This is a 44-page report featuring 15 figures and 31 tables. It examines how AI governance is evolving from policies and compliance assessments into an operational control plane for enterprise models, applications, and autonomous agents.
The report’s ten sections move from an executive summary and market definition through an eight-segment solution taxonomy, demand and supply dynamics, and bottom-up market sizing. It forecasts an addressable market growing from $3.6 billion in 2027 to $12.5 billion by 2030, distinguishing stand-alone governance platforms from governance capabilities embedded in security, identity, data, and enterprise software. Its competitive assessment evaluates 36 vendors using the AIMG AI LeaderMap®, followed by scenarios, risks, and implications for buyers, vendors, and investors. A methodology section, glossary, and figure and table index complete the report. All quantitative findings are AIMG estimates.
The report assesses 36 vendors in its AI LeaderMap® and accompanying scorecards:
Platform, security, identity, data, and observability vendors: Amazon Web Services, Cisco, Collibra, CrowdStrike, Databricks, Dataiku, Fiddler AI, Google Cloud, IBM, Microsoft, Netskope, OneTrust, Palantir, Palo Alto Networks, SailPoint, Salesforce, SAP, ServiceNow, and Zscaler.
Independent and specialist vendors: Airia, Cranium AI, Credo AI, Enzai, Harmonic Security, Holistic AI, LatticeFlow AI, ModelOp, Modulos, Monitaur, Relyance AI, Saidot, Singulr, Trustible, Truyo, Velatir, and WitnessAI.
It also tracks 17 adjacent vendors without scoring them: AppViewX, Arize, AuditBoard, Datadog, Drata, Dynatrace, Expert.ai, Fairly AI, FinbotsAI, JFrog, LangSmith, Lasso Security, Okta, SentinelOne (Prompt Security), TrustWise, Varonis, and Veritone.
Readers gain a structured framework for understanding a fragmented market, comparing suppliers, and identifying where spending and competitive advantage may concentrate. For enterprise leaders, it supports procurement and governance planning; for vendors and investors, it clarifies growth opportunities, differentiation, and consolidation prospects. Its central contribution is connecting regulatory compliance with practical runtime enforcement, agent identity, and audit-ready evidence – showing what organizations need beyond a written AI policy.
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