Environmental impacts and benefits of AI
The energy paradox of artificial intelligence
Italian companies adopt artificial intelligence with a clear objective: to become more efficient, competitive and also sustainable. However, behind the computing power of the servers, an invisible shadow continues to grow silently: the environmental impact of algorithms. Suffice it to say that, today, a single query on a language model (LLM) consumes up to ten times the energy required by a traditional search.
Artificial intelligence is neither inherently 'sustainable' nor inevitably harmful: it represents a vector whose net impact depends on the balance between its ability to optimize processes and its operating cost. The challenge is to prevent technological progress from becoming an unsustainable climate debt.
Measuring net impact: AI's carbon balance
At Up2You, we believe that to govern innovation, it is necessary to measure it. For this reason, in the white paper we introduce the concept of AI carbon balance: the clear difference between the footprint generated by the use of technology (IN Emissions) and the emissions avoided thanks to the optimization that AI allows to achieve (OUT Emissions).
The final balance of this balance sheet depends not only on the amount of technology adopted, but above all on the purposes of use. For example, AI applied to physical processes (such as logistics optimization or predictive maintenance) tends to generate emissions savings greater than the necessary computational footprint, while the prevailing use of generative AI risks driving the balance sheet into negative territory.
What you'll find in the free white paper
- A detailed explanation of how the AI carbon balance is constructed.
- The practical calculation of the carbon balance applied to 5 different types of Italian companies.
- The 4-step strategic roadmap recommended by Up2You to govern the environmental balance of the digital transition in your company.
- An in-depth look at the ethical commitment for responsible AI.
