Your research is centered on the intersection of sustainability and digitalization. What made you choose that path?
During my master's in Business Innovation, I followed an additional certificate program at the University, which focused on understanding the intersection between climate change and business solutions. That's when I realized I wanted to dedicate my research to that field. When I saw the opening for a PhD on digital sustainability at at University of Potsdam, I was curious immediately.
When I started my PhD in 2023, only a few papers on the concept of digital sustainability had been published. One of the foundational papers defines digital sustainability as “the development and application of digital resources and communication technology for the benefit of the environment, society, and economic welfare” (Kotlarsky, Oshri & Sekulic, 2023). I found this focus on the shift of the role of technology beyond a purely economic logic really interesting.
In the society we live in, digital technologies have become indispensable, for the better and for the worse. The discussion at the intersection between digitalization and climate change has existed in the academic world for some years but remained quite fragmented. So instead of treating these two topics as separate debates, I became interested in understanding how they interact. Can digital systems support climate mitigation? Where do they create new risks? We need to bridge the two perspectives to find innovative solutions for advancing environmental sustainability without adding yet another layer of pressure to the natural environment. Finding this balance is the tricky part.
In your latest research, you focus on data for environmental sustainability. What kind of data are you interested in, and why is this data crucial for mitigating climate change?
To limit global warming, we must drastically reduce greenhouse gas emissions. If companies measure and disclose their emissions, they can provide vital information for governments and other political and economic stakeholders. That's how data becomes a lever for change.
The greenhouse gases companies emit are divided into different categories. My research focuses particularly on so-called scope 3 emissions. To illustrate what that means, here's an example: For a company producing smartphones, scope 1 emissions are caused by the company's on-site operations. Scope 2 emissions consist of the electricity, heating, and cooling the company uses. Lastly, scope 3 involves the upstream and downstream emissions along the entire value chain. For the smartphone company, this covers everything from the extraction of rare minerals required for the phone, to transportation, to how consumers charge the phone over its lifetime, and even how it is disposed of or recycled. Scope 3 emissions are often the largest share of a company's carbon footprint. Although different across industries, they represent on average 75% of a company’s total greenhouse gas emissions (CDP, 2023). It is almost impossible to measure the entirety of scope 3 emissions.
I interviewed companies that are making a big effort to accurately measure and possibly reduce their emissions. Unfortunately, they are confronted with challenges in precisely measuring their emissions. This accounting process should primarily rely on the data provided by the suppliers from which companies purchase their resources, but such data is not readily available in most cases. That’s why most companies rely on external, specialized databases. In some instances, this reliance on databases might be starting to show its limits, specifically with regards to the government-led ones.
In the current context of heavy environmental backlashes happening in many countries, the trustworthiness of such data sources might need to be more thoroughly explored and discussed in the future. Ultimately, both companies and policymakers require reliable data on greenhouse gas emissions along the whole value chain for effective climate action strategies.
Large amounts of scarce resources are required for digital technology, and AI requires lots of energy and water. That's why some people argue that digitalization will worsen the climate crisis instead of helping us combat it. What's your perspective on that?
Firstly, I would separate the discussion on digitalization from the one on AI. I believe that digitalization itself is not the core issue for climate change, as long as we are mindful about energy and hardware consumption (which is not yet the case, unfortunately). After all, without digital infrastructure, emissions reporting wouldn't be possible.
AI data centers, on the other hand, use huge amounts of electricity and water. The International Energy Agency estimates that by 2030, AI will amount to around 3% of total energy consumption globally (IEA, 2025). This is significant, especially when we remember that hundreds of millions of people still don't have access to electricity. Water use is an even less discussed issue. In some regions, large tech companies are already competing with local populations for water resources to cool data centers. This highlights the interconnectedness of environmental and social inequalities – and the way tech corporations are perpetuating these inequalities.
What deeply concerns me is the narrative that "we will figure it out". Many tech leaders and politicians argue that renewable energy will solve the climate crisis eventually. But what if renewables don't scale fast enough? We live on a planet with finite resources. Our very existence cannot be based on blind optimism.
This doesn’t mean I am against AI. There are clearly beneficial applications – for example in medical research or certain scientific domains. But do we need AI integrated into every consumer device? Do we need it in refrigerators and washing machines? Or is that driven more by economic growth logic than necessity and societal well-being
We should have an open societal debate about where AI adds real value and where it simply increases consumption and resource use. Digitalization can support environmental sustainability, but scale and purpose matter enormously.
Climate experts are saying it is unlikely we will stay within 1.5°C of global warming. From your perspective – especially regarding data – what should policymakers do to limit global warming effectively?
First of all, measuring scope 3 emissions should become mandatory globally, especially for large companies. This also means that governments should formulate detailed guidelines on the exact emissions they want to be reported. Regulatory clarity with consistent rules provides long-term stability for organizations. Secondly, to enable companies to track their emissions more easily, we desperately need more accurate databases and digital infrastructure.
Parallel to developing mitigation strategies, we must develop strategies for adapting to climate change. Even if we manage to reduce emissions significantly, it is likely that we will exceed 1.5°C earlier than expected. Many parts of the world are already experiencing the implications of climate change on a very real level. Resilience planning must become a priority at national and regional levels.
Lastly, the climate crisis is a complex issue that calls for holistic solutions. It will not be solved by one instrument alone – not by digitalization, not by reporting emissions, not by markets. We need a more fundamental political vision for a society that can thrive within planetary boundaries. Policymakers need to treat the climate crisis as the structural challenge it is. Market-based mechanisms like carbon trading may be part of the toolbox, but do we really just want to trust markets to self-regulate? Politics needs to hold large corporations more accountable for their greenhouse gas emissions to support them towards a profound environmental transition. Data can be a powerful foundation for developing that kind of coordinated action.
Thank you very much for the interview!
Sources:
Kotlarsky, J., Oshri, I., & Sekulic, N. (2023). Digital Sustainability in Information Systems Research: Conceptual Foundations and Future Directions. Journal of the Association for Information Systems, 24(4), 936–952. DOI: 10.17705/1jais.00825
CDP. (2023). CDP Technical Note: Relevance of Scope 3 Categories by Sector. https://cdn.cdp.net/cdp-production/cms/guidance_docs/pdfs/000/003/504/original/CDP-technical-note-scope-3-relevance-by-sector.pdf
IEA. (2025). Energy and AI. IEA. https://www.iea.org/reports/energy-and-ai
