63% of retailers aim to invest significantly in machine learning for pattern matching to enhance cybersecurity.

24% of healthcare executives say they are likely to invest in machine learning for pattern matching.

Of organizations using AI/ML, 88% are incorporating generative AI at some level.

The primary drivers for AI/ML adoption are improving operational efficiency (41%) and maintaining competitive advantage (40%).

46% of respondents say their organizations use AI/ML to prevent cyberattacks.

Over a quarter (27%) of financial and professional services organizations have AI and machine learning as an established part of their financial crime compliance programs, exceeding 2023 levels (24%).

Artificial intelligence (AI - 95%), machine learning capabilities (93%), and Internet of Things (IoT - 89%) initiatives are among the most widely adopted emerging technologies over the past 12 months.

Less than half (48%) of organisations express high confidence in controlling sensitive data used for AI/ML training.

Looking ahead, 70% of organisations will focus on AI/ML data usage governance.

79% of security teams struggle to classify sensitive data used in AI/ML systems.

34% of enterprises admit their security controls are lagging behind AI's rapid deployment.