![Green Intelligence and the Circular Future | A Realistic Path to 2030 Drawn by AI x Climate Tech [SusHi Tech Tokyo 2026]](/images/columns/green-intelligence-circular-future-2026/cover.png)
Hello, this is Hamamoto from TIMEWELL.
"The discussion phase is over. We are simply executing." The moment Taiwan's Minister of Environment, Mr. Peng, said this on stage, the room went silent. When the head of a national agency declares that "the debate is finished," it signals real conviction.
The "Green Intelligence and a Circular Future" session at SusHi Tech Tokyo 2026[^1] sat at the intersection of climate change, the circular economy, and AI — three of the defining agendas for the late 2020s. The panel featured Taiwan's Minister of Environment Mr. Peng[^2], Associate Professor Koshiuka of the University of Tokyo, Associate Professor Anna Yoko Kubo of the University of Tokyo's Interfaculty Initiative in Information Studies, and Dr. Tomo Nagano of Fujitsu[^3]. It was a stimulating hour where the perspectives of two countries — Japan and Taiwan, with notably different approaches to AI and environmental policy — collided productively.
Summary: Three Takeaways from the Session
- Taiwan's Ministry of Environment has executed a "government all-in on AI" strategy that drove internal AI usage from 10% to 90% in a short period, and is now rolling out concrete policy implementations such as full-tree mapping with drones plus LiDAR and a coffee-grounds recycling program called "Jan Jan."
- Fujitsu, with a 2040 carbon-neutral target, has built a supply-chain CO2 information-sharing system aligned with the PACT framework[^4] and is now pulling Tier 2 and Tier 3 SME suppliers into the same data fabric.
- Associate Professor Kubo of the University of Tokyo redefined the smart city around citizen well-being, proposing an approach in which AI surfaces "fun" and "joy" rather than only optimizing for efficiency.
SusHi Tech Tokyo as an International Hub for Climate x AI
As the name "Sustainable High City Tech Tokyo" suggests, SusHi Tech Tokyo 2026 is one of Asia's largest innovation conferences, with sustainability sitting at its core. Held at Tokyo Big Sight from April 27 to 29, 2026, the program featured many sessions at the intersection of resilience and AI, with sustainability as the connective thread.
This particular session was the heart of that sustainability track. The room was packed; standing-room business leaders and policymakers filled the back. The audience itself told the story that climate action has shifted from a topic for environment ministries and NGOs into a board-level agenda for every industry.
You can read my recap of the keynote in a separate article, SusHi Tech Tokyo 2026 Keynote Report. Read together, the two pieces give a fuller picture of what the conference signaled.
A Striking Number — Taiwan's "Government All-In on AI" Strategy
The numbers Minister Peng presented were extraordinary. Inside Taiwan's Ministry of Environment, AI usage jumped from 10% before deployment to 90% afterward. AI tools cut working hours by 25%. The circular-economy index reads 16.5% for Japan, 9% for Taiwan, and 6 to 7% globally.
| Metric | Taiwan | Japan | Global Average |
|---|---|---|---|
| Government AI usage rate (before → now) | 10% → 90% | Limited public data | No data |
| Working-hour reduction rate | 25% | Department-level pilots | Roughly 5 to 15% |
| Circular-economy index | 9% | 16.5% | 6 to 7% |
| ETS (carbon pricing scheme) | Launched 2024 | Under review for FY2026+ | EU and others ahead |
A 90% adoption rate is unthinkable in Japanese government agencies. Minister Peng earned a Ph.D., founded a company, and ran a meteorology business for 24 years before entering politics. A private-sector technologist who actually understands implementation is now the environment minister, transforming a government organization with AI.
The strategic intent of that appointment shows up directly in the numbers. In Japan as well, placing people who have shipped real systems in the private sector into senior government roles — and letting them act top-down — will, I believe, be a deciding factor over the next decade.
What "All-In on AI" Actually Means
The Taiwanese government initiatives Minister Peng described were strikingly concrete.
