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

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.



About the Author:


Nicole Cacal, MSc, is


Executive Director, TRUE Initiative in Hawaii


Vice President on the Governing Board of ISSP



PHOTO: Image AI generated by author using Flux Pro by Black Forest Labs.


 

Read perspectives from the ISSP blog

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. 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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. 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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. 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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. 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By Ioannis Ioannou, PhD June 19, 2025
London Business School Professor Ioannis Ioannou, PhD examines the vulnerable narrative infrastructure surrounding ESG. By collaboratively engaging those most affected by ESG transitions—indigenous peoples, workers, young people, small businesses, and communities, particularly in the Global South—we can foster the trust, legitimacy, and collective commitment for meaningful progress. Who Gets to Tell the Story of ESG? For more than a decade, ESG rapidly evolved from a specialized investor consideration into an elaborate global infrastructure of standards, metrics, taxonomies, and disclosure frameworks. Investor attention soared, corporate sustainability teams grew exponentially, and ESG vocabulary— climate risk, fiduciary duty, and double materiality—became firmly embedded in corporate boardrooms and regulatory discussions globally. Yet, despite ESG’s impressive institutional and technical advancements, the narrative meant to support it remained remarkably fragile. While ESG developed sophisticated standards, disclosures, and metrics, it never invested in the narrative infrastructure to explain its purpose, build public understanding, or secure legitimacy beyond institutional circles. Without the broader stakeholder engagement and effective storytelling that would connect ESG to people’s lived realities, it became vulnerable. Critics didn’t need to challenge carbon accounting or materiality frameworks; instead, they recast ESG as a job killer, an elite agenda, or an unwelcome intrusion into everyday life. The backlash caught many ESG professionals off guard, though the warning signs were visible. ESG’s rapid adoption by investors and regulatory bodies created an illusion of momentum, but this obscured a deeper structural gap. ESG rarely connected meaningfully with those directly affected by ESG-driven transitions—workers facing disruption, small business owners adapting to shifting expectations, and communities, particularly in vulnerable regions, confronting real and immediate climate risks. For these groups, ESG often seemed abstract, distant, and disconnected from their daily concerns. Narrative infrastructure might sound like an unusual concept, but it's foundational to widespread support. It connects people and institutions, conveys meaning, and determines whether ESG is seen as genuine leadership or merely corporate branding. Robust narrative infrastructure ensures resilience under political pressure; without it, initiatives can rapidly lose whatever public approval they may have had. Constructing narrative infrastructure requires explicitly recognizing storytelling— and who contributes to that storytelling—as integral to ESG strategy, not simply a communications exercise. Effective narratives generate trust precisely because they emerge from transparent dialogue, clear accountability, and inclusive stakeholder engagement. By contrast, greenwashing uses storytelling deceptively, aiming to conceal poor performance, and deflect scrutiny. Strong narrative infrastructure, unlike greenwashing, strengthens credibility and legitimacy by openly connecting ESG commitments to shared realities, tangible actions, and measurable outcomes. It is a fundamental strategic asset for ESG success. Importantly, narrative infrastructure also concerns who gets to tell these stories. Over the last decade, the central narrators of the ESG story have largely been institutional actors: executives, investors, sustainability professionals, academics, and regulators. Their contributions have been invaluable, driven by expertise, rigor, and genuine commitment. Yet these narrators also represent a relatively narrow perspective, shaped by institutional backgrounds and professional incentives. Many important voices have remained largely excluded from shaping ESG narratives: indigenous people whose lives are often fundamentally changed by corporate activities, workers whose livelihoods are directly impacted by ESG transitions, young people deeply invested in future outcomes, small businesses continuously adapting to new ESG-related requirements, and especially communities—particularly in the Global South —directly facing the worst of climate disruptions. While these stakeholders' experiences occasionally appear within ESG reporting, they seldom influenced strategy or shape decisions in a substantial way. This exclusion poses significant, practical risks. Stakeholders naturally resist initiatives perceived as imposed from above or disconnected from their lived realities—not necessarily because they oppose ESG’s goals, but because they feel unheard and invisible within such ESG narratives. The resistance appears as political backlash, active public scepticism, or disengagement, all severely undermining ESG’s legitimacy, effectiveness, and public support. Addressing this critical weakness requires deliberately building ESG’s narrative infrastructure through inclusive, collaborative, and ongoing engagement. Practically, companies should move beyond occasional or