The IOC Took Eni’s Money. Greenpeace Called It Absurd.

Markets work when prices tell the truth. In the case of fossil fuels, they do not. Eni, the Italian oil and gas company, sponsored the 2026 Winter Olympics in Milan and Cortina d’Ampezzo. Greenpeace called it absurd. It was also, from a purely economic standpoint, entirely rational.

Eni’s products contribute to the warming that is shortening the Alpine ski season and threatening the long-term viability of winter sport. None of that cost appeared on Eni’s balance sheet. The IOC received a sponsor. Eni received credibility. The glacier continued to retreat.

The arrangement held because the price signal that would have made it unsustainable did not exist.

This is not primarily a story about corporate hypocrisy. It is a story about what happens when externalities go unpriced. The companies that build alternatives to the status quo compete on a tilted field. The companies that created the problem do not pay for it.

A Decade in China and the End of Landfill Space

Manuela Zoninsein spent nearly a decade in China between 2007 and 2015. She arrived as a Newsweek reporter, stayed to study Mandarin at universities in Taiwan and Beijing, and built an agricultural analytics firm tracking China’s agritech market for foreign investors. She watched, over those years, a country of one and a half billion people make the transition from reuse to single use at a speed and scale that settled a question she had not quite known she was asking.

“Anything that happens in China, one point five billion people jump,” she said. “You understand the impact.”

The landfill space ran out. The conclusion she drew was structural, not moral. Single use does not work at scale. She went on to study at Oxford and MIT, work at Palantir across four international markets, and co-found an agricultural marketplace in Brazil. The common thread, visible only in retrospect, was a repeated encounter with what happens when convenience is optimised and consequence is externalised.

Bike Sharing, Bottle Returns, and the Infrastructure Nobody Built

Two further observations shaped what became Kadeya. Watching New York build out its bike-sharing network, Manuela asked why the model worked. The answer was ownership economics. People do not want to maintain a bike, store it, or file a police report when it is stolen. They want mobility. Bike sharing sells the outcome rather than the asset.

The analogy to beverages was direct. At MIT business school she began asking why bottle return rates were assumed to be low. The consensus answer was behavioural: Americans were disinclined to return bottles. Her counter was infrastructural.

“If you create enough density, if you have enough points for pickup and drop off, actually you can get ninety-nine percent return rates with no penalty or deposit.”

The deeper error, she concluded, was methodological. Reuse had always been benchmarked against single use as currently designed, rather than asked what it could achieve if engineered to match single-use convenience. The former comparison always favours the incumbent. The latter is a different question entirely.

A Dishwasher, a Soda Fountain, and a Ninety-Nine Percent Return Rate

Kadeya’s answer is a bottling plant inside a vending machine footprint. Stainless steel bottles are dispensed, returned, inspected by machine learning, washed, sanitised, and refilled on-site. No plastic. No deposit. No supply chain shipping water around the planet.

“We did not invent a single new thing,” Manuela said. “We just recombined existing technologies in a novel fashion.”

The numbers are notable. Across five commercial deployments the return rate has held at ninety-nine percent. Carbon footprint runs seventy-five percent below single use. Employer costs are a third lower. Consumer price is at parity today. The company has turned down exclusivity offers from major beverage firms to keep the network open.

Kadeya targets workplaces where hydration is operationally critical and workers are mobile: construction sites, military bases, refineries, fulfilment centres. Manuela calls it the liquid railroad, beverage infrastructure built on existing tap networks rather than against them. The economic logic is designed to hold without a carbon price. That, for now, is a necessity rather than a choice.

The Additionality Problem and Why Carbon Credits Risk Becoming Indulgences

The Eni case and the Kadeya model represent opposite ends of the same market failure. Eni sponsored a climate-threatened event because its emissions were unpriced. Single use dominates because the cost of plastic waste is unpriced. In a world where those costs appeared in market prices, both propositions would look different.

Manuela’s answer to the magic wand question is a free and open carbon market. Get the price right and the economics of every commercial activity reset. Kadeya’s advantage widens. Eni’s position becomes harder to sustain.

The obstacles are well known. Additionality, establishing that a protected forest would not have been protected in any case, is difficult to prove credibly. Voluntary markets cover a fraction of total emissions. And there is an older problem that she identifies with precision: credits risk functioning like medieval indulgences. The polluter with the deepest pockets buys the right to continue.

“How do you create a cap? How do you really say that you’ve got the full market under consideration? And then how do you ensure that it is being consistently applied and measured? I don’t know that you can.”

The carbon market, in its current form, is not solving the pricing problem. It is deferring it.

When the Richest People in History Do Not Price In the Consequences

There is a political economy argument running beneath the packaging and carbon questions. Manuela makes it directly. The most powerful figures in business and government are, in her reading, pursuing strategies that shrink the markets on which their own wealth depends. A race to the bottom generates less aggregate demand, not more. A hollowed-out middle class buys less.

Her observation about the CEO of Salesforce carries the point efficiently. A prominent climate and DEI position, held publicly for years, has been quietly abandoned as political conditions shifted. The commitment was priced at the prevailing rate of reputational risk. When that rate fell, so did the commitment.

