Sustainability Reporting: Meeting the Needs of the Market

Richard Barker, PhD, of the International Sustainability Standards Board and Professor, University of Oxford's Saïd Business School, recounts the rise in sustainability reporting. In a world where planning for a low carbon, sustainable future creates greater enterprise value than persisting with business as usual, businesses need to effectively communicate their sustainability story.

Sustainability reporting is on the rise. The Securities and Exchange Commission (SEC) has issued its climate disclosure rule. California has introduced legislation to require public and private companies that do business in the state to disclose their greenhouse gas emissions and their climate-related financial risks. The International Sustainability Standards Board (ISSB) has issued its first global standards, IFRS S1 and IFRS S2, which have been endorsed by IOSCO, and which consolidate foundations laid by the Sustainability Accounting Standards Board (SASB), the Task Force on Climate-related Financial Disclosure (TCFD) and others.

These developments have their roots in economics. Sustainability reporting is on the rise because the business case is becoming more widely understood. Change is being driven by markets.

A simple illustration makes the point. Think about the history of the auto industry, what comes to mind? Maybe Henry Ford, who started the production lines that still define the industry. Or maybe Alfred Sloan’s General Motors, and the mass customization that has characterized the industry ever since. Ford and GM have in common the internal combustion engine, the driving force that powered the 20th century and that continues into the 21st. The engine in tractors, haulage trucks, bankers’ saloon cars, and CEOs’ SUVs. The demand for ExxonMobil and Chevron. This is economic activity as we know it. Business as usual. Business as it’s always been done. Enter VinFast, which started making cars six years ago, electric cars. In Vietnam. In August last year, it launched an IPO on the New York Stock Exchange, initially achieving a market capitalization of $87bn, higher than the combined value of Ford and GM. By the standards of the traditional global elite in the auto industry – not just Ford and GM, but also Toyota and VW — VinFast is a startup, but then so too was Tesla in the not-too-distant past. It came from nowhere. It cruised past indomitable incumbents. It became by far the most valuable automaker in the world.

Whether VinFast or Tesla is the more remarkable story, I don’t know. What is unmistakable, however, is that both are stories of disruption. Investors have chased both stocks because they see a future that is different from the past. An 1849, a railroad boom, a dot.com rush. The world is being weaned off oil and gas. Investors are looking to find the money-makers in an electric, renewable economy. There is no climate change denial in the valuations of VinFast or Tesla. The opposite, maybe (and the evidence of a bubble in Vinfast’s opening valuation is clear). But denial, clearly not. Investors buying the stock are buying into an electric future. Their thesis is that the energy sources that built our economies are not those that will sustain it. Economic value will be created in different ways. Profits will be sustained with different business models. New and existing markets will be served in different ways.

There’s the twist. This is not sustainability as an end in itself. It is not glossy stories of corporate social responsibility. It is instead sustainability as a place to do business. Investors are looking to different market conditions that lie ahead, a place where sustainability creates value. Sustainability of profit. Business resilience. Capacity for growth. Flexibility and vision to escape business as usual, to look ahead and see a world that is changing. A business proposition that is worth maybe $87bn.

The point is this. If global warming remains unchecked, and if such things as extreme weather events and global supply chain disruptions further as the new norm, the economy will suffer. And if the economy suffers, conditions will not be favorable for economic activity and neither, therefore, for investors. The corporate reporting implication is obvious. Investors want to know how your business sees the future, how you are planning to meet it, and what value you expect to be able to create. Current financial reporting alone cannot offer this; in a disruptive world, investors cannot evaluate your prospects based upon existing conditions or past performance.

This is how to think about sustainability reporting. How will you make money in a sustainable economy of the future? What’s the business case? What’s your plan? Why should investors buy your stock?

Note what this is not. It’s not compliance. It’s not a PR exercise, promoting green anecdotes as a smoke screen on business as usual. Fundamentally, it’s not even anything new. It’s timeless principles of economic thinking, value creation, and corporate reporting, applied in a setting where the future will look different from the past, and where planning for a low carbon, sustainable future creates greater enterprise value than persisting with business as usual. It’s reporting to investors who value makers of electric cars more highly than those making the cars of yesterday.

