Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Today’s partners don’t need more portals, more PDFs, or more one‑time training sessions. They need momentum. That’s why we built Exabeam Sherpa, an AI‑powered, always‑on virtual Channel Account Manager (CAM) designed to help partners ramp faster, sell smarter, and scale performance as their teams grow.

Artificial intelligence (AI) within security operations has shifted from basic summarization to fully agentic systems that participate in threat detection, investigation, and response (TDIR). As these capabilities evolve, many vendors restrict access through add-ons, credits, or gated previews. The result is predictable: Analysts use AI less, trust it less, and see less value from it. Agentic AI capabilities should be available the moment analysts need it, not controlled through tiers or metering.

AI agents are moving into real workflows faster than most teams expected. According to PwC’s 2025 AI Agent Survey, 79% of companies are already adopting AI agents, and 88% of executives expect to increase AI-related budgets in the next year. These agents are now handling research, summarization, customer engagement, and operational tasks at a scale humans can’t match.

AI agents now operate as core identities in enterprise environments, authenticating, accessing data, and executing workflows at machine speed. Their flexibility and scale introduce a detection challenge traditional security models were never built to solve. Exabeam has seen this pattern before with insider threat and workload identities. AI agents accelerate the need for identity-centric detection.

The latest MITRE ATT&CK Enterprise Evaluations are out, featuring scenarios that emulate sophisticated actors like Scattered Spider and Mustang Panda. While every release of the findings is a significant event for the security community, this year’s evaluation highlights both new and recurring concerns for security professionals.

The Model Context Protocol (MCP) is emerging as a foundational interoperability layer for agentic AI, embraced by major platform providers. MCP simplifies how AI models connect to external tools and data. Think of it as a universal remote for security platforms: Instead of building fragile, one-off integrations, MCP allows AI to discover and use capabilities dynamically. For SIEM and detection providers, this shift is significant.