reactive consultations toward sustained processes where stakeholders actively shape strategies. This can involve establishing community advisory boards with real decision-making power, participatory scenario planning that integrates diverse local perspectives, and internal cross-functional councils that ensure workers, communities, and youth voices directly influence ESG outcomes. Such sustained, authentic collaboration bridges the gap between institutional intentions and genuine public legitimacy. Within companies, narrative stewardship should not be limited to corporate communications or sustainability departments alone. Effective ESG storytelling depends on regular, structured collaboration across multiple functions—including strategy, human resources, procurement, product development, and finance—to ensure ESG commitments align authentically with core business decisions and reflect real-world stakeholder experiences. Companies can institutionalize this collaboration by creating dedicated cross-functional ESG committees tasked with integrating diverse internal perspectives, monitoring stakeholder feedback, and ensuring ESG initiatives clearly connect to tangible social outcomes. At an institutional level, building ESG narrative infrastructure involves establishing platforms that broaden participation in ESG discourse. It requires supporting initiatives that improve public understanding of ESG standards and practices, funding research that evaluates public perceptions of ESG alongside traditional financial metrics and ensuring ESG disclosures transparently reflect diverse stakeholder concerns. ESG narrative legitimacy grows stronger when diverse perspectives genuinely shape how ESG commitments are determined and communicated, implemented, and monitored—not merely as token inclusions, but as integral, strategic components of ESG itself. Regulators have an essential role in shaping ESG narrative infrastructure. Current ESG disclosure standards typically prioritize technical accuracy and financial materiality, mostly targeting investor needs. Broadening these frameworks to explicitly incorporate public legitimacy could significantly enhance ESG’s impact. For example, regulators could introduce clear criteria assessing whether companies effectively communicate their ESG strategies to diverse stakeholders and evaluate how these communications influence brand value and reputational risk—approaches already emerging in Europe’s Green Claims Directive and the CSRD/ESRS focus on double materiality. Additionally, policy evaluations could systematically measure whether ESG initiatives are genuinely perceived as fair, inclusive, and beneficial by the communities they affect. Public support and trust require deliberate and continuous effort; they cannot be assumed or taken for granted. Fortunately, inspiring examples of effective ESG narrative infrastructure already exist. Companies like Patagonia have openly integrated supplier and worker voices into their ESG narratives, transparently highlighting labour practices and sourcing standards, significantly enhancing their credibility. Unilever’s inclusive “living wage” campaigns have similarly leveraged stories from frontline workers to connect ESG metrics with tangible social outcomes, strengthening stakeholder trust. Industry-specific initiatives, such as the Bangladesh Accord in apparel, demonstrate how authentically incorporating diverse stakeholder experiences—including employees, unions, and community representatives—into ESG reporting can reinforce accountability and legitimacy. These examples highlight how inclusive storytelling, grounded in genuine stakeholder participation, can transform ESG commitments from abstract promises into credible actions with real-world impact. ESG professionals now face an exciting strategic opportunity: intentionally building a narrative infrastructure that's genuinely inclusive, collaborative, and resilient. Yes, involving diverse stakeholders means navigating complexity, dialogue, and occasionally tough compromises. It also means embracing participatory processes that might feel messier or less predictable. But it's exactly this diversity of voices and collective authorship that generates persuasive, robust narratives—ones that not only resonate widely but can confidently withstand shifts in politics, culture, and public sentiment. Beyond strengthening ESG's narrative infrastructure, it's important for ESG professionals to step back and consider sustainability more broadly. By explicitly linking ESG narratives to overarching sustainability objectives—such as respecting planetary boundaries and enabling a just transition—professionals can better illustrate how financial markets, corporate strategies, and policy frameworks actively support broader ecological and social well-being. Making these broader connections explicit can deepen trust, enhance engagement, and ensure the interconnected ESG-sustainability story resonates meaningfully with all those whose futures depend on it. We stand at a turning point, facing a critical opportunity to strengthen ESG’s narrative foundations. While ESG’s narrative fragility has been clearly exposed, this moment also offers an inspiring chance to intentionally build a more inclusive, credible, and resilient narrative infrastructure. The future of sustainability depends not only on rigorous metrics or detailed disclosures, but ultimately on whether those whose lives are impacted recognize themselves clearly in its story. By authentically amplifying diverse voices, explicitly connecting ESG initiatives to broader sustainability goals, and developing narratives rooted in real-world experiences, we can foster the trust, legitimacy, and collective commitment necessary for meaningful and lasting progress.
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