The artificial intelligence competition is by nature an energy competition. The conventional narrative focuses on faster chips, yet training and inference consume vast amounts of power. The harsh geographic paradox is that the regions most advanced in artificial intelligence (AI) often face the most acute power constraints.

Hong Kong has emerged as a premier global AI hub. According to the Global AI Competitiveness Index, the city ranks third globally as an AI financial powerhouse. The chief executive’s 2025 policy address further underscored this momentum, highlighting Hong Kong’s world-class research, talent and capital.

But a critical blind spot remains: the energy-compute nexus. Hong Kong’s electricity balance has been in deficit since 1994 with annual shortfalls in recent years of over 1,500 kilowatt-hours per capita, necessitating imports including from the Daya Bay nuclear power station. While the government promotes AI industrialisation, it has yet to fully integrate energy-aware planning into its strategy.

Initiatives such as the AI Supercomputing Centre in Cyberport and the 10-hectare Sandy Ridge data facility cluster under construction reflect a massive commitment to compute capacity. Yet these projects prioritise technical throughput without corresponding long-term energy infrastructure planning, highlighting a mismatch between digital ambition and power supply resilience.

Hong Kong can leverage the Greater Bay Area as its hinterland. Instead of attempting to house all its data centre demand locally – which places unsustainable pressure on its ageing power grid – Hong Kong should act as the high-value brains of the Greater Bay Area. By serving as a gateway coordinator, the city can channel capital and talent into compute infrastructure located in cities like Huizhou or Jiangmen, where energy capacity is more abundant.

By specialising in high-value, low-energy segments – such as financial AI and regulatory technology – Hong Kong can solidify its position in the global AI hierarchy. Its legal prowess offers a unique opportunity to shape AI governance, bridging global regulatory divides.