TLDR: A recent 2025 AI Governance Survey by Pacific AI reveals significant global challenges in the deployment and responsible scaling of artificial intelligence applications. The report identifies critical gaps in organizations’ operational readiness, particularly concerning production deployment, governance maturity, regulatory awareness, and incident response, driven largely by the pressure for rapid market entry.
A comprehensive 2025 AI Governance Survey, conducted by Gradient Flow for Pacific AI in April and May of this year, has brought to light a growing disparity between the ambitious goals for AI adoption and the practical capabilities of organizations to deploy and govern these systems responsibly. The findings, announced on June 17, 2025, underscore that while AI is becoming foundational for modern business, the pace of innovation is often outstripping the ability to ensure safe and responsible scaling.
The survey highlights several key ‘Production Reality Gaps,’ indicating that only 30% of organizations have successfully deployed generative AI systems into production environments, with a mere 13% managing multiple deployments. Large enterprises demonstrate a significantly higher rate of multiple deployments, being five times more likely than smaller firms to have such systems running. Despite this, technical leaders are pushing for aggressive adoption, with 48% targeting 3-5 new use cases, compared to 25% for other roles.
Small companies, in particular, exhibit ‘Small Company Vulnerability,’ consistently lagging in governance maturity. Only 36% of small firms have dedicated governance officers, starkly contrasting with 62-64% in larger organizations. Similarly, just 41% of small companies provide annual AI training, compared to 59-79% in larger counterparts. This gap extends to ‘Regulatory Awareness Deficits,’ where small companies report only 14% familiarity with major AI standards like NIST AI RMF, exposing them to considerable compliance risks.
Furthermore, the report points to ‘Immature Incident Response’ capabilities across the board, with many organizations lacking specific protocols for AI-specific failure modes such as prompt injection attacks or biased outputs. This suggests a reliance on traditional IT playbooks that are insufficient for the unique risks posed by AI.
The primary barrier to effective AI governance, cited by nearly half (45%) of all respondents and 56% of technical leaders, is the intense pressure to achieve speed-to-market. This often leads to shortcuts that compromise safety and responsible practices. While 75% of respondents reported having AI usage policies, only 59% have dedicated governance roles, and just 54% maintain incident response playbooks for AI-specific risks. Less than half (48%) of organizations are actively monitoring their AI systems for accuracy, misuse, or drift, with these numbers dropping drastically in smaller firms.
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David Talby, CEO of Pacific AI, emphasized the gravity of these findings, stating, ‘This survey exposes a growing disconnect between AI policy and practice. Organizations that don’t address it are playing with fire and they know it. Without responsible AI practices baked into the entire AI development lifecycle, developers and thereby the organizations they work for are escalating legal, financial, and reputational risks.’ To assist organizations, Pacific AI offers a free AI Policy Suite, including a recently updated AI Incident Reporting Policy, designed to help companies comply with evolving regulations across the US.
