It’s really exciting to see this conversation happening—AI absolutely has the potential to transform how ESG teams operate. That said, ESG is such a broad space, and AI could be applied in so many ways—from emissions tracking to supply chain transparency to regulatory reporting.
Our team has been exploring how AI can support ESG efforts, but what we’re still trying to understand is: where exactly can we help the most? If you’re part of an ESG team or working in this space, we’d love to hear—what’s one challenge you think AI could genuinely make easier?
What’s the most time-consuming part of your ESG workflow?
Finding The Right Templates
Benchmarking Peer Performance
Conducting Double Materiality
Inconsistent Supplier Data
AI is becoming an essential tool for ESG professionals because it can process large amounts of data quickly and identify patterns that humans might miss. From analyzing sustainability reports to monitoring regulatory updates, AI streamlines research and reduces time spent on repetitive tasks. One of the biggest advantages is the ability to get fast, reliable insights that support decision-making and reporting. For example, I’ve used platforms like askaiquestions.net, which allow you to ask ai and get free AI answers in seconds, and it has been a game-changer for speeding up my workflow. Integrating tools like this can really improve efficiency and accuracy in ESG work.
I think that the best work AI can do for as is small tasks like having 2 or 3 assistances. And content especially if the idea is your but you need to write it in a proper way, formal, professional etc.