How Security, AI, and SOCs Impact Healthcare Organizations
Artificial intelligence is becoming a key asset for security operations centers, streamlining routine tasks, enhancing threat detection, and enabling analysts to stay ahead of AI-powered threats.
Artificial intelligence serves as a force multiplier for security operations centers (SOCs), enabling healthcare organizations to address unique challenges related to patient safety, regulatory compliance, and the complexity of clinical and administrative systems.
AI accelerates the triage of noisy alerts and identifies subtle patterns across electronic health records, cloud logs, endpoints, and medical IoT devices. By linking seemingly harmless events into a unified view of an active threat, it helps detect and stop stealthy, long-running attacks that might otherwise evade human detection.
AI’s Impact on Today’s Security Operations Centers
In sectors like healthcare, where protecting patient data is paramount, AI-powered security operations centers (SOCs) provide a significant edge against increasingly advanced cyber threats.
According to Adam Khan, vice president of global security operations at Barracuda, AI is already transforming security operations by speeding up investigations and easing the burden on security teams.
“AI enables faster, more accurate threat detection and automates responses by analyzing large volumes of alerts across different security tools and environments,” he explains.
For instance, AI can identify suspicious behavior—such as a compromised Microsoft 365 account—and automatically revoke access within seconds, minimizing potential harm.
“This rapid, machine-level response reduces the risk of breaches and allows analysts to concentrate on more complex threats,” Khan adds.
Empowering Healthcare SOCs with Generative and Agentic AI
Generative AI transforms raw telemetry into actionable insights by summarizing incidents in plain language, generating containment scripts, and turning technical findings into executive-level updates that include potential regulatory impact.
Agentic AI takes it a step further by performing predefined, approved actions—executing response playbooks in a secure, least-privilege environment. It can initiate tasks like opening support tickets, isolating endpoints, or pulling identity risk signals, while keeping human oversight in place for critical decisions.
This approach also removes friction during handoffs by automatically escalating incidents to the appropriate teams using integrated asset inventories, on-call schedules, and incident response workflows. For instance, it can send alerts about unusual access to protected health information to the identity team, or route a clinical VLAN issue to the networking team.
“By combining retrieval-augmented generation with runbooks and historical cases, new analysts essentially gain an ‘on-call copilot’—improving speed, consistency, and decision-making while staying compliant,” says Tom Gorup, vice president of SOC operations at Sophos.
He emphasizes that AI agents are not “set it and forget it” tools. As AI models evolve, organizations must adapt and update their systems accordingly.
As healthcare IT environments shift—whether through new cloud infrastructure, applications, or endpoints—security leaders must ensure AI agents remain aligned with those changes. With evolving threats, updated playbooks are essential for effective response.
“This means healthcare SOCs will need to rethink their approach and make more targeted investments in AI than they have in the past,” Gorup adds.
Leveraging AI to Fill Cybersecurity Staffing Gaps
Michael Stempf, vice president of product experience at Commvault, emphasizes that automating high-volume, low-complexity tasks and investing in upskilling existing staff is essential to addressing the significant talent shortages in healthcare.
“AI takes on first-pass alert triage, log parsing, data enrichment, evidence collection, and correlates seemingly normal events to identify real threats,” he explains.
It automatically creates draft investigations and assigns or escalates them to the appropriate team members, eliminating delays caused by uncertainty about ownership. Additionally, AI accelerates onboarding by transforming institutional knowledge into searchable, context-aware guidance, enabling new analysts to navigate complex healthcare IT environments more quickly.
“This approach allows SOCs to function efficiently with fewer Level 1 analysts and enables senior staff to focus on threat hunting and handling complex incidents—so long as data access is well-managed and escalation protocols are clearly defined,” Stempf adds.
