Introduction
When I started my doctoral research, I thought I had to be certain—about my topic, my methods, even my future. But the deeper I go, the more I realise: research isn’t about certainty. It’s about curiosity, reflection, and learning to sit with complexity.
Right now, I’m exploring how Generative AI is reshaping leadership and organisational structures, especially in traditional industries like manufacturing. But I’m not just interested in the technology itself—I’m drawn to the human side:
- How leaders feel
- How teams adapt
- How stress and uncertainty ripple through the system
Three Lenses That Shape My Thinking
1. Systems Thinking
This approach helps me see the organisation as a whole system where one change (like introducing Generative AI) can trigger a chain reaction. A shift in technology might affect leadership roles, which then impacts communication, which then influences team morale, and so on.
It’s about seeing feedback loops and interconnectedness.
👉 Read Daniel Kim’s Systems Thinking Guide
2. Socio-Technical Systems (STS)
Developed by Trist and Emery in the 1950s, STS reminds us that organisations are made up of both social and technical systems. You can’t just drop in new tech and expect everything to work—you have to consider how it fits with people, culture, and structure.
👉 Explore STS at Tavistock Institute
3. Technostress
Even when technology is meant to help, it can create stress—especially when it’s fast-moving, complex, or poorly understood. The term “technostress” was coined by Craig Brod in 1984 to describe the psychological strain caused by digital technologies. Today, it’s more relevant than ever.
Closing Note
This blog is my space to think out loud, reflect on what I’m learning, and share the journey. I’ll be writing weekly—sometimes about theory, sometimes about practice, and sometimes just about the messy middle of figuring things out.
If you’re also navigating change, research, or the future of work, I’d love to hear from you. Let’s learn together.
A Thinking System 
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