The integration of artificial intelligence (AI) into cybersecurity is no longer a futuristic concept; it’s a present-day reality. However, a recent study by Exabeam reveals a significant disconnect between executive optimism and analyst experience regarding AI’s impact on security operations. While AI adoption is widespread, its influence on productivity, trust, and team structure varies dramatically, highlighting a critical “AI Trust Gap” that organizations must address to fully realize the potential of this transformative technology.
The study paints a picture of executives envisioning AI as a silver bullet, capable of slashing costs, streamlining operations, and bolstering strategic decision-making. A staggering 71% of executives believe AI has significantly improved productivity across their security teams. Yet, the analysts on the front lines, those who interact with these tools daily, paint a very different picture. Only 22% of analysts share the executives’ rosy outlook. This perception gap isn’t just a matter of differing opinions; it exposes a fundamental issue with operational effectiveness and the level of trust placed in AI systems.
The Analyst’s Perspective: Alert Fatigue and the Need for Human Oversight
For many analysts, AI hasn’t eliminated manual work; it has simply reshaped it. Instead of reducing the workload, AI tools often generate a deluge of false positives, leading to increased alert fatigue and the persistent need for human oversight. This suggests that some organizations may be overestimating the maturity and reliability of AI tools while simultaneously underestimating the complexities of real-world implementation. The promise of autonomy often falls short, leaving analysts burdened with managing tools that require constant tuning and supervision.
“There’s no shortage of AI hype in cybersecurity — but ask the people actually using the tools, and the story falls apart,” said Steve Wilson, Chief AI and Product Officer at Exabeam. “Analysts are stuck managing tools that promise autonomy but constantly need tuning and supervision. Agentic AI flips that script — it doesn’t wait for instructions, it takes action, cuts through the noise, and moves investigations forward without dragging teams down.”
Where AI Shines: Threat Detection, Investigation, and Response (TDIR)
Despite the challenges, the study also highlights AI’s positive impact in specific areas, particularly in threat detection, investigation, and response (TDIR). A majority (56%) of security teams report that AI has improved productivity in these areas by offloading repetitive analysis, reducing alert fatigue, and improving time to insight. AI-driven solutions are enhancing security operations with improved anomaly detection, faster mean time to detect (MTTD), and more effective user behavior analytics.
However, even in these areas where AI demonstrates its value, trust in its autonomy remains low. Only 29% of security teams trust AI to act independently, and that figure plummets to a mere 10% among analysts. While 38% of executives are willing to let AI act independently in cyber defense, the analysts who are directly responsible for responding to threats remain hesitant to relinquish control.
Performance Precedes Trust: Earning Analyst Confidence
The industry seems to agree on one fundamental principle: performance precedes trust. In security operations, organizations aren’t looking to completely hand over the reins to AI; they’re counting on it to augment human capabilities and exceed the limits of the human mind at scale. To earn the trust of analysts, AI systems must consistently deliver accurate outcomes and automate tedious workflows, becoming a force multiplier that enables faster, smarter threat detection and response.
The Evolving Security Workforce: Restructuring for the AI Era
The adoption of AI is also driving structural shifts in the security workforce. Over half of the surveyed organizations have restructured their teams due to AI implementation. While 37% report workforce reductions tied to automation, 18% are expanding hiring for roles focused on AI governance, automation oversight, and data protection. This reflects a transition towards a new operational model for modern security operations centers (SOCs), where agentic AI supports faster decisions, deeper investigations, and higher-value human work.
Regional Variations: A Global Perspective
The study also reveals significant regional variations in the perceived impact of AI. Organizations in India, the Middle East, Turkey, and Africa (IMETA) report the highest productivity gains (81%), followed by the United Kingdom, Ireland, and Europe (UKIE) (60%) and Asia Pacific and Japan (APJ) (46%). In contrast, only 44% of North American organizations report similar improvements. These regional differences may be attributed to variations in AI adoption strategies, the maturity of AI tools, and the specific security challenges faced by organizations in different parts of the world.
Bridging the AI Trust Gap: A Path Forward
As AI continues to reshape the cybersecurity landscape, organizations must bridge the gap between leadership ambition and operational execution. To close the divide between vision and reality, organizations should consider adopting agentic AI for its proactive, action-based capabilities. Successful strategies will be defined by their ability to align AI capabilities with front-line needs, involve analysts in deployment decisions, and prioritize tangible outcomes over the allure of hype. By focusing on performance, transparency, and collaboration, organizations can foster trust in AI and unlock its full potential to transform security operations.
