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Topics Covered
- AI in the HR lifecycle
- The company and the tool
- The discovery
- The debate
- The fix and its impact
- Three takeaways
- Why this belongs to HR
Talk Citation
Covarrubias Venegas, B. (2026, October 29). AI in HR management and professional development: ethics, risks, and responsible practice [Video file]. In The Business & Management Collection, Henry Stewart Talks. Retrieved October 29, 2026, from https://doi.org/10.69645/YERY3915.Export Citation (RIS)
Publication History
- Published on October 29, 2026
Extended-form Case Study
AI in HR management and professional development: ethics, risks, and responsible practice
Published on October 29, 2026
22 min
A selection of talks on Management, Leadership & Organisation
Transcript
Please wait while the transcript is being prepared...
0:00
My name is Barbara
Covarrubias Venegas.
I have spent over 15 years
working with HR leaders
and organizations across
more than 15 countries
on questions of leadership,
learning, and
organizational development.
I also teach at the
university level,
which means I care
about both what
works in practice and what
the research actually says.
In this talk, I want to give you
a practice-oriented view of
the ethical risks of
AI in human resources.
The talk is grounded in
what's happened inside
one real organization
and connected
to principles you can
apply in your own.
0:42
Picture a Monday morning
talent review meeting.
Eight senior leaders
sit around the table.
A spreadsheet is
projected on the wall.
On it, every employee in
the company has a number,
their AI-generated talent score.
That number will
determine who gets into
the leadership development
program this year.
The leaders trust it.
It is based on data,
not gut feeling.
That is the whole point,
except the number is wrong,
not for everyone, but
wrong often enough,
and wrong in a pattern no
one at that table can see.
It is quietly pushing
women returning from
parental leave,
and employees
educated outside of
Western Europe toward
the bottom of the list.
No one designed it to do that.
The data did it on its own.
In a moment, I'm
going to take you
inside the European firm
where this happened.
I will show you how they
discovered the problem,
the internal debate
it triggered,
and the governance
changes they made.
That case sits at the
center of this talk.