AI for cybersecurity AI is fundamentally transforming security operations – accelerating detection, triage and response while automating labour-intensive tasks such as log analysis and compliance reporting. AI’s ability to process vast datasets and identify patterns at speed positions it as a competitive advantage for organizations seeking to stay ahead of increasingly sophisticated cyberthreats. The survey data reveals that 77% of organizations have adopted AI for cybersecurity, primarily to enhance phishing detection (52%), intrusion and anomaly response (46%) and user-behaviour analytics (40%). How organizations are implementing AI for cybersecurity FIGURE 12 Has your organization implemented any AI-enabled tools to fulﬁl its cybersecurity objectives? (select up to three) Responses (%)77% 23%Yes, for phishing and email threat detection 20% 40%52% Yes, to detect and respond to intrusions or anomalies 46% Yes, for user-behaviour analytics and insider threat detection 40% Yes, for threat intelligence and risk prioritization 39% Yes, for other purposes 8%Yes, for automating security operations 43% 0% 60% Yes No Addressing the practical challenges of AI adoption in cybersecurity, organizations consistently identify insufficient knowledge and/ or skills (54%) to deploy AI for cybersecurity, the need for human oversight (41%) and uncertainty about risk (39%) as the main hurdles. These findings indicate that trust is still a barrier to widespread AI adoption. Criminals are always willing to use all possible ways to get access to value, much of which is contained in the cyber infrastructure. Consequently, to stay ahead, those of us who defend must use every tool at our disposal – which now includes agentic AI. Arvind Krishna, Chief Executive Officer, IBM 22 Global Cybersecurity Outlook 2026