Sustainability as the Only Way to Build Back Better

Irena Zubcevic*, M.Sc. • October 28, 2020

"Today we have a surplus of multilateral challenges and a deficit of multilateral solutions."

António Guterres, UN Secretary-General at the marking of the 75th Anniversary of the United Nations, 21 September 2020


It is important to put this blog in today’s context where we are battling the simultaneous challenges of the COVID-19 pandemic, poverty, climate change, biodiversity loss, and inequalities. The 75th anniversary of the United Nations that was celebrated last month on September 21st could not have come at a better time as it reaffirmed the United Nations as the only global organization that can give hope to people and deliver the future we want. The urgency for all countries and all stakeholders, including the private and business sectors, to come together and to fulfill the promise of the nations united has rarely been greater. COVID-19 exposes both the weaknesses of our socioeconomic and health systems and the devastating effects of inequality on the most vulnerable people in a time of crisis. As we also celebrate this week the 72nd anniversary of the United Nations Day (October 24th), we have more than ever a reason to mark the ratification in 1945 of the UN Charter. COVID-19 has shown that global problems can be addressed effectively only through multilateralism and global solidarity. 


We, as sustainability professionals, need to ask ourselves how we can contribute to building back better and putting us on the path to sustainable development. We need to use this crisis as an opportunity not to go back to unsustainable ways of producing and consuming. For a company to remain competitive even over the next five years, it needs to define policies and strategies that will put it on a sustainable path right now. COVID-19 has made us all aware that something was horribly wrong with the world pre-COVID. Successful businesses will be those that meet the needs of as many people as possible, utilize as few resources as possible, and engage in meaningful, ongoing dialogue with their stakeholders. 


The United Nations Sustainable Development Goals (SDGs), if achieved, would create a world that is sustainable: socially fair, environmentally secure, economically prosperous, inclusive, and more predictable. They have also shown that to achieve sustainability, we need to tackle all three dimensions of sustainable development together — economic, social, and environmental — to establish synergies among the SDGs and related targets, but also to look at trade-offs.


Sustainability is a long-term trajectory. For a company to pursue sustainability, the SDGs need to be part of its business model and aim toward sustainable solutions through strategic planning and innovation, and not as a public relations add-on. A company needs to use a sustainability lens for every aspect of strategy, from appointing board members and senior executives to prioritizing and driving execution. A long-term systemic view, incorporating environmental, social, and governance (ESG) issues, is essential to establishing shareholder value, marketing products and services that inspire consumers to make sustainable choices, and to using the Goals to guide regulatory policy, capital allocation, and leadership development — including women’s empowerment — at every level. 


All of this would strengthen the position of sustainable development professionals working in companies. Sustainability professionals can drive synergies and work across sectors and teams so that sustainability really becomes a leading principle in all aspects of business strategy and not a public relations exercise. But they can only be empowered if board members firmly stand behind them. And only if they are given senior executive positions in companies. It is not enough that a few larger companies are doing it. It is important that all companies, including small and medium size enterprises (SMEs) do it as well. Throughout SMEs, sustainability professionals can then work with their peers in other companies to drive sustainability of markets and value chains. And policy makers need to create an enabling environment for such companies to be able to invest in sustainability through preferential loans and tax breaks. It has never been more important than now to encourage and instigate this type of a business model when COVID-19 has given us this opportunity to reset our world. This will be then a real contribution to building back better and greener. 


Both policy makers and companies need to do their part as equal partners in achieving the SDGs. Policy makers need to create an enabling environment through legislation and public-private partnerships so that true cost can be paid for natural and human resources and longer-term investment is encouraged. Companies, on the other hand, need to create sustainable value chains, respect human rights, be transparent in their work — including paying taxes — and drive innovation and technologies that would benefit everyone. Only the whole of these multisector efforts can successfully drive sustainable economic growth, create more just and inclusive societies, and ensure environmental protection and stewardship of natural resources.


About the Author:

Irena Zubcevic
*, M.Sc.
Chief, Intergovernmental Policy and Review Branch
Office of Intergovernmental Support and Coordination for Sustainable Development
United Nations Department of Economic and Social Affairs
Member of ISSP


* The views expressed here are those of the author and do not necessarily reflect the views of the United Nations.