1. Mapping every tree using drones plus LiDAR
A nationwide project to digitize the entire tree inventory of Taiwan. The goal is to mitigate urban heat-island effects and to make environmental improvements over the next decade measurable. It is a model case for environmental policy that does not stop at "we planted some trees" but quantifies the outcome.
2. The "Jan Jan" coffee-grounds recycling project
In partnership with 7-Eleven Taiwan, used coffee grounds are collected, dried, and converted into high-value products — a circular-economy business built on top of an existing distribution network. Repurposing the convenience-store network as circular-economy infrastructure is a clever idea, and one that Japan could replicate.
3. The 2024 launch of Taiwan's ETS
Taiwan introduced a real carbon-pricing scheme in 2024. It has the potential to become the precursor to an East Asian ETS that links the EU, Japan, and Korea. Minister Peng projected that "over the next 5 to 10 years, an integrated circular economy across East Asia is achievable."
4. Environmental education through the sports game "Sporty"
A litter-collection initiative that turns environmental action into a game and builds public awareness organically. It marks a shift away from command-style policies ("don't use plastic") toward an educational approach where citizens internalize the reasoning themselves.
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University of Tokyo's Associate Professor Kubo — A Smart City Centered on Well-being
Associate Professor Kubo redefined the smart city as urban design centered on citizen well-being. She introduced tools like a "Happiness Finder" — an AI that surfaces small moments of joy in everyday urban life.
The framing was striking. Traditional smart-city thinking has been organized around efficiency and optimization. Kubo's proposal places fun and joy at the center. I read it as a signal that we are entering a phase where technology has to engage with the inner life of human beings, not only their throughput.
Fujitsu's Dr. Nagano — Carbon Neutrality Across the Supply Chain
Dr. Nagano's presentation was, for me, the most useful one from a corporate-implementation standpoint.
Fujitsu has set a 2040 carbon-neutral target and is building a supply-chain CO2 emissions information-sharing system using PACT-aligned data formats. What stands out is that Fujitsu requires reporting all the way down to small Tier 2 and Tier 3 suppliers.
This is far from trivial. Most Tier 3 suppliers are SMEs that lack both the methodology and the headcount to measure CO2. Fujitsu provides them with measurement tools and training programs as a package. "Reducing CO2 at a large enterprise requires upgrading the entire supply chain alongside it." That structural truth of sustainability lives inside this initiative.
Designing the operating model for Scope 3 is one of the highest-priority topics for manufacturing CXOs. For more, see my related article Scope 3 Reporting and AI in Manufacturing.
My Take — "Executing Taiwan" vs. "Cautious Japan"
Listening to this session, I was honestly stunned by the gap in policy-implementation speed between Taiwan and Japan. Behind the move from 10% to 90% AI adoption inside Taiwan's environment ministry sits a top-down decision and the clarity to act on it. There is an organizational culture in which Minister Peng can credibly say "the debate is over." That is genuinely hard to reproduce inside Kasumigaseki.
That said, Japan has its own strengths. Global firms like Fujitsu are driving long-horizon transformation across the entire supply chain. In the short term it can look slow; over a decade, it becomes a deep transformation.
If we frame Minister Peng's Taiwan model as "broad and fast deployment" and Fujitsu's model as "deep and long-term construction," the two are complementary. Japan's government should adopt more of Taiwan's speed; Japanese companies should retain the depth of the Fujitsu approach.
How an ETS Reshapes Corporate Decision-Making
The ETS Taiwan introduced in 2024 is a genuinely significant policy shift. Once carbon emissions become a real cost line, corporate decision-making changes at its foundations. Choices that used to be driven by a vague preference for "being eco-friendly" become driven by hard financial metrics.
Japan, too, is now actively debating a real carbon-pricing regime for FY2026 and beyond. There is a great deal to learn from how Taiwan rolled out its ETS. Introduce the regime early and give companies time to prepare — that is the key to a soft landing.
The Coffee-Grounds Recycling Case as a Lens on the Circular Economy
Minister Peng's coffee-grounds recycling story can look like a small win, but it captures the essence of the circular economy. Three points stand out.
