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Artificial intelligence (AI) is advancing so quickly that it's poised to fundamentally transform the structure of businesses and industries. It will introduce entirely new methods of operating, creating, and innovating — all at a scale and speed never seen before. With its transformative power comes responsibility: the role of AI governance.
Governance refers to the frameworks, policies, and practices that ensure AI systems are developed and deployed ethically, transparently, and in alignment with values. Effective governance is not just about mitigating risks — it is about building trust, fostering innovation responsibly, and ensuring that AI serves the public good while minimizing unintended harm.
One of the key trends for 2026 will be governance. With the light-speed acceleration of AI development, there is a degree of volatility.
Artificial intelligence (AI) is advancing so quickly that it's poised to fundamentally transform the structure of businesses and industries. It will introduce entirely new methods of operating, creating, and innovating — all at a scale and speed never seen before. With its transformative power comes responsibility: the role of AI governance.
Governance refers to the frameworks, policies, and practices that ensure AI systems are developed and deployed ethically, transparently, and in alignment with values. Effective governance is not just about mitigating risks — it is about building trust, fostering innovation responsibly, and ensuring that AI serves the public good while minimizing unintended harm.
One of the key trends for 2026 will be governance. With the light-speed acceleration of AI development, there is a degree of volatility.
Roese emphasized that the number one complexity of moving fast and moving forward is to establish a governance structure, a set of rules that people understand how they can follow, a way to prioritize what is important.
At national levels, the rapid rise of sovereign AI ecosystems will continue as AI becomes critical to state-level interests. In many countries, enterprises are also actively building their own frameworks to drive local innovation, with strong foundations already in place.
Sovereign AI is creating a new stream of the AI economy and ecosystem, driving economic transformation. Roese echoed that the forecast of the sovereign AI industry is to be much bigger than what many anticipate today, as all efforts will need infrastructure as a foundational capability.
By working with experts, government, and industry peers, the sector is bridging the gap and moving towards a collaborative ecosystem. The collaborations have made unbelievable headway in fostering skill development and advancing collective expertise. Leading organizations centralize AI governance, formalize enterprise-wide oversight, and empower dedicated Chief AI Officers (CAIOs) to own risk and align innovation.
However, global AI governance faces significant challenges, including regulatory fragmentation, issues of bias and accountability, power concentration among a few nations and tech giants, and a digital divide between developed and developing countries. The rapid rise of AI has raised global concerns over misuse, inequality, and ethical risks.
The UN has stressed the urgent need for a unified global framework to prevent regulatory gaps and ensure responsible AI development. According to a 2024 UN report examining the state of international AI governance, the landscape consisted of fragmented, siloed solutions that primarily serve developed economies while leaving the majority of nations without representation in frameworks shaping how AI technologies get regulated, deployed, and controlled.
This article was originally published by the 
