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Most companies say they’re tackling Scope 3. Then they rely on averages and hope for the best. That’s not decarbonisation. That’s denial with spreadsheets.

In this episode, I’m joined by Paul Byrnes, CEO of Mavarick AI, to dig into one of the most stubborn blockers to real emissions reduction: bad data across global supply chains. Paul brings a rare mix to the table. Deep manufacturing roots, serious machine learning expertise, and a refreshingly low tolerance for AI theatre. We focus squarely on the climate challenge that keeps executives awake at night. How to cut Scope 3 emissions when suppliers are overloaded, data is unreliable, and margins are thin.

You’ll hear why most Scope 3 programmes stall before they deliver a single tonne of abatement. We dig into how spend-based accounting can introduce error rates of up to 40%, masking risk instead of revealing it. And why primary supplier data is fast becoming table stakes for any credible net zero strategy.

We also unpack where AI genuinely helps emissions reduction, and where it doesn’t. From cleaning contaminated data sets, to identifying real decarbonisation levers with financial and environmental ROI, this conversation is about using technology to move from reporting to action.

You might be surprised to learn why supplier engagement only works when there’s a clear win for suppliers themselves, and why emissions reduction scales fastest when it also improves cost, efficiency, or resilience. No greenwash. No magic bullets. Just physics, data, and incentives aligned.

🎙️ Listen now to hear how Paul Byrnes and Mavarick AI are helping manufacturers turn Scope 3 ambition into real, measurable emissions reduction.

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Credits
Music credits - Intro by Joseph McDade, and Outro music for this podcast was composed, played, and produced by my daughter Luna Juniper