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As energy risks rise, learn how next-gen AI tools can help Asian manufacturers boost productivity, improve efficiency, and sustain industrial leadership.
Smarter energy solutions: Powering Asia’s energy security and manufacturing edge
Asia has long been the world’s manufacturing engine, but its competitive edge is increasingly threatened by a new reality – energy security. Geopolitical conflicts, supply chain disruptions and volatility in global energy markets have reinforced the risks of relying on imported fossil fuels. For many countries across the region, energy security has become a strategic priority alongside economic growth.
Figure 1 – Asia’s economies are more dependent on imported energy supplies
At the same time, industry remains the world’s largest energy-consuming sector, accounting for nearly 40% of global final energy demand1 and around two-thirds of new growth in energy demand since 2019.2 Improving industrial energy efficiency is therefore becoming one of the most effective ways to strengthen competitiveness while reducing exposure to external energy shocks.
Physical AI – an energy solution
This is where physical AI could play an increasingly important role. Physical AI enables mere mortals to see AI’s productivity in action. It’s a catch-all phrase for the many underlying systems that enable machines to perceive, analyse and act in the real world. By combining sensors, connectivity and AI models, it allows industrial systems to optimise processes autonomously, reducing waste, improving uptime and enhancing productivity across manufacturing operations. More importantly, physical AI innovation can achieve these gains while using less energy, improving output with fewer inputs.
Asia companies powering ahead
Asian industrial leaders are already helping to advance this transition. Japan’s Hitachi is building AI-enabled industrial solutions using digital twins and physical AI models that improve energy and process efficiency across manufacturing, energy and infrastructure.3 Taiwan’s Foxconn and Korea’s SK Hynix are deploying AI-enabled digital twins across their factory networks to simulate production processes, train robots and improve operational resilience.4,5
The opportunity is particularly significant in factory robotics where Asia is a clear leader. China is the world’s largest market for industrial robots, while Japanese automation leaders such as FANUC remain central to global factory automation ecosystems. Next-gen robots offer substantial productivity gains, but they also present a growing energy challenge. They rely on motors, drives, gearboxes and actuators that consume significant amounts of electricity. Across the millions of industrial robots already operating worldwide (and those yet to be deployed), incremental efficiency improvements can translate into meaningful energy savings.
AI is already demonstrating measurable results. Using digital twins linked to FANUC industrial robots, engineers achieved a 74.8% reduction in energy consumption during pick-and-place operations through AI-driven optimisation.6 Given these rapid advances, future manufacturing competitiveness may depend on smarter, more energy-efficient robots.
A broad investment set
The AI opportunity extends well beyond chips. To maintain its competitive lead, Asia’s manufacturing leaders need smarter, more energy-efficient equipment and processes. This aligns closely with Smart Energy’s investment thesis, which targets smart grids, electrification, automation, robotics, and power-management technologies that improve productivity, competitiveness and energy efficiency of not just manufacturing but the entire economy.
All companies referenced in this article are for illustrative purposes only in order to demonstrate the investment strategy on the date stated. The companies are not necessarily held by the strategy nor is future inclusion guaranteed. This is not a buy, sell or hold recommendation, nor should any inference be made on the future development of these companies.
1 IEA website, “Industry — Energy Efficiency 2025.
2 IEA, Energy Efficiency Market Report, November 2025. Total final consumption in 2024 was over 450 EJ and has grown by around 25 EJ since 2019. Industry accounts for the largest share of this demand, at nearly 40%. Industry saw the strongest growth since 2019, contributing two-thirds of the total increase in global energy demand.
3 Robeco company research; Hitachi management disclosures. AI agent diagnostics deployed across industrial equipment and power networks.
5 https://www.koreaittimes.com/news/articleView.html?idxno=154166
6 Springer Nature, “Digital Twin-Based Self-Learning Decision-Making Framework for Industrial Robots,” IJAMT, June 2025. FANUC ER-4iA pick-and-place: 74.79% energy reduction via Bayesian optimization.
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Important information. Marketing communication for professional investors only. Capital at risk.
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This is a sponsored advertorial from Robeco.