AI Adoption
We've curated 144 cybersecurity statistics about AI adoption to help you understand how organizations are integrating machine learning and automated defenses to combat evolving cyber threats in 2025.
Showing 1-20 of 144 results
86% of IT decision-makers and platform engineering leaders say AI has increased demands on infrastructure teams.
80% of developers and technology buyers say their organization adopted AI tools faster than it developed policies to govern them.
67% of IT decision-makers and platform engineering leaders say development is ahead of infrastructure in AI adoption.
63% of workers rate AI as either absolutely essential or very necessary to their jobs.
31% of CTOs, CISOs, and CIOs say their organization's tolerance for friction in enabling AI building is near zero.
32% of IT leaders report having agentic AI in production
66% of IT leaders cite data infrastructure and data quality issues as barriers to agentic AI adoption
72.9% of organizations have already deployed AI in some form.
82% of U.S. mid-market enterprise IT leaders say AI is already in production somewhere in their organization or in widespread use.
90% of CTOs, CISOs, and CIOs say business pressure to enable AI building has increased in the past 12 months.
10% of U.S. mid-market enterprise IT leaders cite lack of internal expertise as the top barrier to scaling AI.
16% of U.S. mid-market enterprise IT leaders cite integration complexity as the top barrier to scaling AI.
90% of IT leaders say data streaming helps ease the path to AI adoption
17% of U.S. mid-market enterprise IT leaders cite data readiness as the top barrier to scaling AI.
84% of IT leaders actively stall business-led AI initiatives.
88% of organizations say AI deployment is outpacing their identity and security infrastructure.
93% of organizations say AI is a trigger for reevaluating identity infrastructure.
67% of organizations report that AI coding assistants are now widely adopted across development teams.
70% of organizations have AI-powered components in production.
IT professionals at AI‑mature organizations save an average of 6 hours per week, double the 3 hours saved at organizations with the lowest levels of AI adoption.