Why Only 10% of Security Teams Value Their AI

Despite massive investment, only 10% of security teams say they get excellent value from their current AI-powered security tools.

AI for security has moved rapidly from a marketing concept to a major budget item. Security Operations Centers (SOCs) are quickly adopting AI-powered platforms, agents, and copilots, with billions of dollars invested across the industry. This spending spree reflects a widespread belief that AI is essential for modern cybersecurity. However, a recent analysis reveals a significant disconnect between this investment and the results. The data shows that despite rapid adoption and high spending, the promised value is not materializing for most users. A surprisingly small fraction of security teams are truly satisfied with the performance and impact of these new tools on their daily operations.

The core finding is that only 10% of SOCs believe they are getting "excellent value" from their AI security tools. This statistic challenges the prevailing industry hype and presents a major problem for CTOs, security leaders, and vendors. For organizations that have allocated significant budgets to these solutions, it signals a poor return on investment and raises questions about their current strategy. The low satisfaction rate suggests that the first wave of AI security products may be falling short on key promises, such as reducing analyst workload, improving threat detection accuracy, or speeding up response times. Instead of simplifying security, these tools may be adding complexity without a proportional benefit.

This gap between promise and reality sets the stage for a "second wave" of AI in security. The industry must now focus on delivering tangible value to the other 90% of users. Future tools will need to be better integrated into existing workflows, easier to manage, and demonstrably effective at solving core security challenges. For technology leaders, this data is a crucial reminder to critically evaluate AI tool purchases beyond marketing claims. The focus should shift to practical outcomes and measurable improvements rather than simply adopting the latest technology.

This highlights a critical gap between the hype and reality of AI in cybersecurity, forcing leaders to re-evaluate their strategy and investment in these expensive tools.

Companies may be overspending on AI security tools that deliver a poor return on investment. The low satisfaction rate suggests a risk of wasted budget and continued operational inefficiency in security teams, despite heavy investment in new technology.