Google Leads Forrester Wave as Agentic AI Shifts Threat Intel from Triage to Action

Google Cloud has been designated a Leader in The Forrester Wave™: External Threat Intelligence Service Providers, Q3 2026, securing top scores across nine critical evaluation criteria including analyst tradecraft, attribution frameworks, and intelligence collection sources. The evaluation highlights Google Threat Intelligence’s progression in embedding specialized Gemini-powered autonomous agents capable of performing multi-step malware investigations, adversary campaign attribution, and threat mapping at machine speed, backed by frontline telemetry from Mandiant investigations and VirusTotal crowdsourcing. This development matters because cloud detection and response teams are consistently overwhelmed by high-volume, low-context threat feeds that fail to account for cloud-native adversary techniques. For CISOs, cloud security engineers, and SecOps analysts, external intelligence is only valuable if it can be operationalized instantly across distributed infrastructure. By infusing codified incident response tradecraft into autonomous analysis agents, organizations can move away from manual indicator lookups toward automated detection enrichment and direct policy generation, drastically reducing analyst toil and dwell time. In the broader cloud and DevOps landscape, threat intelligence is undergoing a structural shift from static reporting to integrated, active runtime enforcement. Historically, cyber threat intelligence operated as an out-of-band artifact consumed by specialized research teams. As cloud-native architectures become more interconnected and infrastructure changes occur continuously through automated CI/CD pipelines, security paradigms require intelligence that is programmatically consumable by policy engines and SIEM/SOAR platforms. Google’s consolidation of Mandiant expertise with cloud-scale AI models reflects a wider convergence where threat hunting, runtime telemetry, and automated remediation operate within a unified feedback loop. In practice, security engineers should assess how external intelligence feeds integrate natively with their current cloud SIEM and automated incident response playbooks. Teams adopting agentic threat intelligence must establish strict validation guardrails to supervise autonomous investigative workflows while verifying that synthesized adversary patterns translate directly into hardened cloud access policies, firewall rules, and runtime detection logic. While agent-driven analysis dramatically accelerates initial triage, practitioners must continue prioritizing human-led verification for edge cases and ensuring robust telemetry hygiene across multi-cloud environments.