The global AI governance market is rapidly expanding, projected to grow from USD 310.4 million in 2025 to approximately USD 6.93 billion by 2035, driven by the need for ethical and compliant AI deployment. AI governance frameworks are essential for managing risks related to bias, data misuse, and regulatory non-compliance across various industries.
AI regulation is becoming a critical issue for quality assurance (QA) in banking, as financial institutions struggle to align modern AI systems with regulatory expectations. This challenge is compounded by the increasing complexity and risk associated with AI technologies, requiring QA teams to play a central role in governance and accountability.
As governments worldwide implement comprehensive AI regulations, companies must prioritize embedding governance, risk assessment, and transparency into their AI systems to avoid costly penalties and reputational damage. Early action positions them as responsible innovators in an increasingly regulated landscape.
California and New York have enacted laws to ensure the safe deployment of large frontier AI models. The California Transparency in Frontier Artificial Intelligence Act (TFAIA) and New York’s Responsible AI Safety and Education Act (RAISE Act) require developers to publish safety protocols and report critical incidents, aiming to mitigate catastrophic risks associated with these powerful technologies.
On February 9, 2026, Paris will host a major conference on artificial intelligence governance at the Collège de France titled “AI in Paris, One Year After the Summit: Building the Future.” Organized by PSL University and other institutions, the event will feature distinguished speakers discussing France’s research capabilities and the regulatory challenges facing AI today.
On February 8, 1996, the Declaration of the Independence of Cyberspace and the US Communications Decency Act marked a foundational moment for digital and AI governance, establishing a narrative that technology should operate outside political and legal frameworks. This has led to a dangerous lack of accountability, particularly in AI, where companies can cause harm without legal repercussions.
The EX360-AIRR framework provides a structured approach to managing AI-specific risks such as algorithmic bias and security vulnerabilities within enterprise operations. By centralizing risk identification, scoring, and mitigation, it ensures responsible AI adoption and compliance oversight.
India is leveraging AI to democratize financial access, enabling previously excluded groups such as gig workers and micro-entrepreneurs to secure credit through innovative algorithms based on real economic activity rather than traditional documentation. The upcoming India AI Impact Summit in February 2026 will highlight how ethical AI can drive large-scale financial inclusion.
Ahead of the AI Summit in Delhi, industry leaders emphasize the need to balance rapid AI deployment with strong ethical guidelines, stressing transparency, accountability, and human oversight as essential for responsible AI adoption.
India is poised to balance rapid AI advancement with ethical considerations as it prepares for its largest AI summit, emphasizing transparency, accountability, and talent development across sectors.