Read perspectives from the ISSP blog

By Nicole Cacal, MSc, October 28, 2025
Nicole Cacal, MSc, is Executive Director of the TRUE Initiative in Hawaii and serves as Vice President on the Governing Board of ISSP. In our October blog, she challenges the prevailing narrative around AI's environmental impact, arguing that strategic deployment can transform AI from an environmental burden into a driver of recursive sustainability. Drawing on her background in strategic design and technology management, she presents emerging pathways for responsible AI adoption that balance societal benefit against environmental risk. Toward Appropriate and Responsible AI: Pathways to Sustainable Adoption and Infrastructure Nicole Cacal · October 27, 2025 Whenever I give an AI presentation or offer advice on AI adoption, whether to business owners, C-level executives, or sustainability professionals, one concern surfaces time and time again, especially here in Hawaii: the environmental tension. 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.
By Sobel Aziz Ngom, CEO, Tostan September 25, 2025
For 35 years, the NGO Tostan has partnered with communities across Africa to define and achieve their own vision of sustainable development based on respect for human rights. In our September ISSP Blog, Tostan CEO Sobel Aziz Ngom shares Tostan's unique approach to enduring community-led development: include all, listen before acting, take time to build trust, and share ownership with humility. Start With Community: The First Mile of Sustainable Development September 2025 Sobel Aziz Ngom CEO, Tostan When I stepped into the role of CEO at Tostan, I did not come in with the illusion that I already understood its unique approach. On the contrary, both our Board and senior leadership advised me to begin slowly, by listening, learning, and asking questions. This guidance resonated with my own experience: that lasting change only happens when communities feel ownership and define priorities in their own voices. For me, these first months have been a journey of re-affirmation and discovery. I have seen how Tostan’s approach builds directly on principles I already believed in: participation, dignity, and youth leadership. It has also opened new insights for me about what genuine engagement really looks like. Most of all, I am struck by how the process is not only about involving people in decisions, but about changing the way people relate to one another: listening more deeply, including those often excluded, communicating more peacefully, and governing more fairly. At Tostan, we believe in the dignity and potential of every community. Change is not imposed; it is nurtured through dialogue, trust, and the mobilization of local knowledge. Our approach is built on a conviction: lasting change cannot be decreed, it must be built together, step by step, in dignity and trust. That wisdom applies equally to leadership transitions and to sustainable development. Step by step toward lasting change Rather than relying on one-off or top-down interventions, our approach supports communities through a progressive journey, moving from trust and dialogue to collective action. It begins by creating an inclusive space where every voice is heard and valued. Within this space, communities identify their strengths, priorities, and core values, laying the foundation for a shared vision of wellbeing. Building on this vision, democratic principles and human rights are explored in ways that resonate with local realities, strengthening the community’s ability to organize and make informed decisions. Step by step, communities move toward planning and implementing concrete actions, mobilizing their own resources while engaging local authorities for support. Along the way, new skills are developed — in literacy, management, health, and advocacy — to sustain progress and help translate the community's shared vision into reality. Each phase reinforces the next, deepening trust, knowledge, and collective capacity, until communities are fully equipped to drive lasting change for their own wellbeing.  From voices to livelihoods: the women of Somone Lagoon One story captures this transformation for me. In Somone, Senegal, women from the lagoon area came together to discuss what mattered most for their community. At first only a few spoke. Over time, with dialogue in their own language and through participatory methods, more women raised their voices, sharing concerns, proposing ideas, and debating solutions. By the end, they not only agreed on practical steps, but also shifted how they interacted: listening actively, respecting differences, and ensuring no voice was left aside. What emerged was more than a plan for the lagoon; it was a new practice of governance grounded in fairness and inclusion. And it was not only social. By organizing collectively, the women strengthened their economic group, improved how they managed resources, and increased the income generated from their activities around the lagoon. This story is a reminder that when relationships change, so do livelihoods. Social inclusion becomes the foundation for economic empowerment. Prepared ground, lasting growth It is often tempting to judge progress by what is visible: a new structure built, a service installed, or an activity launched. But the real difference lies beneath the surface, in the preparation that makes lasting results possible. Think of planting a tree. In dry, unprepared soil, even a strong seed struggles to take root. It may sprout quickly but soon withers when conditions become harsh. In well-prepared and nourished soil, the very same seed grows deep roots, withstands storms, and bears fruit for generations. Communities work in much the same way. When there is no shared