New report reveals how emerging markets could hold ‘structural advantage’ in AI governance

New study highlights how countries without legacy tech burdens are building modern AI governance frameworks from scratch – with implications for UK competitiveness and trade

As the UK tries to position itself as a global AI leader, a new report from SAS and the Global Center on AI Governance suggests that some of the most agile and forward-looking AI governance models may not emerge from established tech economies, but from countries starting with a clean slate.

The report argues that many nations across Africa, Latin America and parts of Asia may hold a structural advantage in governance design for ethical and responsible AI.

Without decades of legacy digital infrastructure, fragmented regulatory overlays and retrofitted compliance mechanisms, the report suggests that many of these countries are beginning to design AI governance frameworks from the ground up – embedding sustainability, inclusion and data sovereignty into systems at the outset.

In contrast, mature economies such as the UK face the complex task of adapting legacy technology and layered regulatory systems to fast-moving AI innovation.

The report notes that AI could contribute up to $15.7 trillion to the global economy by 2030, although current projections suggest this value will not be evenly distributed. For example, Latin America is expected to capture around 3% of this potential, while Africa and other parts of the Global South may capture approximately 8%.

The research also points to the scale of the global connectivity challenge, with over 2.5 billion people still offline, the majority located in emerging economies, reinforcing the need for accessible digital infrastructure and digital literacy programmes.

Dr. Josefin Rosén, Principal Trustworthy AI Specialist at SAS, said: “Later adoption does not mean being behind.

“In many cases, it means having the freedom to design governance models that are coherent, sustainable and aligned with local priorities from day one. Countries without legacy systems can avoid some of the coordination and integration challenges faced by mature digital economies - we have seen this in other forms of technology in recent decades.”

Skipping ‘bad AI’

The shift echoes how several regions bypassed landline infrastructure and moved straight to mobile technology. In the AI era, emerging markets are in a position to bypass poorly governed, energy-intensive or siloed AI deployments and instead implement modern, accountable systems from inception.

The report highlights how governments in parts of the Global South are advancing clearer data sovereignty frameworks, prioritising local-language AI models, and investing in AI literacy and digital skills to support inclusive adoption.

For example, initiatives such as India’s AI for All strategy, which introduces AI fundamentals into school curricula, is designed to embed skills development alongside technological deployment. Similarly, Rwanda’s Digital Ambassadors Programme helps extend digital and AI capabilities to remote communities.

Rather than retrofitting governance around deployed technologies, these approaches integrate policy, infrastructure and skills development from the outset.

Despite these opportunities, the report acknowledges that countries across the Global South continue to face significant barriers, including infrastructure gaps, limited compute capacity and the outward migration of skilled AI professionals.

The shortage of local research funding and competitive career pathways has contributed to talent flight in some regions, creating a “brain circulation” challenge that policymakers are working to address.

This structural advantage also extends to sustainability. With AI systems consuming significant energy globally, countries investing now have the opportunity to align AI expansion with renewable energy strategies and decentralised infrastructure, with the opportunity to avoid carbon-intensive pathways taken by early adopters.

Implications for the UK

For the UK, the findings raise important strategic questions. While Britain continues to refine its AI regulatory framework and industrial strategy, businesses may increasingly encounter governance regimes abroad that may be more streamlined and sovereign-focused in certain markets.

As UK firms expand supply chains and commercial relationships in markets such as India and across Africa, understanding emerging data sovereignty laws and cross-border governance expectations will become essential. Compliance changes will not flow in one direction.

Rachel Adams, CEO of the Global Center on AI Governance, said: “This is not a story about assistance or catching up. It is about recognising where innovation in governance is happening and understanding that leadership in AI will not be defined solely by early adoption, but by the quality, coherence and trustworthiness of the systems we build.”

The report calls on policymakers and business leaders in mature AI markets to reassess assumptions of automatic leadership. Simplifying governance structures, improving data stewardship and embedding trust and sustainability into AI strategy will be critical to maintaining both competitiveness and collaboration across markets.

Without reform, established economies risk being constrained by legacy complexity, while more agile markets set new standards for trustworthy AI. Read the report here.

About the report

Constraint to Capability: Flipping the Narrative on AI in the Global South was published in December 2025 and is a collaboration between SAS Institute and the Global Center on AI Governance. The report provides a strategic roadmap for how countries in the Global South can take a stronger role in the global AI economy through investments in skills, infrastructure and inclusive governance. It contains examples and recommendations in areas such as health, education and data management – with a focus on AI that reflects local needs and values. Read the report here.