In 2026, every cybersecurity vendor has added "AI-powered" to their branding. But after using AI in production in Valta for threat intelligence relevance scoring, my perspective on AI and cybersecurity in 2026 is more nuanced than marketing would suggest. AI in security works - but not where most vendors say it works.
Where AI actually works
Alert triage and prioritization: AI excels at reducing noise. In Valta, the GPT-4.1-based relevance scoring engine reduced irrelevant alerts by 70%. AI is good at contextualization - at understanding if a CVE is relevant for YOUR specific environment, not generically. Behavioral analysis: ML is effective at identifying anomalies in user and entity behavior (UEBA). Anomalous login patterns, access to unusual resources, data exfiltration patterns - ML catches things that static rules cannot.
Where AI is still hype
"Autonomous AI replacing the SOC analyst" is pure marketing. AI does not understand business context, does not know your infrastructure, does not know that traffic spike at 3 AM is the legitimate backup. AI as a complete replacement for the human analyst does not exist in 2026 - and I doubt it will in 2027. AI as an assistant that amplifies analyst capabilities? That already works.
Another underestimated aspect: AI as a weapon for attackers. Automatic generation of convincing phishing emails, polymorphic malware creation, deepfakes for advanced social engineering - this is already reality. The AI arms race between attackers and defenders has begun, and those who ignore AI in their defensive strategy will be at a disadvantage. My approach: use AI where it adds measurable value (triage, prioritization, enrichment), keep humans where judgment is needed (investigation, response decisions, communication). Don't buy "AI-powered" - buy measurable results.
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