That train has left the station. Pretty much all major US corporations are doing sustainability reporting in some form. For example, there are currently 1,297 public companies in the United States using SASB’s industry-based reporting standards. These include (to sample from those at the start of the alphabet): Abbvie, Accenture, Adobe, Allstate, Alphabet, Amazon, American Airlines, Apple, AT&T and Avis Budget. In doing so, you are in good company.

This reporting covers all sectors because all have a sustainability story that needs to be told. Leading manufacturers and constructors are investing in energy efficiency and circular business models. Fund managers and banks are de-risking investment and loan portfolios by setting demanding targets on emissions. Aviation is focused on sustainable fuel, the oil and gas industry on energy security during a period of transition to a low carbon future. And so, the list goes on. This reporting is driven in part by investor demand but also because doing business responsibly gives you a license to operate, and transparent reporting validates that license.

So, how should you be thinking about sustainability reporting? How can it be most valuable to your investors, and therefore also to your business? I address these questions in a recent article in MIT Sloan Management Review, Get Ready for More Transparent Sustainability Reporting. That article offers an 8-part guide, as follows:

Don’t stop what you’re already doing — Your company might (for example) disclose its carbon emissions or plans to transition to renewable energy. Build on this, there is no need to start over.
Don’t let perfect be the enemy of good — Investors want to understand what your sustainability-related risks and opportunities are and how you are managing them. They don’t need perfect information; disclose what you can.
Align with financial reporting — Investors want to know how sustainability issues, such as carbon emissions or waste management, affect your financial prospects, whether revenue from new opportunities or capital expenditure to ensure business resilience. The more that disclosure connects to current and prospective financial statements, the better.
Focus on climate — Climate is the dominant sustainability issue. If you are not already on top of climate-related reporting, you will need to be. And if you do climate reporting well, you will have the structures and systems needed for other components of sustainability reporting.
Tighten systems and controls throughout your value chain — Higher quality sustainability reporting is a source of competitive advantage because investors are more willing to invest at a lower cost of capital, if they trust your data.
Align with the ISSB global baseline — Sustainability reporting calls for data throughout global value chains. The ISSB’s global baseline aligns with stock market requirements to disclose material information to investors while also being an efficient foundation for other emerging requirements, such as in California and Europe.
Contribute to the development of industry norms — Investors understand that sustainability issues vary by industry. The ISSB is therefore committed to its industry-based SASB standards. Companies can innovate in developing best-practice reporting in their sectors, helping shape future standards.
Ensure an authentic connection with value creation — If sustainability reporting feels like a costly exercise in compliance, you are missing an opportunity. Your focus should be on aligning disclosure to investors with information that is valuable to you in leading the business. You will have investors’ full support only if you communicate effectively to them how you plan to create value in a changing world.

Above all, think about the economics. Sustainability reporting is on the rise because the business case is sinking in. Focus on meeting the information needs of the market.

This article expresses the personal views of the author, not the official positions of the ISSB.

About the Author:

Richard Barker, PhD
International Sustainability Standards Board
Professor, University of Oxford's Saïd Business School

PHOTO: TJBauman, LLC

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Listening, Learning, and Rebuilding Connection: Reflections from Our First ISSP Town Hall

By Elizabeth Dinschel, December 18, 2025 • December 18, 2025

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Can sustainability be saved by tackling loneliness, not just CO₂ emissions?

