A quiet transformation is underway in the cleantech world. Artificial intelligence is here to stay, and it’s remodeling the very foundation of innovation, reshaping how breakthroughs are conceived, developed, and scaled.

At Cleantech Group, we’ve been closely tracking, for more than two years now, the accelerating impact of advanced AI across the sectors we cover. Three clear themes have emerged:

• AI is more than software. It’s becoming an enabling layer across the entire hardware value chain—often in places few expect.
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• AI in the innovation process is still underutilized. Those who act now stand to gain real strategic advantage.
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• LLMs are raising the bar. The rapid evolution of large language models is creating new competitive pressures. Soon, embedding AI in your innovation process won’t be a differentiator—it’ll be the baseline.

We wanted to know how and who in the cleantech world are seeing and experiencing.

We have contributions this quarter from South Korea, China, and three Singapore-based investors, whose interests and perspectives are pan-regional. Our guest contributors were reacting to the open question:

Will AI become an enabling force for cleantech in Asia, and if so, how and where? Should investors rethink their capital allocations between “hard” cleantech (infrastructure, materials) and “soft” cleantech (software, data, and AI)?

AI can’t drive cleantech without the infrastructure to move.

South Korea’s new administration is betting on AI—not just as a productivity tool, but as a national growth engine. It’s investing in hyperscale data centers, custom semiconductors, and massive computer infrastructure. However, with rising electricity demand, the climate impact of this AI buildout is uncertain.

This is where cleantech infrastructure matters. In Asia, where grids are fragmented and cooling loads are rising fast, AI alone cannot decarbonize systems. Smarter cooling, grid flexibility, thermal storage, and sustainable power distribution must evolve in parallel. AI is the brain—but without the body, it’s just potential.

As cleantech investors, we view this moment as a strategic inflection point. AI is not an abstract technology layer anymore. It will deeply shape energy systems—and how they must evolve. Infrastructure is no longer background. It’s the enabling stage for the entire show.

Cleantech Group Take:

This provides a good example of how the rise of AI will stimulate other forms of innovation activity. Indeed, as Max says, AI cannot decarbonize the data center alone. Achieving that requires new carbon-free baseload energy inputs, stimulating areas like geothermal and advanced nuclear. It also demands new cooling solutions, the emergence of new concepts such as low-carbon AI hosting, and a search for materials innovation, be that related to heat or improving the power efficiency of semiconductors, for example.

AI is rapidly emerging as a critical enabler for Asia’s cleantech transformation, with investment momentum suggesting a fundamental shift in how we approach decarbonization technology.

There is increasing interest from the corporate world across APAC to implement AI into their operations, not only to advance new projects, but to maintain competitiveness within their existing business lines. For example, in a recent report by ABI Research, over 50% of manufacturers in Malaysia now view AI as essential for new ventures, with areas such as robotics garnering particular attention.

In a region like Southeast Asia, where there is a growing need for physical infrastructure to drive the energy transition, AI will serve to supercharge physical assets for competitive advantage. As such, cleantech investments should not diverge into an “either/or” situation when it comes to software versus hardware—the winning strategy will combine both.

Cleantech Group Take:

And, as alluded to, a winning strategy will also involve the combination of AI and Robotics. As per Cleantech Group’s ultimate guide to AI in cleantech, we believe that these ever-improving technologies will offer industrial efficiency in the Asia Pacific region the opportunity for significant productivity gains. This is especially true in Asia because, as we all know, Asia is the motor of the world’s manufacturing and heavy industry economy.

AI is set to emerge as a key enabler of cleantech in Asia, with early signs of adoption across sectors such as renewable energy, smart grids, sustainable agriculture, and waste management. While there are promising pilot projects and initial deployments—particularly in markets like China, India, and Singapore—AI’s integration into cleantech remains at a nascent stage and is not yet mainstream.

What we’re seeing on the ground though is AI being applied in more targeted, practical ways—such as accelerating material discovery, shortening battery development cycles, and optimizing operational performance. Within our own portfolio, examples include AI-powered robots for fertilizer and input application, an analytics platform that improves vehicle performance using AI, AI-powered imaging optimization in renewable energy applications, and AI solutions for more efficient data centers. These hybrid models are beginning to redefine what is possible in emerging markets.

