ISSP 15 Years On: What’s Next for Our Profession?
Marsha Willard, Ph.D., SEP
ISSP Co-founder and Presidio Graduate School Faculty Chair Marsha Willard, PhD, SEP, shares insights into the emerging trends shaping our sustainability profession and how ISSP is enabling us to meet those challenges.
When I formed ISSP 15 years ago with my three colleagues, we talked about how, if we were successful at making sustainability standard practice, there would eventually be no need for the organization — or for sustainability professionals at all. At the time, organizations that had adopted sustainability were setting ambitious goals for 2020. It seemed so far off and plenty of time to put in place the simple and logical practices we all knew were needed, doable, and cost effective.
Well, here we are…coming toward 2024. Now the new target date has been pushed to 2050. While the goals are even more ambitious — complete carbon neutrality — the conditions that necessitate these goals have grown ever more dire. The things we were helping organizations to implement a decade ago, like reducing energy consumption and waste or using more efficient and benign production processes, seem almost quaint by today’s standards. Had we universally done those simple things — things that can return value to the bottom line and are just good management practices — we might be singing a different song now and maybe our profession would, indeed, be in jeopardy. Despite the good efforts that many leading organizations have made, it was all too little, too late. Nature has lost patience with our sluggish response and has way upped the ante.
Trends worth watching
In addition to the increased social and environmental pressures in all corners of the world, we are also seeing emerging trends that will have big impact on our profession and the demands placed on our organizations. Listed below are a few of the trends I’ve been watching and incorporating into my teaching.
- Demand for skilled sustainability professionals is growing. The GreenBiz 2022 State of the Profession Report cites an expansion in CEO interest in sustainability and a corresponding growth in headcount in related positions. The report writes, “For companies looking to staff up their sustainability department, the past 10 years have shown a marked increase in bringing in talent from outside the enterprise. A decade ago, 45 percent of new team members were hired from the outside whereas for the past six years at least two-thirds have been brought in from the outside.” In conversations within my own network, I hear that organizations are struggling to fill these positions and finding professionals with the appropriate training, skills, and certifications. Clearly, we are in demand and will likely continue to be for the foreseeable future.
- Investor pressure is pushing companies to commit and report. The European Union and the SEC in the US are establishing new reporting requirements on emissions and other social and environmental factors that could impact business performance and be material to investors. This will increase the need for accounting and reporting and the development of new strategies for accurately measuring impact throughout the value chain of the organization.
- Reporting standards are merging and consolidating. The growing pressure for companies to report is complicated by the plethora of reporting standards. Fortunately, the organizations managing these standards and related tools are merging and consolidating to simplify the process. The increased demand and complexity will drive a need for professionals versed not only in the standards, but in increasingly sophisticated accounting methodologies and processes for ferreting out data from multiple stakeholder groups.
- Disruptive technologies are increasing. With keen interest, I watch the technologies that will likely upend the way we operate in a variety of areas. Dropping prices in renewable energy and new technologies in the solar, wind, and hydrogen industries will both accelerate the transition as well as up the pressure to shift to net zero carbon. Emerging battery technologies married with developments in AI will upend our entire transportation system while advances in lab grown protein and vertical farming systems will reshape how and where food is produced and delivered.
Implications for the profession
I recently revisited ISSP's 2010 Competency Survey Report that we produced to identify core competencies for sustainability professionals. Seeking to assess its current relevance, I noted that many of the competencies we identified still hold, particularly those categorized as soft skills: skills in systems thinking, communication, strategic planning, building coalitions and, frustratingly, demonstrating the business case for sustainability. But I now also see emerging needs related to the trends mentioned above.
- Reporting and Accounting. The demand for reporting will draw not just on our communication skills, but also require familiarity with the shifting landscape of reporting frameworks like GRI, SASB, NetZero, CDP, ISSB, TCFD, Science Based Targets, and the Integrated Reporting initiative. It will also necessitate new abilities in accounting, tracking down data across multiple organizations and stakeholders, calculating the financial implications of activities, and required reporting on the material financial impacts of those activities.
- DEI and Supply Chain Equity. Despite political efforts to thwart it, I do not see decreasing organization demand for diversity, equity, inclusion, and justice efforts. Nor do I see decreasing organization requirements to address these issues in their supply chains, where they are especially complex and carry wide ranging implications. Sustainability professionals will have to navigate this complicated environment to bring employees, vendors, and board members along on the journey toward a more just and equitable business ecosystem.
- Beyond Sustainability. ISSP still keeps “sustainability” in its name, and I think it should. But ‘sustaining’ what we have now is insufficient to solving the world’s problems. What will we need to learn to move our organizations to be ‘regenerative’ instead of just sustainable? What will be the business practices we need to develop and deploy to give back more to society and the environment than we take in the process of delivering our value? Members of ISSP will be called upon to figure this out, just as we figured out sustainable practices 20 years ago.
Conclusion
I suspect ISSP will be around for many more years and that membership will continue to grow. I also suspect that the profession will continue to evolve and that it will be incumbent upon those of us working in the field to grow and flex with the ever-changing landscape that forms our work. I continue to stay involved with ISSP to ensure that I’m up-to-date and ready to meet the coming challenges. Here’s to at least another 15 years of building the legion of professionals dedicated to making sustainability standard practice across the workforce and around the world.
About the Author:
Marsha Willard, Ph.D., SEP
Faculty Chair, Presidio Graduate School
IMAGE: Ted Eytan
Read perspectives from the ISSP blog
Elizabeth Dinschel, MA, MBA, is the Executive Director of ISSP Earlier this month, we hosted our first global ISSP Town Hall since I stepped into the role of Executive Director. I logged off that call energized, humbled, and deeply grateful for the honesty, generosity, and care that our members brought into the space. This Town Hall was never meant to be a one-way update. It was designed as a listening session — a chance for ISSP leadership and staff to hear directly from sustainability professionals across regions, sectors, and career stages. And you delivered. What follows are a few reflections on what I heard, what we learned, and where we’re headed next together. Why We Called This Town Hall ISSP has gone through a period of transition — new leadership, new staff, and a renewed focus on modernizing how we serve a truly global membership. Change can be energizing, but it can also create moments of uncertainty and disconnection. We knew we needed to pause, gather our community, and listen with intention. The Town Hall brought together members from multiple continents, industries, and disciplines. Sustainability practitioners, consultants, engineers, communicators, policy professionals, and career-transitioners all showed up with thoughtful questions and candid feedback. One thing was immediately clear: this community cares deeply about its work, about each other, and about ISSP’s role in supporting sustainability professionals at a challenging moment for the field.
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?
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.