- Reuse existing infrastructure (convenience stores) instead of building new infrastructure
- Distributed local collection to minimize logistics cost
- Move waste up the value chain to convert it into a profit center
Japan can apply the same pattern to its 30,000-plus convenience stores as circular-economy infrastructure. Used-textile collection, small-electronics take-back, food-loss programs — there is still significant white space for micro-circular businesses delivered through convenience-store networks. I see clearly a future in which a wave of startups gets built in this space.
Citizen Education in an Age of Information Saturation
Minister Peng's observation that "Taiwan has 23 million people but 70 million Facebook users" highlights the information-saturation problem. It is a critical theme that has to be addressed alongside fake-news countermeasures. In a saturated information environment, the question becomes how to deliver accurate knowledge about environmental policy and the circular economy to citizens.
Gamification like "Sporty," participatory content, community-led learning — information design that pulls citizens into active participation will increasingly determine whether environmental policy succeeds or fails.
Why Associate Professor Kubo's "Well-being Axis" Matters
In the second half of the session, Associate Professor Kubo's proposal of urban design centered on citizen well-being struck me as the most important long-term lens. Both the circular economy and carbon neutrality exist in service of human flourishing. If we chase only the indicators and erode quality of life along the way, we have inverted the goal.
An AI tool like a "Happiness Finder" mines sensor data across the city to surface the trace evidence of well-being — "this park has many people laughing in the evening," "shoppers on this street report high satisfaction" — and feeds those signals back into urban design. I expect a unified urban index that integrates sustainability and well-being to become the headline metric of the next decade.
Spillover Effects to ASEAN
Taiwan's AI strategy will ripple into ASEAN. Thailand, Indonesia, and Vietnam are all building their own AI x environment strategies with one eye on Taiwan's playbook. By partnering with Taiwan, Japan has a real opportunity to serve as the hub for AI environmental policy across Asia.
China is also moving quickly in this domain. But on data openness, alignment with international standards, and democratic process, the Japan-Taiwan partnership is in a stronger position to earn international trust. Japan should treat this geopolitical advantage more strategically than it currently does.
Three Questions for Business Leaders
Reframing this session for executives, the implications collapse into three questions.
| Question | What to check | Priority |
|---|---|---|
| Can you trace your CO2 emissions through three tiers of your supply chain? | Maturity of measurement across Scope 3 categories 1-15 | Highest |
| Are you actually using AI as an environmental-policy implementation tool? | Carbon-management SaaS, AI-driven energy optimization | High |
| When carbon pricing arrives, can your business model absorb it? | Per-product CO2, price-pass-through scenarios | Medium to High |
Few Japanese companies can yet answer "yes" to all three. Over the next five years, however, all three will become standard practice. The companies that prepare first will hold the high ground in global competition. I plan to actively bring this discussion into our work with TIMEWELL's partner companies going forward.
What the Startup Side Looks Like — Asuene, Booost, and the Wave Behind Them
I want to add a layer the panel did not have time to cover in detail: the startup side. In Japan, climate-tech startups have moved from "early-stage curiosity" to "core infrastructure for corporate sustainability functions" in a remarkably short period.
Asuene has built a CO2 visualization platform that addresses Scope 1, 2, and 3 in a unified way, and is now used by thousands of companies across Japan. Their sales narrative is no longer "should you measure?" but "how fast can you measure, and how do you turn the numbers into reduction plans?" The center of gravity in the market has clearly shifted from awareness to execution.
Booost has gone further on the operational side, focusing on carbon accounting workflows that can be embedded into existing ERP and procurement systems. Their differentiator is the ability to translate fragmented supplier data into a single audit-ready ledger. For listed companies preparing for mandatory disclosures aligned with international frameworks such as ISSB and SSBJ, this kind of operational rigor is not optional — it is becoming a license to operate.
Looking at this layer alongside Fujitsu's enterprise initiative, you can see a clear pattern. Large enterprises set the standard and pull suppliers in; startups provide the tooling that makes participation realistic for those suppliers. Neither side wins alone. The combination is the actual unlock.