vision, no clear rules, and no sense of ownership, progress often stalls at the first obstacle. But when people take time to build trust, establish transparent practices, and develop the skills they need, their initiatives take root and thrive. As I learn about Tostan from the inside, I see the same truth. Preparation through dialogue, clarity, and capacity is what allows both communities and organizations to carry their ambitions forward with confidence. Why starting from strengths changes outcomes Across sectors, communities point to four recurring benefits of this approach: Resilience. With a shared vision and clear roles, people adapt quickly when supply or budget conditions shift. Lower lifetime costs. Early investments in facilitation and governance save money later. Fairness by design. Co-created rules reflect lived realities — girls fetching water, elders with mobility challenges, young entrepreneurs seeking opportunity. Trust as infrastructure. Trust accelerates coordination and makes accountability real. These are lessons for leadership too: trust, fairness, and resilience are as essential inside organizations as they are in village water committees. Avoiding shortcuts (and their costs) Under pressure, it is tempting to cut corners: brief consultations, over-engineered technology, committees without real mandates, or community sessions held in languages people rarely use. These approaches may deliver short-term outputs, but communities often remind us that the hidden cost is confidence. The same temptation exists in leadership transitions: to announce, to prove oneself, to act before listening. But each shortcut risks raising the cost of trust later. Spaces for sharing and mutual learning Practitioners often ask how such community capabilities are built and sustained. At the Tostan Training Center in Senegal, these questions are explored not through formal lectures but through spaces of sharing and mutual learning. In these settings, facilitators and community members sit side by side with practitioners, opening dialogues in local languages and revisiting real experiences from villages that have gone through Tostan's Community Empowerment Program. Instead of theory, people see how conversations unfold, how inclusive decisions are made, and how trust is gradually built. The value lies in what participants carry back: not a prescription, but a set of practices they have witnessed, tested, and adapted to their own contexts. This kind of exchange helps those working with communities to strengthen their partnerships, avoid common pitfalls, and ground their initiatives in methods that last. For me, it is also a reminder that leadership — whether in a village or an organization — grows through shared reflection, humility, and practice, rather than through quick fixes. Closing the loop Sustainability is not only technical or financial. It is civic and relational. It depends on who decides, who acts, and who continues to nurture progress once the external team has left. Like a tree that grows strong only in prepared soil, communities that invest in trust, inclusion, and clear responsibilities create the conditions for lasting change. Progress does not stop at the first difficulty; it deepens and spreads. The same lesson applies inside organizations. What lasts is not only a set of strategies or plans, but the culture we cultivate: listening before acting, building capacity, and sharing ownership with humility. That is why, both in my role as CEO and in our community work, I return to the same conviction: start with listening, prepare the ground carefully, and let trust grow over time. In Tostan partner communities, this is how water pumps keep running, how health improves, how livelihoods expand, and how governance endures. In Tostan as an organization, it is how culture is preserved, innovation emerges, and transitions succeed. Start with community. Lead with humility. Prepare the ground well. That is how you ensure sustainability.
By Todd Cort, MS, PE, PhD July 25, 2025
Todd Cort, MS, PE, PhD, is a Senior Lecturer at Yale School of Management and Yale School of the Environment and serves as Faculty Co-director of both the Yale Center for Business and the Environment and the Yale Initiative on Sustainable Finance. In our July blog, he sheds light on the fundamental importance of financial modeling for sustainability to be a core part of business strategy. Do the Math: Why Financial Modeling Is Essential for Sustainability As global markets begin to internalize the financial impacts of climate change and other environmental and social risks, I’ve seen expectations rise sharply for companies to provide financially robust disclosures. Standards and regulations are evolving, and the International Sustainability Standards Board (ISSB) has made it clear that sustainability disclosures must be useful to investors by linking environmental and social risks to enterprise value over the short, medium, and long term. Similarly, the EU’s Corporate Sustainability Due Diligence Directive (CSDDD) requires us to identify and mitigate adverse environmental and human rights impacts across our company’s value chain—including integrating these risks into our corporate strategy and financial planning. These frameworks don’t just ask us to be aware; they demand that we develop a quantitative understanding of how environmental and social risks affect our financial outlook. Simply put: we can no longer talk about sustainability in broad, qualitative terms. We have to do the math. And yet, despite these evolving expectations, I see little movement in risk disclosures and still see almost all in the corporate world treating sustainability as a reporting task, not a financial modeling challenge. The one possible