The Future of SecOps Belongs to Case-Aware AI, Not Co-Pilots
For the last several years, the security industry has rallied around a single idea: give SOC analysts a co-pilot to help them query data, summarize alerts, and move faster. That certainly sounded promising, especially in a world drowning in alert fatigue and overwhelmed security teams. A potential solution for a problem faced across MDR teams, MSSPs, and mid-market SOCs alike.
But as the first generation of security co-pilots launched, it became clear that the clever interfaces wouldn’t fix broken workflows.
Today, the market is shifting. Analysts at leading research firms note that AI SOC agents are becoming one of the fastest-growing segments in security operations, with solutions emerging across two camps: full automation and staff augmentation.
And importantly, they, along with our team, emphasize that AI SOC agents aren’t replacements for human operators. Instead, they’re multipliers of human capability, unlocking efficiencies and consistencies that “traditional” tools can’t match.
“Co-Pilots” Have Brought Friction
Chat-based co-pilots promised natural language queries, but they introduced new points of friction for security teams.
Unable to Scale – A co-pilot that requires human input for every alert simply shifts the manual work from the console into a chat box. Chatting your way through 300 alerts a day isn’t sustainable.
Lacking Context – Most co-pilots treat every alert as a blank slate. But security data is deeply contextual: entity relationships, customer-specific patterns, environment baselines, historical behaviors. Without this grounding, co-pilots guess, often with the confidence of a system that doesn’t know it’s missing half the picture.
Hidden Reasoning – Security leaders and analysts need transparent logic to validate decisions. Yet co-pilots bury reasoning in conversation logs, masking how conclusions are reached. In security, opacity is risk.
That’s a central part of Embed’s differentiation through iSteps™.
Creating More Work – Chat is great for exploration, not throughput. SOC analysts need systems that eliminate repetitive work, not ones that turn that work into a sequence of prompt-and-response exchanges.
Why the Market Is Moving Toward Autonomous Agents
A leading analyst firm offers third-party validation to indicate a major shift underway: AI SOC agents are quickly becoming core to modern triage and investigation. This isn’t because they “replace analysts,” but because they extend and stabilize SOC capacity:
- They triage and investigate alerts autonomously, reducing workloads that drive turnover and burnout.
- They apply consistent logic to every alert, something human teams can’t sustain at scale.
- They improve SLAs and customer outcomes, especially critical for MSSP and MDR teams with thin margins and demanding clients.
- They free analysts to focus on complex reasoning, customer communication, and strategic decision-making, not repetitive classification.
In other words, AI SOC agents are becoming the baseline for more resilient security operations, not a novelty feature.
A Better Design Pattern for Assistance
At Embed, we didn’t adopt the co-pilot approach because it didn’t solve the core problem. It added convenience, but not capacity.
Instead, we invested first in an agentic security platform capable of autonomously triaging and investigating 100% of alerts, reducing false positives by 90%, and freeing analysts from the noise that overwhelms modern SOCs.
We introduced Case Assistant as intentionally different from the co-pilots you see on the market today.
Case-Aware By Design – Case Assistant understands the incident context, the relationships between entities, and the evidence already gathered. It doesn’t start from scratch with every question.
Draws from Purpose-Built Security Reasoning – It leverages correlated alert graphs, enrichment pipelines, and environment-specific insights; building on the same engine that powers our autonomous investigations.
Available On-Demand – Most alerts don’t need human attention. But when an analyst wants to dig deeper, they can use Case Assistant to do so instantly.
Shows Its Work – Transparency is a core part of our brand and a non-negotiable expectation for SOC teams that must trust automation with high-stake decisions. Case Assistant is built to expose the context and Embed’s AI reasoning, not hide it.
Where We Go From Here
At Embed, we’re committed to shaping the future of AI SOC agents. In a rapidly crowding industry, we augment human expertise with autonomous support that:
- Removes repetitive effort
- Surfaces high-value insights
- Preserves transparency
- Scales consistently across environments
- Enables analysts to apply judgment where it matters most
Autonomous investigations, transparent reasoning, and case-aware assistance are just the beginning.
