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AI holds the power to transform trade, offering opportunities to enhance efficiency, reduce costs, and empower smaller players in the global market. However, it also introduces complexities and ethical dilemmas. The question remains to be seen: will it bridge gaps, lower barriers, and drive innovation? Or will it create hurdles, deepen inequalities, and exacerbate existing challenges?

The promise of AI reshaping trade and services

When most people imagine AI in a business setting, they picture large tech giants or multinational firms leveraging cutting-edge AI tools to optimise processes and outpace competitors. While larger firms tend to be at the vanguard of the technology’s development, the potential benefits reach smaller businesses as well.

Ganne said, “AI can transform raw data into actionable insights, whether it’s optimising logistics, automating customs and compliance processes, or predicting supply chain disruptions.”

At the state level, countries with limited resources can expand their role in international trade by reducing inefficiencies and cutting costs. This creates opportunities for smaller economies to compete in markets traditionally dominated by larger, wealthier nations.

Ganne said, “AI can reshape countries’ comparative advantages. New competitive advantages could emerge from factors like educated labour, digital connectivity, favourable regulations, or even abundant energy.” Such factors can help them emerge as leaders in this transformative space. The potential for growth and innovation is immense as nations work toward a more connected and equitable global marketplace.

Facing the challenges that come with AI

The technology’s inherent complexity introduces risks, particularly the opacity of its decision-making processes. This “black box” phenomenon of traditional models makes understanding or predicting how AI arrives at its conclusions difficult. Such uncertainty can undermine trust and lead to unintended consequences.

Ganne said, “There is a big challenge to regulate AI and ensure that it is trustworthy, meaning that it meets expectations in terms of reliability, security, privacy, safety, and accountability.”

Ethical concerns also loom large. AI systems are prone to biases that reflect the limitations or prejudices of their training data. These biases can perpetuate stereotypes and create disparities, especially in regions already struggling with inequality. 

This is where regulatory challenges come to the fore, as existing frameworks were designed for human decision-making, not the evolving behaviours of machines. The question of intellectual property further complicates the picture. When AI generates content, who owns it? 

Ganne said, “AI systems rely on vast amounts of data to learn and improve. If that data includes copyrighted material, like books, images, and software code, was permission obtained to use it?”

Balancing innovation with oversight requires a delicate approach. Policymakers must craft regulations that encourage AI’s development while protecting against its potential misuse. Without such balance, the challenges could overshadow the opportunities.

The growing gap between those with AI and those without

While AI opens doors for some, it risks shutting them for others. 

Advanced economies, with their robust digital ecosystems, skilled workforces, and substantial investments in research and development, are able to fully exploit the potential of AI. These countries are not only developing AI but also controlling the data and technology needed to fuel it, consolidating their advantages in trade and economic growth.

Meanwhile, lower-income countries face significant barriers. Without reliable high-speed internet, advanced computing power, or adequately trained professionals, these nations struggle to integrate AI into their economies. This lack of access prevents them from benefiting from the efficiencies and opportunities AI creates, leaving them further behind in the global market.

Ganne said, “The concentration of the AI value chain, with players like NVIDIA, TSMC, or ASML controlling 80% of the market, raises significant concerns about equity and access.”

Moreover, the concentration of AI expertise and resources in a few countries exacerbates this inequality. 

Ganne added, “Only a few players control the rich datasets that actually fuel AI. Without cooperation to address these issues at a global level, the gap between AI haves and have-nots is likely to grow wider.”

This is why targeted and collaborative global efforts to democratise AI are needed.

Why the world needs to work together on AI

The world needs to work together on AI to prevent disparities and inequalities from becoming more pronounced because AI’s potential benefits are immense, but they risk being unequally distributed. 

By collaborating, nations can share knowledge, expertise, and best practices to ensure AI technologies are accessible to all. Unified global standards and regulatory frameworks would help smaller and developing countries adopt AI in ways that align with ethical guidelines, data privacy, and safety measures. 

Trade rules, while technology-neutral, already cover aspects of AI, such as eliminating tariffs on critical components or supporting cross-border services. However, the fragmented approaches taken by individual countries create inefficiencies and inconsistencies.

Ganne said, “What we urgently need is cooperation to promote regulatory convergence.”

By fostering dialogue, sharing best practices, and creating unified standards, nations can avoid the pitfalls of regulatory fragmentation. Equitable access to AI technologies depends on proactive policymaking that prioritises inclusivity and shared progress.

Ganne said, “The WTO, as a global forum for cooperation, dialogue, and exchange of good practices, can play an important role in fostering global convergence.”

By working together, countries can ensure AI serves as a tool for uniting rather than dividing the global trading system.

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AI has the potential to redefine international trade, unlocking new opportunities and transforming the way economies interact. Yet, this transformation is not without its challenges. The hurdles, from ethical dilemmas to growing inequalities, are significant but not insurmountable.

The future of AI in trade depends on how nations and organisations approach these challenges today. Cooperation, inclusivity, and thoughtful regulation will be key to ensuring AI’s promise outweighs its risks. 

Whether AI helps or hinders international trade will ultimately be determined by the choices made now. The opportunity to shape a more connected and equitable global market is within reach, but it demands collective effort and vision.