“ THE EMISSIONS REDUCTIONS WE ENABLE ACROSS OUR CUSTOMER BASE FAR OUTWEIGH THE COMPUTE REQUIRED TO RUN OUR MODELS”
Ted Kornish Co-Founder and Chief Technology Officer Gravity
Critically, every change AI makes to data is logged so customers can always see what was modified, when and on what basis, which is what makes it defensible in an audit. In practice, that means your data is always current, traceable and you’ re not scrambling at year-end to pull everything together.
Q. HOW CLOSE ARE WE TO HAVING“ VIRTUAL COLLEAGUES” THAT CAN RUN ANALYSES AND EVEN DRAFT FULL SUSTAINABILITY REPORTS?
» Ted: Closer than most people realise. We’ re already past the point where AI is only useful for discrete tasks: a chatbot here, a feature there. The shift now is toward agents that take on entire workflows end to end, and at Gravity we’ re already running agents that automatically ingest and reconcile data across hundreds of sites, which is exactly the kind of multi-step work that points toward what comes next.
A sustainability team asking‘ draft our annual emissions report based on this year’ s data’ is a reasonable prompt today, not a future aspiration. Teams need to ask software providers about the breadth of tasks their AI can handle: the new standard is that AI can see and act on everything in your software, not just implement specific features.
Q. FOR SUSTAINABILITY TEAMS BUILDING OUT THEIR DIGITAL STRATEGY, WHAT KINDS OF WORKFLOWS SHOULD THEY START THINKING ABOUT DELEGATING TO AI AGENTS NOW?
» Saleh: The question every team should be asking is:“ what are we doing repeatedly that doesn’ t actually require human judgment?” Data collection is an obvious one, pulling utility bills, reconciling invoices, updating the emissions inventory. But it goes further. Variance analysis, flagging anomalies,
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