Flagship annual studies and benchmark reports
Original Clariantix research on the state of enterprise AI governance, risk exposure, and the emerging AI trust economy.
State of Enterprise AI Governance 2026
Artificial intelligence has rapidly evolved from an experimental technology into core enterprise infrastructure. Organizations across every sector are deploying generative AI, machine learning, intelligent automation, and predictive analytics to improve productivity and decision-making. Yet while AI adoption has accelerated dramatically, governance maturity has not kept pace. Many organizations now operate dozens of AI systems with limited visibility, inconsistent ownership, and fragmented oversight — producing an emerging trust gap. This report examines the current state of enterprise AI governance and identifies the foundational capabilities organizations should establish to build trustworthy, transparent, and accountable AI programs.
Enterprise AI Risk Benchmark Study
Enterprise AI introduces a new category of organizational risk. Unlike traditional software, AI systems can evolve, generate unexpected outputs, and influence business decisions in ways that are difficult to predict. Understanding these risks is the first step toward managing them. This benchmark study examines the six major AI risk domains, the persistent threat of shadow AI, third-party accountability gaps, and the practical priorities for risk reduction.
The AI Trust Economy
Trust has always been one of the most valuable business assets. In the age of artificial intelligence, trust becomes even more important. Customers, regulators, employees, and investors increasingly want to know: can this organization be trusted to use AI responsibly? This report explores how AI changes the nature of trust, the five pillars that sustain it, and why trust is becoming the currency of the next digital economy.
The EU AI Act is the world's first comprehensive horizontal AI regulation. It categorizes AI systems by risk (prohibited, high-risk, limited-risk, minimal-risk) and imposes obligations on providers, deployers, importers, and distributors operating in or selling into the EU.
ISO/IEC 42001 is the first international management-system standard for artificial intelligence. It defines requirements for establishing, implementing, maintaining, and continually improving an AI management system (AIMS), with certifiable controls across governance, risk, lifecycle, and operations.
The NIST AI Risk Management Framework is a voluntary, widely adopted framework for managing risks across the AI lifecycle. It is organized around four functions — Govern, Map, Measure, Manage — and is paired with the Generative AI Profile for foundation-model risks.