Carbon Forecasting At Scale: How Data Science And AI Can Optimize Renewable Energy Procurement

The consumer electronics industry has long grappled with the environmental impact of connected devices, particularly when it comes to the energy consumption and consequently the carbon emissions associated with the usage of their sold devices. As companies strive to meet their sustainability goals, the focus has shifted toward enhancing carbon accounting methodologies and optimizing energy efficiency of such devices. Traditional approaches to measure device level carbon footprints have relied on broad estimates, making it difficult to implement precise decarbonization strategies. However, advancements in AI-driven analytics and real-time energy monitoring are reshaping how organizations can account for and mitigate the overall impact of their sold devices.

Zaid Thanawala has been instrumental in driving this transformation, pioneering new methodologies that bring greater accuracy and accountability to the Scope 3 emissions. With expertise in sustainability, data science, and energy analytics, he has supported companies transition to more accurate reporting. The approach of replacing estimated lifetime energy consumption models with energy consumption derived from real-time energy monitoring, improves the accuracy of calculating and reporting on the carbon emissions. “Accurate carbon accounting is the foundation of effective sustainability strategies. Without precise data, companies cannot take meaningful steps toward reducing their carbon footprint,” he explains. His work has enhanced Scope 3 Category 11- Use of Sold Products emissions reporting, refined energy efficiency strategies for consumer electronics, and enabled organizations to align renewable energy procurement with actual device energy consumption.

His contributions have led to significant improvements in carbon accounting accuracy, supporting organizations move away from static assumptions and towards more real-time insights. By integrating AI-driven data analytics into life cycle assessments, he enabled more precise emissions tracking, leading to more credible and impactful de-carbonization efforts. “The shift from projections to real-time data has changed the way companies approach emissions reduction. It is no longer about compliance, it is about actively shaping sustainability outcomes,” he notes. His forecasting models have also played a key role in renewable energy procurement agreements, ensuring that corporate sustainability commitments translate into real-world impact.

One of his key projects involved developing a carbon and energy forecasting model that enhances Scope 3 Category 11 emissions accounting by replacing lifetime energy consumption data of connected devices with actual annual energy consumption data. “For years, emissions reporting have relied on outdated methodologies that fail to capture real-world device usage. This tool bridges that gap, providing a more actionable and transparent approach,” he shares. His work has also contributed to industry-wide sustainability initiatives, collaborating with standards bodies to refine carbon accounting guidelines for IoT and consumer electronics. The methodologies he has helped develop have been published by The Carbon Trust, with multiple organizations committing to adopting this approach.

Navigating the complexities of Scope 3 carbon accounting has not been without challenges. Ensuring credible renewable energy matching required developing a strategy that directly links energy consumption to newly added renewable capacity. “Renewable energy procurement needs to be more than just a numbers game. It has to result in actual emissions reductions, and that means aligning supply with real demand,” he explains. Another major complexity was overcoming the inaccuracies of Scope 3 Category 11 emissions reporting, which traditionally relied on projected lifetime energy consumption. His work in integrating real-time monitoring has supported companies transition toward annual calculations, providing a more accurate and actionable framework for emissions accounting and reduction.

As the industry moves toward more dynamic sustainability solutions, he believes that automated, AI-powered energy tracking will become the standard. He also anticipates a shift toward adaptive energy efficiency, where devices optimize their power consumption based on usage patterns, reducing energy waste while maintaining performance. Looking ahead, he emphasizes the importance of investing in data-driven sustainability strategies now rather than waiting for regulatory mandates.

Organizations that integrate AI-driven energy tracking and renewable energy matching today for their sold devices, will be the ones setting industry standards for the future. By fostering cross-functional collaboration and embracing automation, Zaid has supported companies move beyond compliance and towards a more proactive and scalable sustainability initiative that has the potential to redefine the role of technology in Scope 3 carbon accounting and reductions.