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Current State: High Hopes Meet Harsh Realities
A new survey of security leaders has revealed a stark contrast between AI expectations and realities – while enthusiasm for AI’s potential runs high, teams are grappling with significant challenges in implementation, demonstrating ROI, and realizing tangible business impact.
Sponsored by Tines and AWS, IDC’s Voice of Security 2025 white paper features survey data from over 900 security leaders in the US, Europe, and Australia.
Absenteeism of AI Adoption
At first glance, the data shows that security leaders’ sentiment toward AI is largely positive:
- 99% of teams are embracing AI
- 78% of leaders are confident that changes to their roles will be manageable
However, 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.
Challenges in AI Adoption
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%).
However, in the present, these teams are grappling with significant barriers to adoption:
- 33% are worried about training capacity
- 27% have compliance-related concerns
- 26% have concerns about AI hallucinations
- 25% are focused on secure AI adoption
- 20% are frustrated by slow implementation
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 detection
While 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 triage
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
Conclusion
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.
FAQs
- What is the ID of the white paper? IDC’s Voice of Security 2025 white paper
- What is the percentage of teams embracing AI? 99%
- What are the most common AI use cases for security teams? Data summarization, threat intelligence analysis, and threat detection
- What are some of the challenges in AI adoption? Training capacity, compliance-related concerns, AI hallucinations, secure AI adoption, and slow implementation
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