DELRAY BEACH, Fla., Sept. 25, 2026 /PRNewswire/ -- According to MarketsandMarkets™, the Shadow AI Risk & Governance Market is projected to grow from USD 1.39 billion in 2026 to USD 8.64 billion by 2032 at a CAGR of 35.6% during the forecast period.

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Shadow AI Risk & Governance Market Size & Forecast:

- Market Size Available for Years: 2025–2032

- 2025 Market Size: USD 1.02 billion

- 2026 Market Size: USD 1.39 billion

- 2032 Projected Market Size: USD 8.64 billion

- CAGR (2026–2032): 35.6%

Shadow AI Risk & Governance Market Trends & Insights:

- A key growth driver is the rapid spread of AI tools beyond centrally managed enterprise environments.

- By offering, the solutions segment is estimated to dominate the market in 2026.

- By solution type, AI access & agent governance is set to grow at the fastest rate, registering a CAGR of 47.2%.

- By deployment mode, the cloud segment is projected to grow at a rapid pace, at the highest CAGR of 36.7%.

- North America is estimated to account for the highest share of 44.0% of the Shadow AI Risk & Governance Market in 2026.

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Organizations are placing greater emphasis on documenting how AI applications are assessed, approved, monitored, and controlled, creating demand for technologies that can generate traceable evidence of governance activities. AI governance programs increasingly require records of risk assessments, policy decisions, control implementation, approvals, and monitoring outcomes rather than relying solely on written policies. This is creating demand for platforms that automate evidence collection, maintain audit trails, and provide centralized documentation across AI applications and governance processes. Recent industry research also indicates that organizations are moving toward more operationalized AI governance, increasing the need to connect governance activities with demonstrable controls and evidence.

Based on solution type, the AI data protection & security segment is expected to hold the largest market during the forecast period.

The AI data protection & security controls segment is supported by the need to secure sensitive enterprise information accessed and processed through AI applications. Organizations are deploying capabilities to identify sensitive data, monitor AI-related data flows, control information access, prevent unauthorized disclosure, and enforce data handling policies. Integration of AI applications with corporate databases, documents, SaaS platforms, and other enterprise repositories is increasing the need for stronger controls that protect confidential information while enabling legitimate AI use. Integration with existing data security and enterprise security infrastructure is also supporting adoption of these capabilities.

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By organization size, the SMEs segment is expected to register the highest CAGR during the forecast period.

The SMEs segment is supported by the growing availability of cloud-based and modular AI governance technologies that require limited infrastructure and internal resources. Smaller organizations are adopting AI across functions such as customer service, marketing, software development, finance, and operations, creating requirements for practical controls around AI usage. Solutions that automate AI risk assessment, policy management, usage monitoring, compliance documentation, and security enforcement are helping organizations address these requirements with smaller technology and governance teams. Subscription-based platforms and integrated solutions are further lowering implementation complexity and enabling SMEs to expand governance capabilities as their use of AI increases.

By region, North America is estimated to account for the largest market share during the forecast period.

North America is expected to account for the largest share of the Shadow AI Risk & Governance Market, supported by its established cybersecurity ecosystem, concentration of AI technology providers, and continued development of practical frameworks for managing AI-related risks. In the US, NIST is expanding its AI risk-management work through updates to the AI Risk Management Framework, AI standards initiatives, and security-focused guidance covering generative AI and AI agent systems. NIST is also developing a Trustworthy AI in Critical Infrastructure Profile to provide sector-specific risk-management practices for organizations deploying AI-enabled capabilities. In Canada, government initiatives are advancing responsible AI through the national AI strategy, AI transparency measures, privacy modernization, and guidance for the responsible use of generative and agentic AI. These developments, alongside the presence of established cybersecurity and AI governance providers, are supporting demand for AI discovery, data protection, policy management, risk assessment, and access controls across enterprises in the region.

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Top Companies in Shadow AI Risk & Governance Market:

The Top Companies in Shadow AI Risk & Governance Market are Palo Alto Networks (US), Microsoft (US), Zscaler (US), Netskope (US), Cisco (US), IBM (US), ServiceNow (US), OneTrust (US), Forcepoint (US), Proofpoint (US), Credo AI (US), Holistic AI (UK), Mindgard (US), Cranium AI (US), NeuralTrust (Spain), ModelOp (US), Monitaur (US), Saidot (Finland), Relyance AI (US), Truyo (US), Airia (US), Trustible (US), HiddenLayer (US), Check Point (Israel), AI Shadow (US), Zenity (US), Noma Security (Israel), and Harmonic Security (US).

Shadow AI Risk & Governance Market - Investment & funding +Merger & Acquisition

Investment Funding Context

The Shadow AI Risk & Governance Market is attracting investment as vendors expand capabilities across AI discovery, governance, data protection, risk management, and agent security. Zenity raised USD 125 million in Series C funding in August 2026, bringing its total funding to approximately USD 185 million, to accelerate its AI agent security platform and global expansion. Airia secured USD 100 million in funding in September 2025 to expand its AI governance, security, and orchestration capabilities for enterprises. ModelOp raised USD 10 million in Series B funding in August 2024 to expand its AI governance software, portfolio intelligence, and automated governance capabilities. These investments indicate increasing investor interest in specialized platforms addressing AI visibility, governance, security, and control requirements.

Revenue Shift Context

The Shadow AI Risk & Governance Market is evolving toward integrated platforms that bring multiple control functions together across enterprise AI environments. Spending is expanding beyond basic AI discovery toward governance and policy management, data protection and security controls, risk and compliance management, and AI access and agent governance. Solutions remain the primary offering, while services are gaining importance as organizations require support for implementation, integration, risk assessments, policy development, testing, assurance, and managed governance. This shift is creating opportunities for vendors that can combine multiple governance and security capabilities within a unified enterprise architecture.

Mergers and Acquisitions

Mergers and acquisitions in the Shadow AI Risk & Governance Market are increasingly focused on adding AI security, identity, access management, asset visibility, and governance capabilities to broader enterprise technology portfolios. Recent transactions involving Palo Alto Networks, ServiceNow, and Armis reflect growing consolidation as established technology and cybersecurity providers expand their capabilities across AI applications, data, identities, and connected assets. These developments are contributing to the integration of AI governance with broader security and risk-management platforms.

SHADOW AI RISK & GOVERNANCE MARKET: MERGERS AND ACQUISITIONS, JANUARY 2024–SEPTEMBER 2026

Company Revenue Share Details

The Shadow AI Risk & Governance Market remains highly fragmented, with the top five players collectively accounting for approximately 13.8% of total market revenue. The competitive landscape includes diversified technology and cybersecurity providers such as Cisco, Microsoft, Zscaler, Palo Alto Networks, ServiceNow, and IBM, alongside specialized vendors such as Tuya, Airia, Mindgard, NeuralTrust, Credo AI, ModelOp, and Zenity. Established providers are extending their broader security, data, identity, and enterprise technology platforms to address AI governance requirements, while specialized vendors focus on AI discovery, governance, data protection, risk assessment, AI security, and agent controls. The remaining market is distributed across numerous emerging and specialized providers, reflecting the fragmented nature of the market and the coexistence of diversified technology companies, cybersecurity platforms, and dedicated AI governance and security vendors.