The AI TRiSM (AI Trust, Risk and Security Management) technology market is expanding quickly as organisations move from experimental pilots to large‑scale, business‑critical AI systems (Precedence Research, 2025). Recent estimates suggest the global AI TRiSM market is worth around USD 2–3 billion in the mid‑2020s and could grow to roughly USD 7–21 billion by the early‑to‑mid 2030s, reflecting strong double‑digit annual growth (Precedence Research, 2025; Dimension Market Research, 2025; Allied Market Research, 2025). These projections underline a shift from “AI at any cost” to “AI that is safe, fair and compliant,” especially in regulated and impact‑driven sectors such as financial services, ESG analytics and climate‑finance organisations (EY, 2024).

Why the AI TRiSM market is emerging

Gartner defines AI TRiSM as a set of capabilities that safeguard AI ecosystems, covering data privacy, model transparency, robustness, bias management and regulatory compliance (Mindgard, 2025). Three main forces are driving demand for specialised tools and services:

• Regulation and supervisory expectations. Financial regulators and policymakers increasingly expect robust model risk management, explainability and non‑discrimination for AI models, particularly in credit, insurance and risk decisions (Grand View Research, 2024).
• ESG, sustainability and greenwashing concerns. Organisations using AI in ESG and climate‑related analytics must show that their metrics, risk scores and impact estimates are based on defensible, auditable methods (CEUR‑WS, 2024).
• Rapid growth of generative and embedded AI. As generative AI and embedded models appear across business processes, boards and risk teams worry about data leakage, security breaches and uncontrolled “shadow AI” adoption (Šimšek, 2026).

Together, these drivers make AI TRiSM a strategic investment rather than a technical add‑on (Splunk, 2023).

Types of AI TRiSM providers

The market includes both specialised AI TRiSM platforms and broader AI governance and risk tools (Šimšek, 2026).

• Dedicated AI governance / AI TRiSM platforms. Benchmarks highlight solutions such as Asenion, Monitaur, Sigma Red AI, Solas AI and KomplyAi as examples of platforms designed to manage AI risk, bias, compliance and documentation across the AI lifecycle (Šimšek, 2026). Typical capabilities include model inventories, real‑time monitoring, bias testing, explainability dashboards and automated evidence collection for regulators (Šimšek, 2026).
• Vendors recognised in Gartner’s AI TRiSM Market Guide. Concentric AI is named as a representative vendor for information governance in the 2025 Gartner Market Guide for AI Trust, Risk and Security Management, reflecting its focus on data security posture management and protection of sensitive information used by AI systems (Concentric AI, 2025a). Zenity is also recognised as a representative vendor in the same Market Guide and as a Cool Vendor in agentic AI TRiSM, with strengths in securing AI agents and providing AI security posture management and detection/response (Zenity, 2025a). These examples show how vendors specialise in distinct layers of the AI TRiSM stack (Concentric AI, 2025b).
• Model‑risk and lifecycle tools for finance. In financial services, vendors such as ModelOp extend traditional model‑risk practices to machine learning and generative AI, providing workflow, controls and audit trails for models used in lending, fraud detection and risk management (ModelOp, 2024). These platforms often integrate with existing governance, risk and compliance systems to give risk teams a unified view (Persistent Systems, 2025).
• Consulting‑led Responsible AI frameworks. Firms such as EY promote Responsible AI frameworks that embed fairness, transparency, accountability and data privacy into AI‑driven decision‑making (EY, 2024). Rather than a single tool, they offer methodologies, policy design and implementation roadmaps, often combined with technology selection and configuration (Persistent Systems, 2025).

Market offer relevance for Profonanpe’s Sector

For an environmental fund like Profonanpe, which manages international climate and biodiversity finance, the AI TRiSM technology market offers a menu of capabilities for governing any future AI use in project selection, risk analysis or impact reporting (EY, 2024). Understanding features such as bias detection, explainability, lifecycle monitoring and automated compliance, plus the roles of vendors like Concentric AI and Zenity, can help Profonanpe define requirements, align with emerging standards and position itself as a trustworthy steward of climate‑finance resources (GreenFi, 2024).