exception being the calculation of appropriate shadow prices for carbon emissions for oil and gas asset planning by companies like Occidental Petroleum and ConocoPhillips. Although even these can be difficult to reconcile with global energy scenarios. The ISSB and CSDDD reference enterprise value, financial planning, and risk mitigation, but I notice that many corporate responses stop at narrative statements—talking about reputational risk, regulatory uncertainty, or stakeholder pressure. While those qualitative insights provide context, they fall short of supporting sound financial decision-making. As a board member, CFO, or investor, I must move beyond vague statements like "climate change may impact our operations" and instead ask: by how much, under what assumptions, and with what financial consequences? Without this level of rigor, we can’t prioritize investments, adjust capital allocation, or weigh transition risks against emerging opportunities. The data challenge I understand the lack of financial modeling and the prevalence of qualitative risk assessment and mitigation narratives issued by corporations today. The data that underlies and explains environmental and social risks feels like it is not up to the challenge of quantitative financial modeling and making statements of financial risk based on shaky data is a good recipe for inviting litigation. Even for the most well documented risks such as climate adaptation, the data can leave enormous gaps in our ability to forecast financial impact. How frequent and of what duration are the expected climate events? Where in my supply chain am I likely to see the greatest disruption? What components or operations will prove to be most vulnerable and most critical in the face of disruption? How will critical stakeholders such as regulators react and respond in the face of severe events? How strained will our backstops such as insurance coverage become in the face of widespread events? These and other questions are important to calculating severity and likelihood of financial risks, but the available data may leave us with enormous sensitivities and error bars in our analysis. However, I have found in practice that the data challenge is frequently not as daunting as it appears. Many variables turn out to be less important to the model, thereby making the data challenge less relevant. In other cases, we are able to find new data sets that provide meaningful insights to critical variables. Even in those cases where the data are lacking and the question is critical, I find that knowing the range and likelihood of outcomes is more useful than an unsubstantiated narrative. Net present value Looking forward, companies must integrate sustainability risk and opportunity into financial modeling tools typically used in capital budgeting and investment analysis to make better strategic decisions. That means projecting the net present value (NPV) of sustainability-related projects, whether it's decarbonizing operations or installing renewable energy systems. NPV is a fundamental tool for companies to assess whether these projects will create or erode value over time, especially when compared to the cost of inaction—such as paying for carbon emissions or recovering from extreme weather damage. A key part of this is choosing the right discount rate—one that reflects our risk-adjusted cost of capital and the long-term calculations of climate investments. If I choose a rate that’s too high, I risk undervaluing the future benefits of resilience; too low, and I might overstate the returns. Embedding sustainability into financial models Practitioners must also recognize that environmental and social risks directly influence key financial metrics like free cash flow, leverage ratios, and cost of capital. For instance, rising water stress and deforestation policies can drive up input costs and squeeze margins in some circumstances and for some companies. Exposure to carbon pricing can increase earnings volatility, which affects beta and ultimately raises the cost of equity. Lenders and insurers are beginning to price environmental risk into debt and premiums, which means corporate cost of capital is increasingly tied to how well companies manage sustainability. If we want to integrate sustainability into our enterprise valuation and ensure that our initiatives are financially sound—not just aspirational—we have to model these dynamics accurately. Equally importantly, we must be cognizant of which financial metrics are most critical to financial health and whether these are the most sensitive factors to sustainability risks. For example, earlier ventures typically live and die by free cash flow whereas larger companies may be much more sensitive to leveraged ratios. Matching the sustainability risk and opportunity to the appropriate line item can be the difference between critical and meaningless insights. At the end of the day, I see financial modeling as the essential bridge connecting sustainability goals, enterprise valuation, and fiduciary duties. By quantifying the financial implications of our net-zero targets, carbon transition risks, nature-positive investments, labor disruptions, and resource constraints, we can move beyond abstract narratives and deliver forecasts that truly guide action. This shift allows wise capital allocation, sets credible decarbonization paths, and communicates sustainability risks and opportunities in ways that matter to investors. For sustainability to be a core part of business strategy—not just a footnote in a report—we must embed it in our financial models. In today’s world of tightening regulation and growing risk, doing the math isn’t optional. It’s essential.
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