top of page
uintent company logo

AI & UXR, CHAT GPT

The Environmental Impact of AI – Why Sustainability Also Matters for Digital Innovation

3

MIN

Mar 25, 2025

Why is the environmental impact of AI important? 

Artificial intelligence is changing our world. It simplifies processes, revolutionizes industries and offers numerous possible applications – from analysing medical data to automating business processes. But as AI's benefits grow, so does its environmental footprint. Many see AI as an invisible force that is integrated into systems ‘just like that’. But in fact, it is backed by an energy-intensive infrastructure with significant environmental impacts. Today, AI applications already consume as much energy as a large city. The central question is: how much environmental pollution can we afford, and do we want to afford?


The biggest negative environmental impacts of AI


Energy consumption and carbon footprint of large AI models 

AI is an energy guzzler. Particularly large models such as GPT-4 from OpenAI require enormous amounts of electricity for their training and application. A study by the Massachusetts Institute of Technology (MIT) shows that training an AI model generates as much CO₂ as five cars over their entire lifespan. Even more worrying: the global energy consumption of AI could be equivalent to the annual electricity demand of a large city like New York. (Source: https://taz.de/Oekologischer-Fussabdruck-von-KI/!5946576/)


Water consumption for cooling data centres 

Data centres that run AI models not only require electricity, but also huge amounts of water for cooling. In hot climates, this exacerbates water scarcity. For example, a data centre in West Des Moines, Iowa, used around 6% of the city's total water supply in July 2022. This is increasingly becoming a problem in water-scarce regions. (Source: https://www.nature.com/articles/d41586-024-00478-x)


Material consumption and electronic waste due to specialised hardware 

AI relies on specialised hardware such as GPUs and TPUs, which contain rare raw materials such as cobalt and silicon. The mining of these materials is not only ecologically questionable, but also socially problematic. In addition, rapid technological progress means that hardware is quickly replaced – with increasing amounts of electronic waste. (Source: https://www.t-online.de/digital/aktuelles/id_100416212/chatgpt-umweltbilanz-wie-viel-energie-die-ki-verbraucht.html)


Storage requirements for ever-larger amounts of data 

Machine learning and AI require enormous amounts of data to be stored. Studies show that the storage requirements of AI systems are growing by about 20% annually. More data means more energy consumption for storage and processing. (Source: https://journalofbigdata.springeropen.com/articles/10.1186/s40537-024-00920-x)


Inequality in access to AI 

The high energy requirements of AI make it a technology that primarily industrialized nations can afford. This widens the digital divide: while wealthy countries benefit from AI, regions with fewer resources are often excluded. (Source: https://www.dw.com/de/wie-k%C3%BCnstliche-intelligenz-der-umwelt-schadet/a-66305844)


Solutions: What can be done? 


‘Green AI’ and more efficient models 

Researchers are working on AI models with reduced energy consumption. One example is MIT's ‘Liquid Neural Networks’, which are more flexible and economical than conventional networks. (Source: https://www.wired.com/story/liquid-ai-redesigning-neural-network/)


Data centres powered by renewable energy 

Google wants to be carbon neutral by 2030 and is already using solar and wind energy in some of its data centres. Other tech companies are also optimising their energy sources. (Source: https://www.welt.de/wirtschaft/webwelt/article252321534/Googles-grosses-Oeko-Ziel-wackelt-aus-zwei-Gruenden.html)


Improve code efficiency 

Cleaner, more resource-efficient code saves energy. Developers can significantly reduce power consumption through optimised programming. Tools are available to identify inefficient code. (Source: https://www.hosteurope.de/blog/ki-code-generatoren-wie-ki-webentwicklern-hilft-code-effizienter-zu-schreiben-und-fehler-schneller-zu-finden/)


Location optimisation of data centres 

Cooler regions reduce the energy and water requirements for data centres. Iceland, for example, uses geothermal energy and the cold climate for particularly efficient server farms. (Source: https://reset.org/wie-wird-der-energiefresser-ki-nachhaltiger/)


Political incentives for sustainable AI 

Governments can provide incentives for sustainable AI research. Germany is funding projects for the resource-efficient use of AI. (Source: https://www.bmuv.de/pressemitteilung/grosser-schritt-fuer-ki-und-umwelt-bmuv-zeigt-erste-ergebnisse-der-green-ai-hub-pilotprojekte)


Sustainable use of AI in everyday work: practical tips 


  • Use AI tools efficiently: Avoid unnecessary requests.

  • Raise awareness: Every AI request costs energy, especially computationally intensive tasks.

  • Favour smaller, specialised models: A less energy-intensive solution is often sufficient.

  • Use long-lasting hardware: Modular, upgradable devices avoid unnecessary electronic waste.

  • Use green AI tools: Some AI applications rely on energy-efficient architecture.


With these measures, we can use AI more responsibly. Or just use our brains for a change. Well.

Podcast cover for episode 2 of “Beyond Your Business: Transitions” with two photos of Tara at different life stages.

Episode 5: The Future Starts Now – UX in Transition and Tara Right in the Middle of It

UX, BACKSTORY

Podcast cover for episode 2 of “Beyond Your Business: Transitions” with two photos of Tara at different life stages.

