Use of generative AI and cyber security
While GenAI promises significant advancements, practical concerns persist, including data exposure, reliability issues, and potential data manipulation by attackers. This presentation delves into the nuanced impact of GenAI adoption, contrasting its hyper-acceleration of certain technologies with potential minimal effects on others. Through trend analysis, we evaluate risk levels, implementation complexity, practical solutions, organizational benefits, and success metrics across various use cases.
Generative AI is all around us and in cybersecurity it brings both opportunity and risk. The real change, however, will not come from new “miracle” tools, but from a thoughtful integration of technologies with people and decisions. Let’s not get carried away by the hype—it’s an evolution, not a replacement of people with machines. Every new wave of technology tempts us to believe it will solve all the old problems. Generative AI is powerful, but it is not all‑powerful: attackers and defenders use it alike, and often even the same tools. Attacks are also increasingly targeted at people—our habits, emotions, and mistakes—so it’s not enough to “just add more software.” Today, cybercrime is organized and scales like a regular business, including “crime‑as‑a‑service.” At the same time, AI is extremely accessible, so even a less experienced attacker can quickly assemble a credible phishing message or other traps. The same accessibility, however, is an opportunity for defense—if we use it responsibly and with an understanding of its limits.From excitement to reality: machines and emotions
