The expansion of artificial intelligence regulation across global markets is expected to accelerate demand for AI governance platforms, creating a compliance market valued at $1 billion by 2030, according to research from Gartner. The firm forecasts that fragmented AI regulation will quadruple by the end of the decade, extending to 75% of the world’s economies. As regulatory coverage broadens, organisations are expected to increase investment in AI governance and compliance infrastructure to manage operational and legal risks. Spending on AI data governance is projected to reach $492 million in 2026 and surpass $1 billion by 2030.
Gartner also projects that by 2028, large enterprises will deploy an average of 10 governance, risk management and compliance (GRC) technology solutions, up from eight in 2025. However, the firm indicates that traditional GRC tools may not adequately address the specific risks associated with artificial intelligence systems, including automated decision-making, bias, misuse and oversight of third-party or embedded AI components.
Lauren Kornutick, Director Analyst at Gartner, said that conventional GRC platforms are not designed to manage real-time AI risks or continuous regulatory obligations. “Traditional GRC tools are simply not equipped to handle the unique risks of AI, from real-time decision automation to the threat of bias and misuse,” she said. “This gap is fuelling surging demand for specialised AI governance platforms, which provide centralised oversight, risk management, and continuous compliance across all AI assets including third-party and embedded systems.”
A Gartner survey of 360 organisations conducted in the second quarter of 2025 found that companies deploying AI governance platforms were 3.4 times more likely to report high effectiveness in AI governance compared with those that had not adopted such systems.
The regulatory landscape is expected to become increasingly complex. Kornutick said organisations must demonstrate ongoing compliance rather than relying on periodic audits. “Organisations must be able to demonstrate compliance not just at a single point in time, for a single obligation, but continuously as AI systems and regulations governing them operate and evolve,” she said.
AI governance platforms are designed to enable automated policy enforcement at runtime, monitor AI systems for compliance, detect anomalies and prevent misuse. According to Gartner, these capabilities are becoming critical as AI systems increasingly operate autonomously and interact with sensitive data.
As organisations evaluate adoption strategies, Gartner advises reassessing existing governance and compliance processes, identifying capability gaps and clarifying roles across assurance teams. Interoperability with existing technology stacks is considered essential to enable scalable oversight across enterprise systems.
The market for AI governance platforms is also expected to consolidate as buyer requirements become clearer. While consolidation could provide financial stability and broader product portfolios, Gartner notes that it may also affect innovation and product differentiation. Organisations are advised to assess vendor strategies and product roadmaps in a market characterised by evolving risks and technological change.
Vendor selection decisions may involve trade-offs between established providers, which may offer integration with legacy systems and financial stability, and startups that may deliver more specialised capabilities but carry potential risks related to acquisition or product continuity. Some organisations may also weigh investment in dedicated governance platforms against extending existing business intelligence systems to monitor AI-related risks.
Gartner identifies several features as central to effective AI governance platforms. These include a centralised inventory of AI assets across the lifecycle, advanced risk management and regulatory compliance capabilities, and support for frameworks such as the EU AI Act, the National Institute of Standards and Technology AI Risk Management Framework and ISO 42001.
The EU AI Act, the National Institute of Standards and Technology AI Risk Management Framework and ISO 42001 establish compliance requirements that organisations may need to integrate into governance systems. Gartner states that platforms should also provide data usage mapping and evidence collection tools to support regulatory audits.
The firm projects that effective governance technologies could reduce regulatory expenses by 20%, potentially allowing organisations to redirect resources toward innovation and growth. To remain adaptable, organisations are encouraged to prioritise platforms that support emerging use cases such as multisystem AI agents, third-party risk management and measurement of AI business value.
