- Bára is an influencer. What support does she need? Is she at risk of burnout? Are we too dependent on her?
- There's an isolated cluster around Monika. Why?
- Jakub is an outlier. Is that working for him? Is he an introvert? Does he need something different — has anyone talked to him?
Slack, Claude Code, from zero to first actionable insights in 30 minutes. And that's what I think strategic HR looks like in the age of AI. (* See note below about compliance.)
1. Data instead of gut feeling
Companies sit on mountains of data that already contain the truth about how people are doing and what results they're achieving. It's possible to move beyond eNPS, which correlates more with bonus cycle timing rather than with actual engagement. While being compliant (*).
2. AI assistants in processes
Interactive onboarding instead of reading policy documents, a chatbot that tells you where to get office supplies. An AI L&D coach for practice, as a complement to training. Focus on defining the right goals, not agonizing over OKR phrasing – a prompt handles that in 5 minutes. I consider this table stakes already.
3. Non-human Resources
When AI agents can handle a growing range of skills, it makes sense to think about how to combine human talents and machine capabilities side by side. Can we rethink competency models entirely?
4. Human Relations
How do we make sure AI works for people's benefit? We don't want people ending up – in the best case – with fractured attention and anxiety, in the worst case displaced by machines and left behind. I'm not talking about philosophical debates, but concrete practices for companies.
Next-generation HR will need to tackle all of this. Smart engineers can help with the data side, but the mindset has to live inside the HR team.
I'm looking for a new role where I can connect the world of people and technology this way. I'd love to be a partner to leadership — delivering a data-enhanced People strategy that attracts and develops talented people, drives results, and makes people genuinely thrive.
I've scaled a tech startup, led culture workshops, optimized HR processes, and I bring both psychotherapy training, and a GitHub account to the table. I've won Company of the Year (twice) and I'm #opentowork.
(*) To be fair, I've written this code as demo and proof-of-concept and at first I didn't think about compliance. And it got some backlash on LinkedIn. I am aware that legal compliance is a significant factor and a boundary. I am still ssure there is a lot of data you can analyze and stay legal, safe and fair. Note: this particular program was written by CC as a static code and was working with fictional meta-data, not real people, not even message contents.