By Raz Godelnik, Associate Professor • November 20, 2025

Raz Godelnik is an Associate Professor of Strategic Design and Management at Parsons School of Design — The New School. He is the author of Rethinking Corporate Sustainability in the Era of Climate Crisis . You can follow him on LinkedIn . Can sustainability be saved by tackling loneliness, not just CO₂ emissions? Earlier this month, I stopped at Sunshine Coffee in Laramie, Wyoming, on our way to Yellowstone Park. What brought me there was the fact that it’s a zero-waste coffee shop, with no single-use consumer items. In other words, there are no disposable cups — not for customers dining in, and not even for those who want their coffee to go, like I did. Instead, you can either bring your own reusable cup or get your drink in a glass jar for $1, which is refunded on your next order when you return it (or you can simply keep it, as I did). At first, I was excited about the zero-waste coffee shop concept, wondering what it would take for Starbucks and other coffee chains to adopt it and eliminate the waste that has become an integral part of our coffee (and other drinks) consumption. But as I waited for my coffee, I began to notice something else — something that had little to do with waste and everything to do with people. As I looked around, I noticed their stickers. Beneath the logo, it read: Zero waste. Community space . Suddenly it clicked — this coffee shop isn’t just about eliminating waste; it’s about creating a place where people feel connected. As owner and founder of Sunshine Coffee, Megan Johnson, explained in an interview with This is Laramie : “I wanted to bring sustainable values to Wyoming as well as build a business that serves the community.” That got me thinking about how the second part — serving the community — is integral to the first. After all, in a world where loneliness — a key barrier to people’s well-being — is on the rise, shouldn’t creating spaces for connection be just as central to sustainability as going zero waste?

Toward Appropriate and Responsible AI: Pathways to Sustainable Adoption and Infrastructure