Episode 4: A New Outlook on Life – Tara, the Transition and Becoming Visible

UX

Stylized illustration of a brain and a neural network representing AI and machine thinking.

How a Transformer Thinks – And Why It Hallucinates

AI & UXR, LLM, HUMAN VS AI, OPEN AI

Podcast cover for episode 2 of “Beyond Your Business: Transitions” with two photos of Tara at different life stages.

Episode 3: From Corporate Life Back to Freedom: How Frustration Led to the Idea for Resight

UX, BACKSTORY

Podcast cover for episode 2 of “Beyond Your Business: Transitions” with two photos of Tara at different life stages.

Episode 2: Self-Denial, Growth and Crises: The Second Phase of Sirvaluse – And of Tara

UX, BACKSTORY

Three stylized characters with speech bubbles on a blue background – “Chattable Personas”.

Artificial Users, Real Insights? How Generative Agents Could Change the Field of UX

AI & UXR, HUMAN VS AI, LLM, TRENDS, UX METHODS, PERSONAS

Colorful illustration of a robot with a document and pencil on a light background.

Write More Clearly With Wolf-Schneider AI – A Self-Experiment

AI & UXR, OPEN AI

Dark designed picture as a podcast announcement. A picture of a baby and a man is shown.

Episode 1: ‘Inside and Out’ – A Podcast Series About Change, Responsibility and Self-Discovery

UX, BACKSTORY

Illustration with five colorful icons on a dark background, representing different AI systems.
Top left: Brain and lightbulb – “GenAI: Creativity”.
Top center: Book with magnifying glass – “RAG: Knowledge”.
Top right: Flowchart diagram – “MCP: Structure”.
Bottom left: Code window with arrow – “Function Calling: Access”.
Bottom right: Smiling robot – “Agents: Assistance”.

Five Types of AI Systems – And What They Do for Us

AI & UXR, CHAT GPT, LLM, OPEN AI

Illustration of a stylized brain (LLM) between a human profile and a bookshelf with a magnifying glass – symbolizes AI accessing external knowledge.

RAGSs Against Hallucinations – Well Thought Out, but Not Good Enough?

AI & UXR, CHAT GPT, LLM

Two people sit at a breakfast table using a tablet with the 'ZEITKOMPASS' app by Inclusys, which displays a colorful daily schedule and clock. The table is set with bread rolls, fruit, and coffee.

UX for Good With INCLUSYS: How We Learned to Better Understand Barriers in Everyday Life

ACCESSIBILITY, ADVANTAGES USER RESEARCH, RESEARCH, UX FOR GOOD

Woman in an orange shirt sits on a blue couch and looks at an interviewer and is laughing.

UX in Healthcare: The Essentials of Conducting Interviews With Patients

BEST PRACTICES, HEALTHCARE, RESEARCH, UX INSIGHTS

Illustration of a friendly robot learning from its mistakes.

Better Answers, Less Nonsense: How ChatGPT Learns

AI & UXR, CHAT GPT, HUMAN VS AI, OPEN AI

A visual representation of the environmental impact of AI, featuring data centers, energy consumption, and environmental effects.

The Environmental Impact of AI – Why Sustainability Also Matters for Digital Innovation

AI & UXR, CHAT GPT

Colorful illustration of a futuristic workspace with holographic AI interaction and structured prompts.

How to Work With Complex Prompts in AI: Structured Strategies and Best Practices

AI & UXR, CHAT GPT, OPEN AI

A humorous image on AI quality assessment: A robot with data charts observes a confused hamster in front of facial recognition, a pizza with glue, and a rock labeled as "food."

Anecdotal Evidence or Systematic AI Research – The Current Situation and What Still Needs to Be Done

AI & UXR, CHAT GPT, HUMAN VS AI, OPEN AI

Three talking businessmen, their silhouettes visible in front of a window.

Making the Case for UX Research: Convincing Stakeholders of UX Value

HOW-TO, OBJECTION HANDLING, STAKEHOLDER MANAGEMENT, UX

Futuristic cosmic scene featuring the glowing number 42 at the center, surrounded by abstract technological and galactic elements.

What ‘42’ Teaches Us About Change Management and UX

AI & UXR, CHAT GPT, OPEN AI, UX

An abstract humanoid outline formed of handwritten notes, books, and flowing ink lines in soft pastel tones, surrounded by a cozy study environment.

Who Are We Talking To? How the Image of ChatGPT Influences Our Communication

AI & UXR, CHAT GPT, HUMAN VS AI, OPEN AI

Illustration of the Turing Test with a human and robotic face connected by chat symbols.

Why Artificial Intelligence Still Can’t Pass the Turing Test

AI & UXR, CHAT GPT, HUMAN VS AI, OPEN AI

 RELATED ARTICLES YOU MIGHT ENJOY 

AUTHOR

Tara Bosenick

Tara has been active as a UX specialist since 1999 and has helped to establish and shape the industry in Germany on the agency side. She specialises in the development of new UX methods, the quantification of UX and the introduction of UX in companies.


At the same time, she has always been interested in developing a corporate culture in her companies that is as ‘cool’ as possible, in which fun, performance, team spirit and customer success are interlinked. She has therefore been supporting managers and companies on the path to more New Work / agility and a better employee experience for several years.


She is one of the leading voices in the UX, CX and Employee Experience industry.

bottom of page