The recent escalation in tensions involving Israel, the United States, and Iran has highlighted a critical reality for security leaders across the Middle East: geopolitical instability does not only raise the risk of external cyberattacks, but it fundamentally changes internal risk dynamics in ways many organizations are not prepared to manage. As enterprises continue to navigate remote work shifts, dispersed access patterns, complex supply chain dependencies, and the growing adoption of artificial intelligence (AI)-powered business tools, insider risk has become more complex, less predictable, and harder to detect using conventional methods. In this environment, AI is emerging not just as a cybersecurity enhancement, but as a practical tool for managing uncertainty at scale.

According to Mazen Adnan Dohaji, senior vice president and general manager of IMETA at Exabeam, conflict does not necessarily increase the number of malicious insiders, but it creates more operational noise at the exact moment defenders need clarity the most. The real challenge for security teams is not simply that conflict creates more cyber risk, but that it creates more noise, more edge cases, and more ambiguity when faster decisions are needed. That distinction matters significantly in the Middle East, where organizations are balancing ambitious digital transformation goals with rising concerns about sovereignty, resilience, and cyber preparedness. During periods of geopolitical tension, routine behaviors can suddenly appear anomalous: users logging in from unfamiliar locations, contractors requiring temporary privileged access, or employees interacting with both sanctioned and unsanctioned generative AI tools in ways that security teams have limited visibility into.

Traditional insider threat programs fall short

Traditional insider threat programs, built on static rules and manual investigations, often falter under these conditions. Behavior, not alerts, is the new signal. Security teams should focus less on expanding watchlists and more on understanding how normal behavior changes under stress. This is where AI-driven user and entity behavior analytics (UEBA) becomes critical. Machine learning can establish baselines for normal activity across employees, contractors, service accounts, and privileged users. It helps identify subtle anomalies that may signal misuse, coercion, credential compromise, or data exfiltration. Insider risk is rarely a single dramatic event; more often it emerges through a sequence of explainable but unusual actions that only become meaningful when viewed together. AI helps security teams connect those signals earlier, before misuse, compromise, or exfiltration becomes harder to contain.

Insider risk now includes machines

The rise of non-human identities is transforming the insider risk landscape. As enterprises adopt AI agents, copilots, and automated workflows to retrieve data and trigger actions, insider risk expands beyond human actors. AI agents and automated workflows increasingly authenticate to systems, retrieve documents, call APIs, and trigger actions on behalf of users. For Middle East organizations accelerating AI adoption—particularly in sectors such as government, financial services, and energy—this significantly expands the attack surface. Compromised or over-privileged AI agents can create risks similar to those posed by human insiders, but at machine speed. Organizations need visibility into agent behavior, identity changes, and privilege escalation, while linking human actions and machine actions into a unified investigative path. Separating AI and insider risk domains is a mistake; increasingly, they are the same problem.

AI for investigation, not just detection

Beyond detection, AI is reshaping the investigation layer. The right tooling can automatically collect evidence, correlate related activity, build timelines, summarize cases, and surface the entities most likely to require action. In a stretched security operations center (SOC), that is not a convenience feature; it is how teams protect analyst time. This can be especially valuable as regional defenders handle daily threats and uncertainty from geopolitical events. The bigger lesson is that resilience in today's threat environment is increasingly about context. Unstable operating conditions make intent harder to read, risky behavior easier to hide, and traditional detection models less effective.

For organizations across the Middle East, this means turning AI from an innovation narrative into an operational discipline. It involves instrumenting environments where work is actually happening, monitoring sanctioned AI use, building behavioral baselines, and using automation to reduce analyst workload without removing human oversight. It also means preparing for realistic scenarios: excessive data movement before an employee's exit, abnormal off-hours access, or an AI agent suddenly expanding its access pattern. Real resilience gives defenders the ability to see changes in behavior early, connect human and machine activity, investigate faster, and act before an anomaly becomes a breach.

Practical steps for organizations

To effectively manage insider risk amid geopolitical turmoil, organizations should implement AI-driven UEBA that monitors both human and non-human identities. They must invest in tools that provide unified visibility across all access points, including cloud environments, on-premises systems, and third-party applications. Additionally, security teams should conduct regular tabletop exercises simulating insider threat scenarios, such as an employee exfiltrating data during a period of heightened tension or an AI agent being used to access sensitive information without authorization. By integrating AI risk and insider risk into a single strategy, organizations can stay ahead of the evolving threat landscape.

The escalation in the Middle East serves as a reminder that cybersecurity is not just about defending perimeters; it is about understanding behavior. With AI, security teams can gain the context they need to distinguish between normal operational changes and genuine threats, ensuring resilience in the face of uncertainty.

Source: ComputerWeekly.com News