The State of Enterprise AI Governance
Comprehensive insights into how enterprises are deploying, governing, and managing AI systems in 2025. Based on data from 500+ organizations across industries.
Key Findings
The most critical insights from our 2025 research
of enterprises now using AI in production
lack formal AI governance framework
cite data privacy as top AI risk
of AI governance gaps per year
Enterprise AI Adoption Trends
How organizations are deploying AI across functions and industries
Top AI Use Cases in 2025
Top AI Governance Challenges
What's keeping enterprises up at night
Data Privacy & Security
62% of organizations cite this as their #1 concern
- • PII/PHI exposure in prompts
- • Third-party AI provider risks
- • Data residency requirements
Hallucinations & Accuracy
58% struggle with AI reliability
- • Incorrect information generation
- • Lack of confidence scoring
- • Difficulty detecting errors
Regulatory Compliance
51% uncertain about compliance requirements
- • Evolving AI regulations (EU AI Act)
- • Industry-specific requirements
- • Audit readiness gaps
Bias & Fairness
47% concerned about algorithmic bias
- • Discriminatory outcomes
- • Lack of testing frameworks
- • Reputation risk
Cost & ROI Visibility
44% lack visibility into AI spending
- • Unpredictable costs
- • Difficult ROI measurement
- • Budget overruns
Skill Gaps
41% lack AI governance expertise
- • Shortage of skilled staff
- • Complex tool landscape
- • Training requirements
What High Performers Do Differently
Insights from the top 10% of AI-mature organizations
Establish Governance Early
High performers implement governance frameworks before scaling AI, not after. 92% have formal governance policies in place.
Automate Compliance Monitoring
They use automated tools for continuous monitoring, reducing manual effort by 80% while improving coverage.
Invest in Training
Provide comprehensive AI governance training to teams across the organization, not just technical staff.
Partner with Experts
78% of high performers leverage managed services for specialized expertise and 24/7 monitoring capabilities.
AI Adoption by Industry
Maturity and challenges vary significantly across sectors
Financial Services
AI adoption rate
Leading in model risk management and regulatory compliance due to strict oversight.
Top challenge: Balancing innovation with SOX/PCI compliance
Healthcare
AI adoption rate
Growing fast but concerned about PHI protection and clinical accuracy.
Top challenge: HIPAA compliance and patient safety
Insurance
AI adoption rate
Focus on algorithmic fairness in underwriting and claims processing.
Top challenge: Bias testing and state regulations
Get the Full 2025 Report
Download our comprehensive 50-page report with detailed findings, methodology, and actionable recommendations for your organization.
Includes executive summary, industry breakdowns, and governance framework templates