AI’s global test: Why the Gulf’s workforce strategy offers lessons for Washington

Artificial Intelligence (AI) is no longer a concept confined to Silicon Valley labs; it is the most disruptive economic force since the internet, fundamentally reshaping work across the globe. For policymakers in Washington—currently consumed by the technology’s impact on US domestic labor—the AI transformation underway in the Gulf region offers crucial, and often surprising, lessons in proactive workforce planning.

Globally, projections are stark: AI could automate up to 30% of current jobs over the next two decades, particularly in clerical work, transportation, and manufacturing. This looming disruption fuels legitimate anxiety about job displacement. Yet, focusing solely on jobs lost overlooks the critical pivot required for new jobs gained—roles in technology management, AI oversight, and human-AI collaboration. The question is not if the labor market will change, but how quickly governments adapt their education systems.

While the US debates regulation, Gulf countries—specifically Saudi Arabia and the United Arab Emirates—are not waiting. They recognize that preparing their workforces for the AI future is essential for economic diversification away from oil. Their approach is characterized by aggressive, top-down integration.

Dubai’s AI strategy, for instance, aims to make the city a global AI innovation hub by 2031, integrating AI into transportation, energy, and healthcare systems. Similarly, Saudi Arabia’s Vision 2030 emphasizes technology through massive investment in AI-based education and training programs.

These strategies go beyond building smart infrastructure. They are about creating a national talent pipeline that can operate and govern that infrastructure. This regional focus on proactive national upskilling—rather than reactive safety nets—is where the real lesson for the West lies.

The Gulf’s educational challenge, however, is more complex than simply teaching coding. The AI revolution demands a blend of technical expertise and critical cross-disciplinary skills. In a world where AI drives decision-making in finance or healthcare, understanding how the technology interacts with business processes, ethics, and societal impacts is non-negotiable.

AI systems often inherit biases embedded in historical data, risking the perpetuation of inequality in hiring or lending decisions. Governments and universities in the region are beginning to tackle this head-on, incorporating courses in AI ethics, data stewardship, and human-centered design. The worker trained to identify and correct algorithmic bias will be invaluable. This focus shifts the premium from merely using AI to governing it responsibly.

Real-world applications illustrate the necessity of human-AI collaboration. Consider the Dubai Roads and Transport Authority, which uses AI-powered systems to manage traffic flow. The technology does not replace the human operator; it requires a newly trained professional whose role evolves from routine monitoring to making judgment calls in unusual situations guided by AI insights. Technology, when implemented thoughtfully, enhances human judgment, rather than replacing it.

This principle extends to small and medium-sized enterprises (SMEs). Automation is not just about job displacement; it’s about competitive advantage. Retailers use AI to optimize inventory; logistics firms use it for route efficiency. Workers in these sectors must be upskilled to transition from performing routine tasks to problem-solving and decision-making driven by data.

For the United States, the social equity dimension of this transformation is paramount. If not managed with thoughtful policy, AI could dramatically widen the gap between highly skilled and low-skilled workers. Without targeted interventions—such as subsidized training and accessible apprenticeship programs—automation could disproportionately affect marginalized groups, leaving them behind.

The private sector, both in the US and the Gulf, holds the key. Gulf-based banks, for instance, have implemented internal AI labs where employees rotate through data science, compliance, and human-centered design teams. This model creates a robust, internal talent pipeline that benefits the company’s efficiency while equipping its staff with future-proof skills.

The biggest challenge, globally, is adaptability. Workers, educators, and policymakers must anticipate changes that are often unpredictable. Lifelong learning, flexible curricula, and continuous evaluation of labor market trends are no longer abstract ideas—they are essential tools for economic survival.

The future of work is not predetermined; it is being written today. The Gulf region, through its aggressive investment in AI infrastructure, education, and workforce development, is seeking to lead. By fostering robust human-AI collaboration, prioritizing equitable access to training, and learning from global strategies, societies can ensure that AI serves as a tool for economic empowerment rather than a source of widespread displacement. Washington should pay close attention to this global test case.

Amr mohamed Elghazaly is an opinion writer based in Egypt