Kadeya’s commercial model is not constructed on reputational risk. It is constructed on cost, convenience, and return rates.

The bet is that a business case built on operational advantage rather than goodwill holds across political cycles.

Whether a functioning carbon market arrives to reprice the competition before those cycles exhaust the window for structural change is, for now, the open question.

The Label and What It Does Not Require

When OpenAI completed its restructuring as a Delaware Public Benefit Corporation on 28 October 2025, it did not create any new enforceable obligation to publish safety metrics. It did not require disclosure of how outputs are generated. It did not give civil society organisations formal standing in governance decisions. It did not mandate independent verification of whether the stated public benefit is being achieved.

A public benefit corporation is a legal structure that requires directors to consider the interests of stakeholders beyond shareholders. It does not require them to demonstrate that they have done so.

The distinction is the subject of a recent Financial Times article explored in this episode of The Responsible Edge. The article’s central question is whether PBCs can solve AI governance challenges. Asher Jay’s answer is clear.

“Just making it about intention and not having tangible ways to translate that into practice is a cop-out.”

Formation

Asher did not arrive at this argument through law or policy. She arrived through coastlines.

She grew up travelling, and the water told the same story wherever she went. Bloated dolphins. Turtles in nets. Plastic on the shoreline. She describes these encounters as affecting her “on a very cellular and emotional level.” They produced not a career path, but a preoccupation.

She studied biochemistry and environmental science, volunteered across conservation nonprofits, and then moved into fashion design, branding, and modelling. She describes that period honestly. “

That’s a way to sort of deflect true responsibility and be in alignment with my own calling,” she said. “It was me listening to what the outside world thought would be a safer way.”

The recalibration came through creative conservation work: campaigns against wildlife trafficking for WWF, the Rainforest Action Network, and National Geographic. In 2014, the National Geographic Society named Asher an Emerging Explorer for that work. She later founded Henoscene, a platform built to surface discrepancies in corporate impact commitments around net zero claims, carbon offsets, and water positive pledges. It raised one million dollars in seed funding before entering a strategic pivot. She now serves as Chief Network Architect at the Shareholder Democracy Network, a bipartisan nonprofit that redirects retail proxy votes through civil society organisations, and as an impact consultant to the Mountain Lion Foundation.

The question she has been asking across all of it is the same. Whether stated commitments can be made legible to anyone outside the organisation making them.

The Governance Gap

Asher’s critique of OpenAI is structural, not personal. She tracks the company’s trajectory: nonprofit, then capped-profit entity, then public benefit corporation, with purpose-oriented language accompanying each transition. None created an external verification mechanism that would allow an independent observer to determine whether the mission remained intact.

Her characterisation of the implicit logic is direct.

“Let’s get away with what we can,” she said, “make as much money as we possibly can while we’re getting away with it and then wait to be tapped on the wrist.”

On Anthropic, which also operates as a public benefit corporation, she is conditional. There is an opportunity, she says, to learn from OpenAI’s trajectory. But the conditional is load-bearing.

“It’s always an aftermath, afterthought,” she said. Intention stated in founding documents does not constitute a governance mechanism.

The structural absence she returns to most consistently is civil society. The boards of the major AI labs are composed primarily of people with a financial stake in the company’s commercial performance. Organisations representing ecological, social, and democratic interests, the constituency that the PBC structure is nominally meant to serve, have no formal standing in how these companies are governed.

What Verifiable Accountability Would Require

Asher is specific about remedies. She would mandate that AI labs publish safety metrics and accountability standards. She would require disclosure at the level of every output: where information was sourced, how an image was generated. She would fund AI literacy globally, including for populations with no current access to the technology.

“AI is also a privilege,” she said. “I don’t think it reaches a vast majority that we don’t even converse about because they may not even have access to food, let alone a computer.”

Her most structurally significant proposal is civil society representation at board level. Not advisory boards. Voting seats. If the benefit being served is public, the organisations that represent the public should have a direct role in governance decisions. Market-facing board members cannot, she argues, adequately represent interests that do not appear in price signals.

“We should have greater representation of the diversity of people, of democratic representation being afforded,” she said. “That can only be done through civil society.”

Her work at the Shareholder Democracy Network operates on a related logic. Most retail shareholders receive proxy vote notifications and disregard them, lacking time or expertise to evaluate board nominees or governance resolutions. The network routes those votes through civil society organisations with established positions on corporate conduct. A shareholder aligned with the Sierra Club elects to have their proxy cast in accordance with the Sierra Club’s recommendations. One decision. One click. Retail influence redirected through organisations already trusted to represent public interest.

Unresolved

Regulatory frameworks for AI governance are being constructed across multiple jurisdictions, at different speeds, with different assumptions about what accountability requires. The major AI labs are participating in those processes while continuing to scale.

OpenAI’s PBC structure formally requires the company to advance its stated mission and consider the broader interests of all stakeholders.

It does not require it to prove that it has.

Whether governance architecture takes shape before these systems become too embedded to constrain is genuinely open.

The PBC label describes an aspiration. Governance requires a mechanism.