Seemplicity

88% of enterprises have integrated AI into their security stacks

50% of security professionals spend more time on coordination than technical analysis at enterprises

31% of enterprises fully trust AI-sourced recommendations to influence prioritization decisions

45% of U.S.-based cybersecurity leaders work 11 or more extra hours per week.

89% of U.S.-based cybersecurity leaders say their position now requires significant cross-functional collaboration and business alignment.

20% of U.S.-based cybersecurity leaders work an additional 16 or more hours weekly.

85% of organizations believe their cross-team collaboration is strong.

49% measure success of vulnerability remediation by mean time to remediation.

54% measure success of vulnerability remediation by fewer breaches.

A lack of transparency and explainability was the top reason for turning off AI functionality, cited by 58%

77% of respondents reported that one or more of those vendors had overhyped their AI performance or are underdelivering on their promises

Security and privacy risks were a reason for turning off AI functionality, cited by 55%

59% of security and engineering teams still negotiate who is responsible for each fix at enterprises.

94% of cybersecurity and IT leaders at enterprises can translate security risks for non-technical stakeholders

43% of cybersecurity and IT leaders at enterprises admit their remediation processes are still ad hoc

64% of U.S.-based cybersecurity leaders report sufficient budget for AI.

94% of U.S.-based cybersecurity leaders would still choose cybersecurity as a career.

52% of U.S.-based cybersecurity leaders say training for human-AI collaboration is limited or insufficient.

44% of U.S.-based cybersecurity leaders say their role feels emotionally exhausting more often than rewarding.

73% of U.S.-based cybersecurity leaders say AI oversight and governance is the most important future capability.

68% of U.S.-based cybersecurity leaders rate technical expertise as the most important future capability.

85% of U.S.-based cybersecurity leaders feel pressure to strengthen communication and business skills because of AI.

82% of U.S.-based cybersecurity leaders say people skills are more central to cybersecurity leadership than five years ago.

Fewer than 1 in 5 organizations use structured prioritization models.

30% cite budget limitations as their biggest barrier to adopting additional solutions.

Nearly 40% of organizations still rely on manual workflows for most of their vulnerability remediation processes.

1 in 5 organizations take four or more days to fix critical vulnerabilities.

91% of organizations experience delays in vulnerability remediation.

61% of organizations still measure success of vulnerability remediation by the number of vulnerabilities resolved.

86% of organizations are increasing their security spending in 2025.

Nearly a third of respondents reported that their team spends at least four hours per week training AI models within their own tools or within commercially available AI functionality

56% of security teams say the use of AI has become crucial to their team’s operations

42% cited identity and access management as a security function where AI will provide the most value in the next 3 years

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%)

Incident response was the second security function where AI will provide the most value in the next 3 years, cited by 59% of respondents

False positive and negative rates are the No. 1 way that organizations reported that they evaluate the efficacy of AI in security, named by 66% of respondents

Just 6% of respondents say that they fully outsource their AI training

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

The top three most common security use cases for AI are endpoint security (52%), basic vulnerability scanning (47%), and antivirus/anti-malware (40%)

56% cited data protection as a security function where AI will provide the most value in the next 3 years

Among those security departments that do their own custom AI work, 66% report that they have hired their own internal data science staff within their security teams

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

Endpoint security was a current application of AI in 52% of security tech stacks

About 16% of security teams say their use of AI has been very beneficial and have made it a core part of their program

Speed of threat detection was used to evaluate AI efficacy by 57% of respondents

Endpoint security (34%), antivirus/anti-malware (31%), and malware analysis (31%) were the security tech categories where AI is thought to be the most overhyped

The majority of organizations (55%) say that they’ve enabled AI in under half the tools in their environments that have it available

39% of firms are using AI to solve data overload problems that stymie vulnerability and exposure management work

Antivirus/anti-malware was a current application of AI in 40% of security tech stacks