Human + Machine and Lyra Labs ran the AI-Native Employee Lifecycle Day with UCL's MSc People Analytics & Human Centric Management cohort. Five teams stepped in as the new People Leadership Team of Meridian Health, a fictional healthcare group with a traditional, siloed HR function. With AI at their fingertips, they had to redesign its employee lifecycle twice: once for capability, and once more for humanity.
Every design was scored publicly on two axes — AI maturity and humanism — because the most sophisticated designs can also be the most dystopian. From 9:30 to 5pm, the energy never dropped. Wave two was a working lunch, and nobody treated it as a break.
The questions changed
What stayed with us most was how the questions shifted. In the morning, some students were understandably in academic mode: "This data isn't provided." "What exactly do we submit?" "What are the marking criteria?" By the afternoon — after a curveball from the "board" and a hot seat where the voice of the employee asked, "I'm the nurse your system just scored. What does it know about me?" — the questions had become: "What outcome are we actually creating? Why does this matter, and for whom?"
Real work doesn't come with complete data or a rubric. The data was messy on purpose, the numbers had to be checked, and every decision was debated before it could be defended in front of the panel.
Why it works
That shift is the point. Watching students use AI, think about AI, and ask what it means for humanity — all in a single day — is exactly what applied AI learning should do. These are the people who will shape the future of work. As the course lead put it at the close, the hope is that every student leaves the programme like a warrior holding their weapons, ready to face reality. Days like this let students meet reality, not just receive advice about it.
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