99% of teams are embracing AI78% of leaders are confident that changes to their roles will be manageableBut this enthusiasm coexists with many concerns about AI, including frustration at the pace of adoption. And a deeper analysis of the data suggests that these adoption challenges may be preventing teams from exploring more impactful applications. While AI adoption is widespread, realizing its full potential remains elusive for many of the leaders surveyed. IDC’s white paper found that most security leaders view AI as a force multiplier, expecting future benefits like increased business efficiency (54%), improved customer experience (51%), and greater competitive advantage (46%).But in the present, these teams are grappling with significant barriers to adoption:
33% are worried about training capacity27% have compliance-related concerns26% have concerns about AI hallucinations25% are focused on secure AI adoption20% are frustrated by slow implementationAs we examine IDC’s data further, two potential solutions emerge to help teams better realize AI’s potential. Solution #1: Move to use cases that support critical decision-making: IDC’s research reveals that the most popular AI use cases for security teams primarily involve data manipulation:
“¢ 36% use AI for summarization”¢ 35% use AI for threat intelligence analysis”¢ 34% use AI for threat detectionWhile data summarization is an excellent starting point for AI adoption, it should be viewed as a stepping stone rather than an end goal.Less common in IDC’s research, but indicative of more mature AI programs are the following use cases:
“¢ 32% use AI for risk assessments”¢ 25% use AI for attack surface management”¢ 22% use AI for advanced triageThis focus on data manipulation implies that many of the security teams featured in the study are still early in their AI journey. To achieve true business impact, they’ll need to progress from short-term efficiency gains through data summarization to applications that fundamentally transform operations. For instance, an AI-powered risk prioritization workflow could offer more substantial, enduring benefits to an organization’s security posture.Of course, realizing these advanced use cases requires leaders to address the concerns highlighted earlier, which leads us to our second potential solution. Solution #2: Adopt a flexible, holistic approach to AI: To pave the way for these advanced use cases, security teams need to move beyond relying on isolated AI features in existing tools and focus on developing a comprehensive AI strategy that addresses their specific challenges.Based on the challenges highlighted in IDC’s research, this approach might involve:
Integration of AI with workflow orchestration combining AI capabilities with automated workflows to maximize impact and efficiency.Skill development investing in training to ensure team members can effectively leverage AI tools and interpret their outputs.An adaptive AI strategy developing a flexible AI roadmap that can evolve with technological advancements and changing security needs.Robust security and privacy measures choosing tools with strong guardrails to address concerns about security, data handling, and compliance.As AI matures, the promise for security use cases will grow exponentially. If security leaders can effectively manage their concerns with the right tooling and processes, their trust in AI will grow, too.A flexible and holistic approach to AI, like the one described above, can help teams navigate adoption complexities, address current challenges, and prepare for more sophisticated AI applications as technology evolves.A flexible, security-focused AI strategy enables leaders to quickly act on emerging opportunities for impactful use cases, and ultimately facilitate the delivery of AI’s promised ROI.Learn more about how security leaders are approaching AI in 2025 in IDC’s white paper.
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