The No. 1 security issue respondents are most hopeful that AI will help fix is the prioritization of disparate results from scanning tools, for which 82% are hopeful for gains

21% say they apply AI to security through a mix of vendor-led and internal AI.

Sophisticated threat landscape was the most commonly cited security pain point, named by 60% of respondents

A scant 6% reported that AI is detrimental to their security program

Costs were an obstacle for 46% of respondents in effective use of AI.

Difficulty in tuning, training, and supervising AI was an obstacle to the effective use of AI for 39% of respondents

Almost 70% of CISOs/CSOs/CTOs have taken on new data discovery responsibilities, specifically for AI initiatives.

72% of CISOs express the most concern about discovering data used in AI initiatives.

Almost 59% of US cybersecurity professionals added new AI data responsibilities in the past year.

The top use case where security leaders say AI will offer most value is vulnerability and risk management, named by 74% of respondents

Third-party and supply chain risk was a big security pain point (42%)

Just 25% of teams use AI to power vulnerability prioritization

Just 18% have utilized GenAI to speed up summarization and reporting work

82% were optimistic about AI applicability to sifting through disparate results from scanning tools

81% were optimistic about AI applicability to dealing with overload of data

Lack of skilled personnel is the biggest obstacle to the effective use of AI in cybersecurity today, cited by 55% of respondents

Lack of transparency in AI decision making was an obstacle for 46% of respondents in the effective use of AI.

Just a fraction of respondents said that their tools come trained and/or tuned — 5%

Just over half of respondents said that they regularly disable AI functionality in some or all security tooling due to a range of considerations

1 in 5 respondents reporting that 75% or more of their tool stack promotes AI capabilities