As AI becomes part of everyday enterprise operations, security teams are working in environments that behave very differently from the past. Networks are always on. Activity is continuous. And identities now include humans, service accounts, and AI agents acting autonomously at machine speed.
That shift is driving the thinking behind the latest platform update from Vectra AI. The focus is not on adding more tools or alerts, but on helping defenders keep up with environments where attacks unfold faster than human workflows.
AI agents act like identities
AI agents don’t look like traditional users, but they still behave in patterns. The challenge is telling the difference between expected automation and an attacker abusing that automation to move quickly through the environment.
Vectra AI’s VP of Product Research and Strategy, Mark Wojtasiak, explained to MSSP Alert that the key signal is not just what is happening, but how fast it happens. “The short answer is that intent shows up in behavior over time, and increasingly, in speed.”
He points out that both human and non-human identities leave behavioral trails. “In modern enterprises, AI agents, service accounts, and automations behave differently than humans, but they still follow patterns. Vectra AI continuously observes how identities - human and non-human - authenticate, access resources, move laterally, and interact across network, identity, cloud, and SaaS environments.”
Where things break down is when attackers step in. “Normal automation is typically consistent and bounded. When attackers hijack or abuse AI agents, behavior changes, not just in what is accessed, but in how fast activity unfolds. Sudden spikes in velocity, rapid lateral movement, accelerated privilege use, or compressed sequences of actions are strong indicators of automation being abused to move at machine speed.”
By watching behavior and velocity together, the platform aims to surface problems earlier. “By correlating behavior and velocity across the modern network in real time, Vectra AI can distinguish expected AI-driven activity from attacker-driven automation, often early in the attack lifecycle before access turns into impact.”
What “machine speed” really means
Stopping attacks at machine speed does not mean removing humans from the loop. Wojtasiak is clear that automation matters most in the parts of security work that slow teams down today. “Machine speed matters most in detection, correlation, and prioritization - that’s where defenders lose the most time today.”
Vectra AI processes telemetry as it is generated and connects activity across domains without waiting for batch jobs or manual review. “Vectra AI continuously processes telemetry as it’s generated, correlates activity across domains, and prioritizes risk based on how fast and how far an attack is progressing. That removes the latency introduced by batch analysis, manual correlation, and alert overload.”
Automation can also trigger predefined actions, but only when confidence is high. “Where automation is appropriate, the platform can trigger integrations and workflows - such as containment actions or investigation steps - based on high-confidence behavior. But this isn’t about replacing humans. It’s about bringing humans in earlier, with clarity, instead of after damage is already done.”
The end goal is better starting points for analysts. “Human analysts still make judgment calls, oversee response, and handle business-context decisions. The difference is they’re no longer starting from raw data - they’re starting from answers.”
Scaling without chaos for MSSPs
For MSSPs running multi-tenant SOCs, scale often creates risk instead of efficiency. More customers usually means more alerts and more manual work. “MSSPs told us their biggest challenge isn’t lack of data - it’s scale without chaos,” Wojtasiak said.
Vectra AI separates customer environments while still automating analysis. “Vectra AI is designed to operate across many environments while keeping customer telemetry, context, and investigations strictly separated. Each tenant maintains its own behavioral baselines, risk context, and visibility, which is essential for both security and trust.”
At the same time, the platform handles correlation and prioritization automatically. “The platform reduces analyst workload by doing the hardest parts automatically: correlating activity across domains, suppressing low-value noise, and prioritizing what actually matters.”
That changes how teams operate day to day. “Analysts don’t have to manually stitch together identity events, network flows, and cloud activity for every customer - that correlation is built in. The result is fewer alerts, faster investigations, and the ability to support more customers without linear increases in staff or risk.”
Differentiation focused on outcomes
In a market crowded with AI claims, Wojtasiak keeps the differentiation narrow. “We’re differentiating by being specific about where AI actually helps defenders - and where it doesn’t.”
The platform is built around one core problem. “Vectra AI focuses on one concrete problem: defender latency in environments that operate at AI speed.”
That reflects how enterprise security has changed. “Identity is now the control plane, non-human entities outnumber people, and attacks unfold across the network in motion. Platforms that were designed for static environments or single domains can’t keep up with that reality.”
For Vectra AI, success is measured by what partners can deliver. “Our differentiation isn’t that we use AI. It’s the outcomes our MSSP partners deliver rooted in clarity, confidence, and resilience for the AI enterprise.”
As AI reshapes enterprise infrastructure, security teams are no longer short on data. They are short on time. Vectra AI’s platform update is aimed at closing that gap by focusing on behavior, speed, and context.
