enterprises makes governance even more complex.
From Buzz to Business Value: Leadership in a New Era
While many organizations are experimenting with AI, the panel emphasized that technology should follow strategy, not the other way around. Successful integration depends on clearly defined problems, practical use cases, and small-scale pilot programs.
This is particularly crucial in domains such as secure software development, vendor risk management, and incident response—areas where AI can accelerate tasks but also amplify vulnerabilities. Strong leadership is essential for balancing innovation with accountability.
The Human Edge in an Intelligent World
Contrary to fears about job loss, panelists agreed that AI will not replace cybersecurity professionals; rather, professionals who embrace AI will replace those who don’t. In fact, as automation takes on routine tasks, demand is growing for cyber leaders who can combine technical fluency with strategic thinking.
Graduates entering the field will need to understand AI models, explain risks to business stakeholders, and lead with ethical clarity. The human touch—curiosity, judgment, and empathy—remains irreplaceable.
Looking Ahead: Intelligence with Intention
In the age of AI, the stakes have never been higher. Will organizations build reactive systems that patch vulnerabilities, or proactive frameworks that anticipate and neutralize threats? The answer will depend on how intentionally AI is designed, deployed, and governed. Trust, resilience, and human-centered leadership must be at the core of the next chapter in the evolution of cybersecurity in the age of AI.
About the Program
Columbia University’s Master of Science in Technology Management is a hands-on technology leadership development program designed to train professionals for equal fluency in tech fundamentals, business operations, and ethical leadership.
The program is available for part-time or full-time enrollment. Learn more about the program here.
