Those working on corporate decarbonisation already know that the supply chain is where the majority of emissions sit, often above 80-90% of total emissions. What’s less understood is why, after years of net zero targets and growing internal reporting capability, so few of those targets translate into measurable reductions. That gap, between measuring Scope 3 and acting on it, is the real story, and it’s the problem AI is now best placed to help solve.
There is certainly no lack of ambition when it comes to sustainability, but there is a lack of action. All too often sustainability and procurement teams do the hard work of measuring their Scope 3 emissions, but aren’t sure how to turn that data into reductions. To overcome this hurdle, AI will be a critical tool as it is able to quickly gain oversight of the supply chain, identifying key emissions hotspots across thousands of suppliers, and process volumes of data that humans simply can’t at speed. Furthermore, AI can be used to model reduction scenarios and the impact of initiatives before investing additional time and resources.
The Scope 3 challenge
Organisations face four recurring barriers when it comes to addressing Scope 3 emissions.
The first is fragmented data. Relying on incomplete or estimated data makes it very difficult to identify where emissions really lie across a complex supply chain, and reliable data is the foundation everything else depends on.
The second is supplier ability. Engagement capacity varies hugely across a supply base: a large strategic supplier may have resourcing to measure and report, while a smaller supplier further down the chain may have never calculated a footprint at all, and has neither the budget nor capability to do so on request. One size fits all suits no one: it can overwhelm the suppliers who aren’t ready and underuse the ones who are.
The third is the ever-shifting regulatory landscape surrounding corporate emissions. Reporting requirements don’t just change frequently and vary by country, they can tighten in one market while relaxing in another, sometimes within the same year. That inconsistency makes it easy for a business to miss a requirement entirely, or to keep resourcing for a rule that no longer applies, and leaves companies spending more time interpreting rules than acting on them.
The fourth is the business case. The problem isn’t a lack of funding, it’s that decarbonisation is still framed as a cost rather than a value driver. The value is concrete: less exposure to energy price shocks, stronger supplier relationships, lower risk when disruption hits. Without that case made explicitly, programmes stall no matter how much ambition sits behind them.
AI as the solution
AI’s potential here is significant. Used well, it can bring fragmented data together at the source: normalising messy spend data and reducing manual cleanup, meet suppliers where they actually are on the maturity curve (for example, AI screening for those who’ve already disclosed, guided calculators for those measuring for the first time), keep pace with regulation by turning shifting requirements into concrete next steps, and help build the financial case that’s so often missing by putting a number on the cost of waiting, all while letting smaller teams do more with what they have. AI can drastically improve workflows and analytical output, and is best used with a human in the loop to orchestrate its work.
None of this makes AI a silver bullet. Its own environmental impact is currently front of mind, and work needs to be done on making data centres more environmentally friendly. These limitations, however, are outweighed by AI’s ability, when effectively deployed, to rapidly drive substantial decarbonisation, making the technology a net positive once all factors are considered.
AI now, not later
That gap between measuring emissions and acting on them won’t close itself. Timing and urgency is key. Organisations looking to decarbonise that fail to embrace AI in the near future will only find their data becomes more complex, themselves further behind regulation, and their emissions growing ever larger.
