AI isn’t just something to adopt; it’s already embedded in the systems we rely on. From threat detection and response to predictive analytics and automation, AI is actively reshaping how we defend against evolving cyber threats in real time. It’s not just a sales tactic (for some); it’s an operational necessity.
Yet, as with many game-changing technologies, the reality on the ground is more complex. The cybersecurity industry is once again grappling with a familiar disconnect: bold promises about efficiency and transformation that don’t always reflect the day-to-day experiences of those on the front lines. According to recent research, 71% of executives report that AI has significantly improved productivity, but only 22% of frontline analysts, the very people who use these tools, say the same.
When solutions are introduced without a clear understanding of the challenges practitioners face, the result isn’t transformation, it’s friction. Bridging that gap between strategic vision and operational reality is essential if AI is to deliver on its promise and drive meaningful, lasting impact in cybersecurity.
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Steve Povolny
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Senior Director of Security Research & Competitive Intelligence at Exabeam.
Executives love AI
According to Deloitte, 25% of companies are expected to have launched AI agents by the end of 2025, with that number projected to rise to 50% shortly thereafter. The growing interest in AI tools is driven not only by their potential but also by the tangible results they are already beginning to deliver
For executives, the stakes are rising. As more companies begin releasing AI-enabled products and services, the pressure to keep pace is intensifying. Organizations that can’t demonstrate AI capabilities, whether in their customer experience, cybersecurity response, or product features, risk being perceived as laggards, out-innovated by faster, more adaptive competitors. Across industries, we’re seeing clear signals: AI is becoming table stakes, and customers and partners increasingly expect smarter, faster, and more adaptive solutions.
This competitive urgency is reshaping boardroom conversations. Executives are no longer asking whether they should integrate AI, but how quickly and effectively they can do so, without compromising trust, governance, or business continuity. The pressure isn’t just to adopt AI internally to drive efficiency, but to productize it in ways that enhance market differentiation and long-term customer value.
But the scramble to implement AI is doing more than reshaping strategy, it’s unlocking entirely new forms of innovation. Business leaders are recognizing that AI agents can do more than just streamline functions; they can help companies bring entirely new capabilities to market. From automating complex customer interactions to powering intelligent digital products and services, AI is quickly moving from a behind-the-scenes tool to a front-line differentiator. And for executives willing to lead with bold, well-governed AI strategies, the payoff isn’t just efficiency, it’s market relevance.
Analysts distrust AI
If anyone wants to make their job easier, it’s a SOC analyst, so their skepticism of AI comes from experience, not cynicism. The stakes in cybersecurity are high, and trust is earned, especially when systems that are designed to protect critical assets are involved. Research shows that only 10% of analysts currently trust AI to operate fully autonomously. This skepticism isn’t about rejecting innovation, it’s about ensuring that AI can meet the high standards required for real-time threat detection and response.
That said, while full autonomy is not yet on the table, analysts are beginning to see tangible results that are gradually building trust. For example, 56% of security teams report that AI has already boosted productivity by streamlining tasks, automating routine processes, and speeding up response times. These tools are increasingly trusted for well-defined tasks, giving analysts more time to focus on higher-priority, complex threats.
This incremental trust is key. While 56% of security professionals express confidence in AI for threat detection, they still hesitate to let it manage security autonomously. As AI tools continue to prove their ability to process vast amounts of data and provide actionable insights, initial skepticism is giving way to more measured, conditional trust.
Looking ahead
Closing the perception gap between executive enthusiasm and analyst skepticism is critical for business growth. Executives must create an environment where analysts feel empowered to use AI to enhance their expertise without compromising security standards. Without this, the organization risks falling into the hype cycle, where AI is overpromised but underdelivered.
In cybersecurity, where the margin for error is razor-thin, collaboration between AI systems and human analysts is critical. As these tools mature and demonstrate real-world impact, trust will grow, especially when their use is grounded in transparency, explainability, and accountability.
When AI is thoughtfully integrated and aligned with practitioner needs, it becomes a reliable asset that not only strengthens defenses but also drives long-term resilience and value across the organization.
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