AI adoption is picking up across every industry, but public sector patterns stand out

Across the board, AI adoption increased in 2025. Every industry tracked in the Zscaler cloud saw year-over-year growth in AI/ML activity, reinforcing that AI is no longer an emerging capability, but a persistent operating layer across daily workflows. What stands out in the public sector is the combination of rising AI usage volume and wide variation in how much AI/ML traffic is being blocked across sectors that all handle highly sensitive data.

Healthcare generated 71 billion AI/ML transactions in 2025, making it the largest public sector contributor by volume. Government followed with 38 billion transactions, reflecting steady year-over-year growth as agencies apply AI to operational and administrative workflows. Despite being the smallest by share, Education reached 16 billion transactions and grew 184% year-over-year—one of the fastest growing rates observed.

Blocked AI/ML traffic also varied sharply. Healthcare blocked 8.5% of AI/ML activity, government blocked 4%, and education blocked just 0.6%. AI adoption is rising across the public sector, but the level of blocked activity and the resulting visibility into how AI is being used looks very different across government, healthcare, and education.

Healthcare: high AI usage, higher blocking rates

Healthcare drove 7.2% of total AI/ML activity observed in the Zscaler cloud in 2025, as AI is increasingly integrated into both patient-facing and back-office workflows, including patient access and administrative processes.

Healthcare also recorded the highest percentage of blocked AI/ML transactions among public sector industries, with 8.5% blocked. In a sector where AI routinely intersects with regulated data, this level of blocked traffic reflects how quickly AI use cases can become data protection challenges.

Government: steady expansion with measured constraints

Government agencies and entities accounted for 3.8% of total AI/ML activity in the Zscaler cloud last year. Government use cases for AI are varied, from drafting, summarization, and research to internal operations, especially where departments are under pressure to improve efficiency.

The Government sector also blocked 4% of AI/ML activity, pointing to a more cautious posture than Education but fewer outright restrictions than Healthcare.

A key challenge in government AI adoption is consistency: AI usage spans agencies, departments, and environments with different governance maturity. A 2025 Government Accountability Office review found that generative AI use cases increased significantly across agencies over the past several years, but officials cited ongoing challenges in complying with federal policies and keeping up with evolving guidance.

Education: fastest growth, minimal blocked activity

The Education sector's 16 billion AI/ML transactions in 2025 represented just 1.6% of total activity—but 184% year-over-year growth made it one of the fastest-growing sectors in ThreatLabz analysis.

At the same time, Education blocked only 0.6% of AI/ML activity. That low level of blocked traffic suggests AI is being used broadly with limited friction, even as schools and universities work through privacy, integrity, and governance concerns. With AI adoption rising this quickly, visibility and guardrails will need to mature fast to reduce exposure.