Spending on artificial intelligence (AI) governance platforms is set to exceed $1 billion by 2030 as governments expand regulation and organizations move to control mounting AI risk, according to research firm Gartner.
The firm projects that by 2030, fragmented AI regulation will quadruple and extend to 75% of the world’s economies, driving $1 billion in total compliance spending. Outlays on AI governance platforms are expected to reach $492 million in 2026 and surpass $1 billion by the end of the decade.
“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,” said Lauren Kornutick, director analyst at Gartner. “This gap is fueling surging demand for specialized AI governance platforms, which provide centralized oversight, risk management, and continuous compliance across all AI assets including third-party and embedded systems.”
Gartner forecasts that by 2028, large enterprises will deploy an average of 10 GRC technology solutions, up from eight in 2025. But Kornutick said adding more conventional tools will not address the fast-changing regulatory environment or the operational risks tied to autonomous systems.
A Gartner survey of 360 organizations conducted in the second quarter of 2025 found that organizations deploying AI governance platforms were 3.4 times more likely to achieve high effectiveness in AI governance than those that did not.
“AI governance platforms help organizations stay compliant by enabling automated policy enforcement at runtime, monitoring AI systems for compliance, detecting anomalies, and preventing misuse,” Kornutick said. “Point-in-time audits are simply not enough.”
She added that as AI systems increasingly make autonomous decisions and interact with sensitive data, continuous monitoring becomes critical for responsible and ethical use.
Kornutick said organizations must take a strategic approach when adopting AI governance platforms, weighing business value against legal and reputational risk.
“Balancing the risks and benefits of AI governance platform adoption requires a strategic and flexible approach,” she said. “This balance depends on weighing the clear benefits, such as value provided to the business, as well as against risks that are unlawful or are potentially harmful to the business’ reputation resulting from AI use.”
She advised enterprises to reassess existing governance processes, identify gaps, and clarify roles and responsibilities before selecting a platform. Interoperability with existing technology stacks is also essential to ensure scalable oversight.
Market consolidation is expected as buyer requirements mature. While consolidation may strengthen vendors financially and expand feature sets, Kornutick cautioned that it could also limit innovation or reduce alignment with end-user needs.
To remain adaptable, organizations should prioritize platforms with centralized AI inventories, advanced risk management capabilities, and support for emerging regulatory frameworks such as the EU AI Act, the AI Risk Management Framework from the National Institute of Standards and Technology, and ISO 42001.
Data usage mapping and evidence collection tools are also becoming critical as regulators demand audit-ready documentation.
“As compliance costs rise, Gartner projects that effective governance technologies could reduce regulatory expenses by 20%, freeing up resources for innovation and growth,” Kornutick said.
She added that enterprises should also consider support for multisystem AI agents, third-party risk management, and tools that measure AI’s business value, ensuring governance investments remain effective as regulations and technologies evolve.