Using AI to transform ESG: Wayne Ching on decoding Scope 3

Wenwei (Wayne) Ching (MSc Environmental, Social, Governance (ESG) Management, 2024) is at the forefront of a new wave of sustainability professionals using AI to decode the complexities of ESG. With a top-ranked dissertation exploring Scope 3 emissions through natural language processing, Wayne blends technical precision with strategic insight. His work challenges traditional ESG reporting by surfacing hidden patterns in qualitative data—making it faster, smarter and more transparent. Now at Delta Electronics, he’s helping build systems that connect carbon management, energy platforms and global standards, showing how technology can elevate—not replace—human judgment in the race toward sustainability.

You’ve recently graduated from King’s with an MSc in ESG Management, where you earned the top dissertation mark for your work on Scope 3 emissions and natural language processing. What first drew you to combine ESG with data and AI, and how did your time at King’s—especially the support of your teachers and supervisors—shape that journey?

Before joining King’s, I had a solid technical background in mathematics, statistics and business data analytics and was confident using tools like Python. But I hadn’t yet found a way to apply those skills with real purpose.

A year before the programme, I worked on a project with the Bank of England using AI to analyse climate disclosures. That opened my eyes to ESG as a dynamic field—not just about compliance, but about driving meaningful change. The MSc in ESG Management at King’s stood out for its interdisciplinary approach, combining Climate Science, Economics, Regulation and Finance. It offered the depth and breadth I was looking for, with access to experts across disciplines in a fast-paced, immersive environment.

The support from faculty was key. Professor Luca Taschini’s Sustainable Finance module, in particular, was built around cutting-edge research and helped me approach ESG through a data-driven lens. That foundation shaped my dissertation, which used AI to analyse Scope 3 emissions and was recognised for its innovation.

Most importantly, the programme gave me the confidence to pursue ESG professionally. By combining technical skills with ESG insight, I was able to secure a role in the field soon after graduating.

At King’s Business School, we talk about 'Life-Changing Business'. From your perspective, what kind of impact do you hope your work at the intersection of ESG and AI will have—whether for businesses, communities or the planet?

ESG is transforming how businesses operate, especially in how they report and are evaluated. Traditionally, rating systems focused only on financial metrics, but ESG introduces a new layer—one that’s often qualitative, complex and difficult to standardise. That’s where AI can make a real difference.

AI isn’t here to replace human insight—it’s an agent that supports it. For example, analysing a 300-page ESG report used to require decades of experience. Now, with AI tools like natural language models, even junior analysts can surface key insights quickly and accurately. This helps accelerate and standardise ESG analysis, reducing inconsistencies and minimising human error—not because people are careless, but because qualitative interpretation can vary widely.

AI can also help uncover greenwashing by identifying whether companies are genuinely taking action or merely making vague claims. It allows us to go beyond the 17 core metrics of carbon reporting—that is, Scope 1, Scope 2 and the 15 categories of Scope 3 emissions—and dig deeper into the underlying methodology, stakeholder engagement and real-world impact behind the numbers.

Ultimately, I believe this work can empower businesses to be more transparent, help communities hold them accountable and contribute to a more sustainable and equitable future. That’s the kind of life-changing impact I hope to be part of.

Can you share an example where you’ve already seen technology and ESG strategy working together to drive meaningful change?

One area I find particularly powerful is the integration of IoT and AI systems. Take energy management as an example: IoT devices continuously monitor electricity usage across different appliances — for instance, a sensor in a refrigerator can detect precisely how much power it requires to operate. This detailed, real-time data is aggregated across the entire building and fed into the energy management system, where AI analyses usage patterns, identifies inefficiencies and recommends targeted improvements.

These recommendations draw on a solution database, allowing the AI to suggest proven actions—whether switching to more efficient devices or adjusting electricity inputs. This kind of integration between ESG strategy and technology not only helps reduce emissions and energy waste but also makes sustainability more actionable, measurable and scalable.

AI isn’t replacing human decision-making—it’s acting as a smart assistant, helping us make better choices faster and with more consistency. That’s the kind of meaningful change I want to be part of.

Looking at your current role, what do you see as the biggest opportunities—and the biggest risks—in applying AI to ESG reporting and compliance?

While AI offers incredible opportunities to accelerate ESG reporting—especially by aggregating data and reducing human error—it’s important to acknowledge the risks, particularly around creativity and originality.

AI models are built on existing data, which means they often replicate patterns and ideas that are already circulating. But ESG is a rapidly evolving field that demands radical, context-specific thinking. The best solutions come from people—drawing on their unique understanding of their company, tools, region and stakeholders. If we rely too heavily on AI, we risk creating a homogenised approach to ESG that overlooks the diversity of thought needed to drive real progress.

That’s why I see AI not as a replacement, but as a co-pilot. It can help us work faster and smarter, but the human value-add—our creativity, judgment and innovation—must remain at the centre. ESG will only move forward if we protect space for original thinking and ensure that technology supports, rather than overrides, that process.

Scope 3 emissions remain one of the toughest challenges for companies. How do you think AI and data innovations could accelerate progress here?

Scope 1 and 2 emissions have been tracked and regulated for over a decade, so the methodologies are well-established. But Scope 3 is a different story—it covers a wide range of indirect emissions across a company’s value chain, from suppliers to customers. The scope is vast and the methods for calculating it vary significantly between companies, creating uncertainty and making comparisons difficult. What are we comparing, if everyone’s using a different approach?

This is where AI can play a transformative role.

For example, some companies include termination clauses in supplier contracts, stating they’ll cut ties if emissions exceed a certain threshold. That’s a serious commitment—but it’s buried in qualitative data, not easily captured by traditional analysis.

AI can read ESG reports line by line, surfacing these kinds of agreements and assessing their depth—whether they apply to all suppliers or just a few, across regions or specific sectors. It can also identify other meaningful actions, like commuting policies or renewable energy commitments, and help distinguish genuine efforts from greenwashing.

By accelerating the analysis of qualitative data, AI helps investors, rating agencies and regulators identify true ESG leaders. It doesn’t replace human judgment, but it enhances it—making Scope 3 reporting more transparent, comparable and actionable.

Finally, looking to the future, what role do you hope to play in shaping the global ESG landscape?

When I first graduated, my goal was simple: to become an ESG analyst, using AI to interpret ESG reports and build smarter databases. But since joining Delta Electronics, my perspective has expanded. I’ve realised ESG isn’t just about reporting—it’s about action, platforms and systems that manage everything from carbon footprints to energy usage and labour practices.

Now, I’m working with experts across domains—learning about IoT-powered energy platforms, carbon management systems and global standards like ISO certifications. I’m building a toolkit that goes beyond AI and reporting, allowing me to engage with real-time data and understand the operational challenges companies face.

My ambition is to become a leader in ESG analytics—someone who not only understands the data but also the context, the platforms and the human impact behind it. I want to help shape standards, support transparency and ensure that ESG strategies are both innovative and grounded in reality. It’s a journey and I’m excited to keep learning, collaborating and contributing to a more sustainable future.

Have an interesting alumni story or experience to share? Contact us at foreverkbs@kcl.ac.uk.