The Energy-Optimization Frontier and Why AI Matters
Another area that came up briefly in the session, and that deserves its own emphasis, is renewable-energy optimization. Solar and wind output is intrinsically volatile. Without intelligent balancing, every percentage point of renewable share in the grid increases the operational stress on the system.
This is where AI becomes structurally important. Demand forecasting at the household and facility level, dynamic dispatch of distributed batteries, and bidding optimization in wholesale electricity markets — all three are domains where machine learning models are now demonstrably outperforming traditional rule-based methods. Several Japanese utilities have begun running AI-based forecasting in production, with measurable reductions in imbalance penalties.
Long term, what this means for corporate energy procurement is that "buying clean electricity" stops being a procurement task and becomes a portfolio-management task. Companies that learn to manage their energy portfolio actively — combining on-site generation, PPAs, batteries, and demand response — will hold a structural cost advantage over companies that treat electricity as a passive utility cost.
The Data Layer Underneath It All
Underneath every visible green-intelligence application sits the same unglamorous problem: data. Emissions data is fragmented across ERP, procurement, logistics, facilities, and external supplier systems. Most of it was not designed to be aggregated. A surprising amount still arrives by email and spreadsheet.
Three patterns are emerging as the practical answer. First, a unified emissions data lake that ingests both structured ERP records and unstructured documents (utility bills, freight invoices, supplier surveys) and normalizes them against a shared activity-data taxonomy. Second, AI-assisted classification of expense lines into emissions categories, which collapses what used to be weeks of manual work into hours. Third, data-quality scoring at the row level, so disclosure teams can defend exactly how confident they are in each number.
The companies that get this layer right will treat emissions reporting like financial reporting — auditable, repeatable, and continuously updated. The companies that do not will find themselves running an emergency project every reporting cycle.
Closing Thought — Why I Care About This Personally
I want to close on a personal note. As founder of TIMEWELL, I think a lot about what kinds of challenges deserve to be democratized. Climate is at the top of that list. The cost of inaction is borne disproportionately by people who had the least power to cause the problem in the first place.
What this session showed me is that the tools have arrived. AI is no longer the bottleneck. What is left is execution — political will, organizational courage, and the patience to do the unglamorous data work behind the scenes. I leave the venue more determined to make TIMEWELL a place where that execution work can actually happen, with partners who are willing to do it together.
For a related view on the executive-level implications of the AI agent era, please also see the companion article AI Agents Pioneering the Future.
Conclusion — AI Becomes a "Democratization Tool for Environmental Policy"
The biggest message I took away is this: AI is a democratization tool for environmental policy. It plays out in four layers.
- AI inside government raises both the quality and speed of policy (Taiwan)
- Citizen-facing AI builds environmental awareness organically (Sporty)
- Enterprise AI enables transformation across entire supply chains (Fujitsu)
- Urban AI surfaces citizen well-being (Kubo Lab)
Across these four layers, AI democratizes environmental policy.
TIMEWELL's mission of "democratizing challenge" sits on the same horizon as this democratization of technology. A society in which AI functions as supporting infrastructure for individuals taking on challenges, citizens protecting the environment, and companies driving transformation. The time to start moving toward it concretely has arrived.
To borrow Minister Peng's phrasing once more: "The discussion phase is over. We are simply executing." I genuinely hope every Japanese decision-maker takes those words personally — and soon.
A Note from TIMEWELL
If you are working through a sustainability x AI strategy or designing how to apply AI to Scope 3 reporting, our AI consulting service WARP offers individual advisory engagements. You can start with a 30-minute online consultation.
Related Articles
- SusHi Tech Tokyo 2026 Keynote Report
- AI Agents Pioneering the Future [SusHi Tech Tokyo 2026]
- Scope 3 Reporting and AI in Manufacturing
References
[^1]: SusHi Tech Tokyo 2026 official site. https://sushitech-startup.metro.tokyo.lg.jp/ [^2]: Ministry of Environment, Taiwan. https://www.moenv.gov.tw/ [^3]: Fujitsu Carbon Neutral Strategy. https://www.fujitsu.com/jp/about/environment/ [^4]: PACT Framework (WBCSD). https://wbcsd.org/pact