By Nicole Cacal, MSc, • October 30, 2025

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People want to explore AI's potential, but they're acutely aware of the energy consumption, the water usage, the carbon footprint. It's become almost a reflex: mention AI, and someone immediately raises the environmental cost. I get it. The data centers, the training runs, and the resource demands. They're real and they're significant. But here's what I've come to believe: if we shift the narrative from focusing solely on AI's detriment to the environment and instead ask how much good it can create, what role we can play in driving data centers to go greener, and how we can generate recursive sustainability, we unlock better questions. We start thinking forward rather than just defensively. As sustainability professionals, our job isn't to reject technology wholesale. It's to shape its evolution. And right now, we have an opportunity to influence how AI develops and deploys in ways that align with planetary boundaries and social equity. But to do that, we need to move beyond binary thinking. Right-Sizing AI: Why Bigger Isn't Always Better One of the most overlooked levers we have for sustainable AI is also one of the simplest: choosing the right model for the job. The AI industry has been caught in a "bigger is better" arms race for years now. Every new model release touts more parameters, more capabilities, more everything. And sure, these massive general-purpose models are impressive. But they've created a dangerous assumption: that every task requires maximum firepower. This is where my strategic design training from Parsons kicks in. Good design isn't about having the biggest toolkit. It's about matching the tool to the task. It's about elegance through constraint. The same principle applies to AI deployment. The emerging concept of "Small is Sufficient " is gaining traction for good reason. Research shows that selecting smaller, purpose-fit AI models for specific tasks can achieve nearly the same accuracy as their larger counterparts while reducing global energy demand by up to 28% . Twenty-eight percent. That's not marginal; that's transformational. Think about what your organization actually needs. Are you processing customer service inquiries? Analyzing spreadsheet data? Generating product descriptions? Most of these tasks don't require a frontier model. A fine-tuned, task-specific model will do the job with a fraction of the computational overhead. The shift we need is cultural as much as technical. We need to move from asking "what's the most powerful AI we can deploy?" to "what's the most appropriate AI for this specific use case?" That question changes everything, from procurement decisions to vendor relationships, internal training, and infrastructure planning. AI as Infrastructure Manager: The Self-Optimizing Data Center Here's an irony that doesn't get enough attention: AI might be energy-intensive, but it's also one of our best tools for managing energy systems efficiently. When we only think of AI as a consumer of data center resources, we miss part of the story. AI can also be the conductor of efficiency, orchestrating complex systems in real-time to minimize waste and maximize renewable integration. Consider three optimization domains where AI is already making measurable impact: Cooling systems: Data centers generate enormous heat, and cooling accounts for a massive portion of their energy use. AI can continuously adjust cooling based on workload patterns, outside temperature, humidity, and dozens of other variables, optimizing in ways that static systems simply can't match. Workload scheduling: Not all computing tasks need to happen immediately. AI can intelligently schedule batch processing, model training, and background tasks for times when renewable energy is abundant or when grid demand is lowest. This isn't just theory. Companies are already doing this. Renewable energy integration: This one hits close to home in Hawaii, where we're working toward aggressive renewable energy targets but face unique challenges with grid stability and storage. AI-managed facilities can modulate demand in response to solar and wind availability, essentially turning data centers into flexible grid assets rather than inflexible burdens. When organizations approach their operations as integrated systems rather than collections of independent components, they achieve results that surprise even them. AI-orchestrated data centers represent this systems thinking at its most sophisticated. The technology optimizes itself recursively, reducing the footprint of AI through AI. That's the kind of elegant solution we should be scaling. Measuring What Matters: Beyond Energy to Net Benefit But here's the challenge: if we only measure AI's direct energy consumption, we miss the full picture. We need frameworks that capture both the operational cost and the systemic benefit. This is where life cycle assessment combined with comparative modeling becomes essential. We need to ask: compared to what? And over what timeframe? The sectoral success stories are compelling when you run the numbers: Building automation systems powered by AI are consistently achieving energy savings in the range of 20-30% across diverse building types. One documented case study of a commercial office building in the United States showed a 32% reduction in overall energy consumption with a 2.4-year return on investment (a $2.1 million system investment generating $875,000 in annual savings). In Stockholm, the SISAB school building portfolio achieved similar results with a two-year payback period. In precision agriculture, AI-driven irrigation and fertilizer application systems are cutting water consumption by 20% to as much as 50% and reducing chemical runoff, addressing both resource scarcity and ecosystem health. Waste management optimization is another powerful example. AI-powered sorting systems in recycling facilities dramatically improve material recovery rates while reducing contamination. The resource efficiency gains far exceed the AI system's energy footprint. These aren't marginal improvements. When properly deployed, targeted AI applications produce emissions savings and resource efficiencies that dwarf their own operational costs. That being said, given today's fossil fueled data center expansions, we may find that we have much further to go in making the environmental positives outweigh the negatives. But that's no reason to throw in the towel or to assume that these technologies cannot - over time - deliver more environmental benefits than downsides. It requires companies to demand more of their technology providers and deploy their systems sustainably when greener options become available. But (and this is crucial) these benefits only materialize when we pair the right AI with the right infrastructure and the right deployment strategy. Which brings us to governance. The Path Forward: Governance, Transparency, and Adaptive Thinking The sustainability community, including organizations like ISSP, is actively developing shared frameworks for assessing AI's net impact. These emerging approaches include system-level energy auditing, selective task deployment protocols, and strategies for minimizing "dark data" (the vast amounts of stored data that's never used but still requires energy to maintain). Multi-stakeholder governance initiatives are bringing together technologists, policymakers, environmental scientists, and business leaders to create adaptive standards. This isn't about creating rigid regulations that will be obsolete in two years. It's about establishing principles and processes that evolve with the technology. Those with a technology management background know that the most successful systems are those designed for adaptation. We need governance structures that can respond to new information, course-correct quickly, and remain grounded in measurable outcomes. Transparency is non-negotiable. Organizations deploying AI need to measure and report not just their energy consumption but their net impact. What problems are you solving? What resources are you saving? What would the alternative approach have cost? These aren't easy questions, but they're the right ones. As sustainability professionals, this is our arena. We have the frameworks: life cycle thinking, systems analysis, stakeholder engagement, and metrics development, to name a few. We need to apply these tools to AI with the same rigor we've applied to supply chains, built environments, and industrial processes. So here's my invitation: What are you seeing in your sector? How is your organization approaching the AI sustainability question? Are you finding innovative ways to ensure deployment is appropriate and responsible? Because ultimately, appropriate AI isn't about choosing between progress and sustainability. It's about insisting that progress is sustainable. It's about right-sizing models, optimizing infrastructure, measuring net benefit, and building governance systems worthy of the challenge. The technology itself is neutral. Our choices determine whether AI becomes a driver of sustainability or another extractive burden. Let's choose wisely.