Sofiya Pohurskyy

What sparked your interest in researching sustainability in global value chains?

What fascinates me about global value chains is that they are essentially the foundation of everything in our daily lives. The food we eat, the clothes we wear, the technology we use—none of it would exist without the vast and interconnected web of supply chains behind it. They reveal just how complex, interdependent, and fragile our global systems are. This complexity makes sustainability not just a moral imperative, but a logistical challenge of the highest order. At the same time, I’m deeply intrigued by how artificial intelligence is evolving within this space. It often starts with isolated applications—say, with one person optimizing logistics—but quickly scales and spreads, embedding itself across entire systems and networks. It’s like a digital veil that gradually extends over the supply chain landscape. Understanding how this ‘veil’ can either support or hinder sustainability is what drew me into this research.

What is the focus of your current research, and what impact do you hope it will have?

My research explores how AI can act as a catalyst for more effective sustainability governance within global supply chains. I look at it from multiple angles—technologically, organizationally, and ethically. How can AI be meaningfully embedded into corporate sustainability strategies? How can it enable more transparent decision-making across complex networks? And how can we ensure that it supports—not replaces—human responsibility? I combine empirical work with conceptual analysis, aiming to understand both what’s already happening in practice and what should be happening. Ultimately, I hope this research helps shape the way we design digital infrastructures: not just for efficiency, but for fairness, resilience, and ecological responsibility.

What do you see as the biggest knowledge gaps in sustainable global value chains?

One of the biggest gaps lies in the disconnect between technological potential and practical implementation. We know AI can support sustainability—but how do we integrate it meaningfully into governance structures that are often fragmented and opaque? We also lack systemic thinking. Too often, sustainability is treated as a checkbox or a separate track, instead of being embedded into every layer of decision-making. There’s still a lot to learn about how sustainability goals can be aligned with algorithmic logic—especially in a way that respects both data and people.

How do you hope to collaborate with others in this research network?

I’m looking forward to interdisciplinary exchange—particularly with colleagues from environmental sciences, data science, and business ethics. I believe that real impact happens when we combine perspectives and challenge each other’s assumptions. I’d also love to collaborate on joint case studies or empirical research projects that bring theory and practice closer together. Sharing data, tools, and ideas is essential if we want to tackle the sustainability challenges ahead—together.