The ESG platform that centralizes your data, simplifies any regulatory framework and gives you information you can trust.

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Topics we opened during the session
Executive summary
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Topics we opened during the session

How does this actually work in practice with AI?
Inside Dcycle, AI sits on top of a structured ESG dataset. Once your emissions, supplier and operations data is in one model, a CFO or operations lead can ask plain-language questions, where are my biggest carbon costs, which supplier is dragging the average, what would Scope 3 look like next quarter, and get an answer in seconds. It is the same data you collect for CSRD, queried for a different reader.
What kind of savings can we realistically expect when we reframe ESG data this way?
The customers in the session were finding savings in the 2M to 15M EUR range, depending on the size of the operation. The mechanism is consistent. Connect emissions data to procurement, fleet and logistics, then identify the outliers, one bad supplier or one over-used vehicle, that account for most of the cost. Most companies have those outliers, they just have not run the analysis.
Does operational intelligence replace traditional CSRD or Scope 3 reporting?
No, it complements it. You still produce the regulatory report. What changes is the framing. The same dataset that satisfies the auditor also feeds the steering committee with cost, risk and exposure insights. One collection effort, multiple stakeholders. This is what avoids the duplicate work problem in the first place.
How do we bring this story to a CFO who still sees ESG as a cost centre?
Lead with the financial case, not the regulation. The shift from defense, we have to report, to offense, we can save money and reduce risk with the data we already collect, is the one that opens budgets. Bring one concrete number to the next steering committee, ideally a saving identified or a supplier risk avoided. Once the CFO sees the link to the P&L, ESG stops being a cost line and becomes a strategic dataset.

Executive summary

Why your ESG dataset is one of the most strategic assets in the business

After 25,000 conversations a year with ESG leaders across Europe, Dcycle uncovered something its team wasn't looking for. The same data sustainability teams collect for CSRD, Scope 3 and ESG reporting can answer the questions CFOs and CEOs ask every day, from fleet optimisation to supplier risk to CBAM exposure.

In this session, Jacobo Umbert and Davide Lauritano show, live with real customer data, how connecting AI to ESG datasets turns compliance work into operational intelligence.

The headline numbers from the session

  • 2,324 companies spoken with in one month (28 March to 28 April 2026).
  • 7,400 companies across Spain, Portugal, France, Italy, Germany and the UK in the last twelve months.
  • ~25,000 conversations a year with sustainability, operations and finance teams.

What changed when we plugged AI into the ESG database

  • A fleet review found that 5 vehicles accounted for 63% of CO2 per vehicle, with 7 rented vehicles showing zero activity.
  • A supplier audit surfaced one supplier with an emission factor 61 times higher than its US equivalent, with up to 15M EUR in potential savings.
  • A manufacturing customer is already implementing 2M EUR in cost reductions from the same dataset.

The three shifts to bring back to your team

  • Defense to offense. Stop talking about ESG as a compliance cost, start talking about it as a business asset.
  • Evidence beats Excel. A live, traceable dataset is more credible to a CFO than a quarterly PDF.
  • AI plus clean data equals board reports in minutes. Link sustainability to financial impact at the steering committee.

The mindset shift in one line

Stop calling it sustainability data. Start calling it business data. The rest of the company finally listens.

Dcycle reuses this same data for your carbon footprint. See it in a demo

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Schedule a 30-minute walkthrough with the Dcycle team. We will show you how to turn your ESG dataset into operational intelligence, with your own emissions, suppliers and operations data.

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