Why Southeast Asia’s next healthtech winners will be built around healthcare workflows, not just AI
Artificial intelligence has become one of the most exciting areas of healthcare innovation. From clinical documentation and diagnostics to patient engagement and remote monitoring, founders are finding new ways to bring AI into almost every part of the healthcare journey. But for healthtech startups in Southeast Asia, having an impressive AI model may not be […] The post Why Southeast Asia’s next…
Hong Kong is prioritizing computing power and stable, clean electricity as it seeks to develop its AI sector. Joseph Law, president of AESIEAP and managing director of CLP Power, made this clear on September 15 to regional utility executives. The city's five-year plan and Chief Executive's 2026 Policy Address both emphasize high-efficiency computing power, stable electricity supply, and a low-carbon transition.
Hong Kong's power system is facing challenges due to the rapid growth of generative AI and data centers, which is increasing electricity demand faster than the average of the past decade and at least two and a half times as fast as energy demand overall. The shift in demand is complex, with factors such as geopolitics, extreme weather, electric vehicles, and AI-driven data centers all contributing.
Utilities now face the task of connecting new loads quickly, operating increasingly complex power systems, and maintaining public confidence during this rapid transformation.
Hong Kong's unique position as a bridge between China and international markets makes it an ideal venue for regional energy dialogue. The city will play the role of a "super connector" and "super value-adder" by deepening collaboration across borders and sectors, improving green standards, and strengthening regional energy cooperation. This broader perspective on the future of energy in Asia is set to be further explored at the upcoming Conference of the Electric Power Supply Industry (CEPSI) 2027.
Written by urgent.news from SCMP Business's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
