Artificial intelligence is revolutionising the way we work, offering remarkable efficiency gains in research, data analysis, and communication. But this transformation comes with a cost. For environmental consultants, the use of AI presents a striking paradox: it saves time, yet contributes to the very environmental burden we aim to reduce.
As AI becomes more integrated into our work, it’s time to ask a critical question: what is the role of AI in environmental reporting?
AI´s huge energy demand
Let´s start directly with the elephant in the room, something that keeps us sustainability consultants busy everyday. The footprint of AI.
Behind every chatbot query lies a vast network of data centres, many powered by non-renewable energy and cooled with lots of (drinking) water. Since 2017, the energy consumption of data centres has surged, driven in large part by AI workloads. In the U.S. alone, data centres already account for 4.4% of total energy consumption. By 2028, AI could consume half of that share, equalling the electricity use of 22% of American households.
The environmental impact of our new digital co-worker is substantial. While calculating the exact carbon footprint of a single ChatGPT query is complex and varies based on the prompt's complexity and the data center's energy mix, the overall trend is clear: AI demands a massive amount of energy, and we are just at the beginning of this all.
In this article, we'll explore this paradox. We address:
- How AI currently supports environmental reporting
- Challenges and risks, from data quality issues to the potential for greenwashing
- Future of AI in sustainability reporting and the role of human consultant
How AI practically supports environmental reporting
Whether it's a full carbon footprint or a detailed product lifecycle assessment (LCA), the process involves navigating complex software and vast amounts of data. We've found that while the idea of a fully automated process is still a long way off, AI can perform as a facilitating and time-saving tool for tackling specific bottlenecks that cause some of our common delays.
For Hedgehog, we have the core rule to use AI as a co-pilot, instead of an auto-pilot. Having said that, besides smaller tasks in desk research, data analysis, and communication, AI is proving to be an assistant in two key areas:
- Enhancing the final report: Raw data and standard software outputs are rarely enough. A report needs to tell a story, provide clear insights, and be tailored to its audience, whether that's a board of directors, your customers, or a regulatory body. We use AI to translate complex datasets into clear dashboards, compelling visualisations, and actionable narratives. It helps us build a report that isn’t just accurate, but also meaningful for your specific business goals.
- Streamlining data export from software: Environmental reporting relies on specialised software that create complex datasets. One of the most common frustrations we see is getting the data out of these systems in a usable format. In some cases, we can use AI-powered tools to facilitate this process. This ensures that all the necessary data is formatted consistently, and ready for reporting, saving valuable time and preventing manual errors.
AI helps to streamline the technical work, allowing the consultant to concentrate on the strategic analysis and advice that the client needs.
A critical look at AI in sustainability reporting
Despite the benefits, we believe it is needed to approach AI tools with a critical eye. The promise of AI can be alluring, but there are significant challenges.
- The environmental impact of AI itself: As said in the beginning of the article the AI´s environmental footprint is undeniable. Using AI wisely is key. Following the principle of circular economy: refuse the use of AI if it is not necessary or beneficial to the process to avoid unnecessary energy consumption.
- "Garbage in, garbage out": This is the most important rule in data. An AI model is only as good as the data it’s trained on. Feeding incomplete or inconsistent data into an AI would produce beautifully presented but fundamentally misleading results. The expertise of the consultant is vital for validating the quality of your data before it’s ever used by an AI.
- The "black box" problem: Some AI systems can be opaque, making it difficult to understand how they arrived at a result. This is a major risk. When you report your environmental impact, you need to be able to explain your numbers. That’s why we only use tools that offer transparency and allow us to audit the calculations.
- The risk of greenwashing: AI can generate convincing reports that might hide or misrepresent data. As ethical consultants, we believe our role is to use AI to reveal the truth, not to obscure it. We use technology to provide genuine, data-driven insights that lead to real environmental improvements.
The future of AI in sustainability reporting
The integration of AI into environmental reporting is just beginning, and its future potential can be exciting. Today, AI acts as an assistant, but tomorrow it might become a more proactive partner. However, it is still speculation, we are closely following developments in several areas:
- Predictive analytics: AI could be able to accurately simulate the future carbon footprint of a new product line before you even commit to suppliers. Modeling the impact of different material choices or manufacturing processes, turning sustainability reporting into a strategic forecasting tool.
- Prescriptive optimisation: The next step beyond prediction is recommendation. Future AI won’t just identify problems; it could suggest the best solutions. For example, an AI could analyse an entire supply chain and not only flag the highest-emission transport routes but also recommend alternative, lower-carbon logistics partners or shipping methods that balance cost, speed, and environmental impact.
- Real-time, automated compliance: Environmental regulation is constantly evolving. In the future, AI will be able to monitor your company's activities in real-time, automatically checking them against the latest requirements of regulations like the CSRD. This will transform compliance from a stressful, periodic event into a continuous, automated process, flagging potential issues long before they become problems.
The human touch in an AI-enabled world is still irreplaceable
So, what is the role of AI in sustainability reporting? In short, it is a powerful tool that accelerates, simplifies, and streamlines time-consuming processes. AI promises radical changes, but it is not that advanced yet so it can replace the quality of a human consultant.
An AI can process data, but it cannot understand your unique business context in regard to LCA and/or carbon footprint rules or make nuanced strategic decisions. Also, AIs tend to hallucinate when solving complex issues that occur occasionally when performing LCAs or carbon footprints. That is where the quality of human (and Hedgehog) expertise remains irreplaceable.
As consultants, we bring the critical knowledge to make the right choices throughout the process. We have the flexibility to adapt and make adjustments, ensuring the final results are perfectly tailored to what you need. AI is a fantastic instrument as a co-pilot, but not (yet) ready to autopilot your environmental reporting.
Conclusion
AI is a powerful enabler. It helps us work faster, communicate better, and focus on strategic insights. But it also carries a significant environmental cost. The challenge, and responsibility, for consultants is to strike the right balance: using AI where it adds value, and avoiding it where it doesn’t.
Taking this into account, and only using AI where it is a valuable contribution to our work.
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