By Chris Kirkpatrick
As companies explore the ways generative AI can transform customer and employee experiences, some may overlook the question of how well this technology aligns with their environmental, social and governance (ESG) goals.
A recent study found that creating a single image with an advanced Al model consumes as much energy as fully charging a smartphone.1 Another study suggests Chat GPT-3 "drinks" the equivalent of a 500ml bottle of water for every 10-50 responses it produces.2
Now, let's scale that up.
Imagine the cumulative footprint when these tools are employed across an entire multinational organization. That’s an environmental impact that companies today cannot afford to overlook as they consider their long-term strategic business objectives holistically.
Current generations in the workforce aren’t shy about voting with their feet, and taking business elsewhere if a company's values don't align with theirs.3 Meanwhile, regulatory initiatives like the Corporate Sustainability Reporting Directive (CSRD) set the stage for more standardized and enforceable corporate ESG practices.4
So how can your team execute a successful generative Al play without losing sight of these stakes?
Shift from an 'ESG' to a 'SEE' mindset
My day-to-day focuses on elevating employee and customer experiences. This has led me to a perspective shift when it comes to the question of sustainability: from an ESG to a SEE (social, economic, environmental) mindset.
The SEE mindset prioritizes ethical and social considerations. In the context of generative Al, it means evaluating the technology’s broader impact, beginning with its effect on your employees and customers. This might seem like a subtle pivot, but I’ve found that approaching sustainable practices with a people-first mindset is a powerful way to motivate and drive change. After all, the true value of a cleaner planet lies in ensuring it can be enjoyed by future generations.