At ADB Ventures, we are supporting a newer generation of early-stage companies that are developing advanced, integrated solutions, enhanced by AI. We believe, as investors in Asian markets, it’s not a choice between “hard” and “soft” cleantech, but rather that true value lies in integration of AI with the physical foundations of the clean economy. It’s not without its fair share of challenges, though. There are cost implications, increased demands on energy consumption and limited availability of skilled talent.  

Unlocking AI’s full potential will require targeted investment, better data infrastructure, and supportive policy environments. As the cleantech ecosystem continues to evolve, the focus must remain on real-world applications—where AI serves as a powerful tool to amplify climate impact, not as an end in itself.

Cleantech Group Take:

We absolutely agree with the notion that AI and its impact across the cleantech theme is at an embryonic stage. Still, too much of the hype and attention is on AI itself and its thirst for power.

Not to deny that this matters a lot, but it distracts from focusing more attention on AI’s applications and how they could accelerate the development of cleaner, more efficient solutions. That is where the big upside for cleantech and emissions lies.

The notion of power-hungry AI enabling cleantech reminds me of the story of Baron Munchausen pulling himself out of a swamp by his own hair. Current evidence paints a rather grim picture, given the rapid expansion of energy-intensive data centers that largely depend on fossil fuels, consequently increasing carbon emissions. Despite this, there is genuine promise in AI’s potential.

With intermittent and distributed renewable generation, grid management and balancing supply and demand have become exceedingly complex. Efficiently addressing this complexity demands advanced tools, with AI emerging as a critical component.

However, between software and hardware investments, we emphasize investing in hardware—especially intelligent, responsive hardware—in Southeast Asia. The basis for intelligent control is simply not there yet.

Singapore’s SP Group is leading the way by developing a digital twin of 18,000 transformers, aiming to optimize grid operations using AI. The program just started, results are coming, and we will see them by next year. It remains to be seen whether AI can, like Munchausen, pull itself and us out of this one.

Cleantech Group Take:

This reminds me of a discussion which took place at our May 2025 Cleantech Forum Asia around how differently we need to think about the design of future infrastructure.

“Perhaps the most provocative insight of the session was that future infrastructure will be built not primarily for human use, but for machines. The demands of AI, robotics, and digital services will drive infrastructure decisions to a greater extent than urban population growth. It’s a reversal of past planning assumptions—and a call for a new design philosophy.”

You can read more on that discussion led by Anthony DeOrsey, Research Manager at Cleantech Group, here.

AI is emerging as a key enabler for Chinese cleantech, extending past traditional “hard” cleantech to also encompass “soft” cleantech. In manufacturing and transportation, companies no longer “teach” robots/EVs with software-coded rules. Instead, Chinese enterprises are applying Physical AI to “train” robots/EVs beyond what humans can teach. Current AI technology can generate Vision-Language-Action (VLA) operation datasets and modeling, simulate tasks, then verify and receive feedback from physical world models (i.e., World Foundation Models). This technology is accelerating factory automation, embodied robotics, and EV smart driving. AI enables these applications with superior precision, enhanced production efficiency, while optimizing energy consumption and minimizing material waste.

In China’s new materials and bioscience industries, AI has become a transformative developmental tool. AI-designed biomaterials have greatly reduced cost and achieved higher performance than animal-derived materials. A trend is emerging of companies leveraging AI for R&D applications including data analysis, predictive modeling, high-throughput experimentation, and design optimization. For example, PAM2L Biotechnologies is a leading company in this space, specializing in AI-driven protein mining/evolution technologies to expedite development of new bio-based materials including mussel adhesive proteins (MAP), HythermFN (recombinant fibronectin), and Colamin Biocellulose materials. As AI continues to expand vertically in this space, we expect cleantech materials and bioscience companies in China to also grow immensely.

Despite its advantages for cleantech, as AI models grow in complexity and scale, their energy consumption has become a significant concern. Hence, we will also be zooming in on start-ups that can optimize existing AI infrastructure for better energy efficiency, while maintaining or even improving performance.

Cleantech Group Take:

China remains a blind spot for most and I think it is a reasonable bet that, given China’s leadership in the most mature clean technologies–solar, batteries, EVs, and heat pumps, the core pillars of a future electro-state–there will be new areas in the cleantech landscape where China, through focused use of AI in cleantech, will come out with something that blindsides the rest of the world.

Certainly, we agree with the notion of AI as a transformative developmental tool. We have identified scores of startups who are using it as such–whether that’s in taking months out of the R&D processes, modeling new materials, simulating fusion reactors, or reducing risks and costs in exploration for potential mining or geothermal sites.