Human & AI: Collaboration, Competition, or Something Else?
Which of my skills still matter as AI takes over more of my work?
Everyone’s quietly asking this question. Almost no one answers honestly in public. LinkedIn gives you hype. Conferences give you polished success stories. Your own team gives you a shrug.
So we are doing something different.
The event
Five organizations. Real AI deployments. Real talk.
Five organizations will tell you what really happened when they deployed AI. They will share the parts that failed, the roles that quietly changed, and the skills that lost value. No stage. No script. Just real experience.
The evening
75 people. Five stations. Everyone moves.
You’ll join a group of 15 and rotate through five stations, 20 minutes each. No rows of seats. No watching someone else’s slides from the back:
Real cases: An organization walks you through an AI deployment they actually shipped. What changed. What broke. Which skills gained value and which quietly stopped mattering. Five minutes of context, then you dig in.
Real talk: Sharp questions about our future with AI to encourage honest peer debates. The kind of conversation you usually only get after the second drink.
A facilitator at every station keeps things moving and captures where each group lands.
The part we are most excited about
Every group’s conclusions will be captured. At the end of the night, we will show you what the whole room thinks, including the questions where the five groups disagreed.
You will not just hear five organizations’ answers. You will leave knowing where 75 people in your field stand and how much they differ.
What you will take home
Real AI projects, including the failures — the things that never appear in case studies
A clear view of which skills people around you think are gaining or losing value
Peers you actually talked to, not just stood next to
A written summary afterwards, so you do not have to take notes
Who is in the room
Practitioners and business leaders who build and manage AI systems: data scientists, ML/AI engineers, MLOps and platform folks, heads of data, product owners, innovation leads, researchers from different areas, and people moving into the field.
Hands-on experience is normal here. We skip the basics and go straight to what was built, what it cost, and what did not work.
This is a Women in Data Science event — and like all our events, it is open to everyone.
Schedule
17:00 — Doors, registration, welcome drinks
17:20 — Welcome & opening
17:30 — Station rotations, five rounds of 20 minutes
19:30 — Closing & synthesis
19:45 — Apéro
21:30 — End