AI
We've curated 1618 cybersecurity statistics about AI to help you understand how machine learning algorithms, automated threat detection, and AI-driven defenses are shaping the landscape of cybersecurity in 2025.
Showing 1601-1618 of 1618 results
Nearly 2 in 5 organisations are counting on cost savings from AI-driven efficiencies to pay for the technology.
35% of enterprises are just beginning their AI journey.
Half of respondents said their organisation will divert capital allocations from other budget areas to fund AI initiatives.
77.4% of API-related vulnerabilities in AI products are directly API-related, such as weak API authentication, inadequate rate limiting, and broken access controls.
Only 1.1% of the vulnerabilities in AI products were entirely unrelated to APIs.
85% of organizations face challenges in scaling and operationalizing AI across their business.
49% perform a privacy risk assessment to monitor their privacy programs.
Machine learning-based discovery tools often identify 31% more API endpoints than those reported by enterprises.
79% of businesses that deploy AI lack a way to control, manage and sustain it effectively.
48% of enterprises report implementing specific security controls for AI deployments.
85% of businesses face challenges in scaling and operationalising AI across their businesses.
12% of enterprises are waiting for security controls to be ready before deploying AI.
93% of businesses acknowledge that AI must be "fully integrated" into their processes to maximise their return on investment.
Gartner predicts that Spending on AI-optimised servers will double that of traditional servers in 2025, reaching $202 billion.
90% of surveyed executives expect to scale, optimise, or innovate with AI within the next two years.
Only 36% of respondents said their organisation has a dedicated AI fund.
54% of enterprises report engaging in multiple AI deployments.
AI vulnerabilities increased by 1,025% from 2023 to 2024.