Shownotes
In this episode of the Future Proof HR podcast, Thomas Kunjappu sits down with Alim Dhanji, CHRO at TD SYNNEX, whose career spans HR, finance, M&A, and even serving as President of Adidas Canada.
From leading through supply chain crises to running startups and now driving an AI-first HR transformation, Alim shares how curiosity, simplicity, and critical thinking have shaped his leadership across every function.
He talks about reimagining HR as a series of products, helping teams overcome fear of AI through experimentation, and building a “super worker” culture—where technology multiplies human capability instead of replacing it.
Alim also reflects on why this is the most exciting moment to be in HR, how leaders can simplify for impact, and how embracing AI literacy and critical reasoning can redefine the next generation of people leadership.
Topics Discussed:
- Reframing HR as a product-driven function.
- Building an AI-first, digitally enabled HR team.
- Turning resistance to AI into experimentation and learning.
- Simplifying HR programs for real business impact.
- The rise of the “super worker” and the fall of technical gatekeeping.
- Why critical thinking is HR’s most future-proof skill.
- How AI creates capacity for more human leadership.
If you’re rethinking what it means to lead HR in the age of AI, this conversation with Alim Dhanji offers a rare look at transformation from both sides of the business—where strategy meets empathy, and technology powers people to do their best work.
Additional Resources:
Transcripts
I do think that this is the moment where HR
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professionals and HR leaders can
have a greater impact, not only in
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business, but helping to channel and shape
some of the implications of AI in society.
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We shouldn't forget that.
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And I think that creates purpose because
it is going to change the swim lanes
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of how people graduate, how people
learn, how many people are employed.
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Thomas Kunjappu: Hello and welcome to the
Future Proof HR podcast, where we explore
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how forward-thinking leaders are preparing
for disruption and redefining what it
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means to lead people in a changing world.
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I'm your host, Thomas
Kunjappu, CEO of Cleary.
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Today's guest is Alim Dhanji,
CHRO at TD SYNNEX, a dynamic HR
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leader and business executive
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whose unconventional career spans
multiple industries and functions.
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Alim has moved in and out of HR roles,
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serving as president of Adidas Canada,
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leading M&A strategy,
stepping into CFO duties,
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and even running a tech startup.
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Now as a seasoned CHRO, Alim
brings together commercial
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acumen, strategic HR leadership,
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and is even driving
AI-driven transformations.
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So he believes that
today's HR leaders must go
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beyond traditional functional
boundaries, using AI to deepen
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business understanding and becoming
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indispensable strategic partners
to the C-suite and the board.
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Alim, welcome to the podcast.
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Alim Dhanji: Thank you, Thomas.
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So wonderful to be here.
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I appreciate you inviting me.
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Thomas Kunjappu: So right off the bat, you
have a very unconventional career, I would
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say, coming in and out of HR in many ways.
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Could you tell us a little bit about that?
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Alim Dhanji: Sure.
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It wasn't designed that way, certainly.
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I've been in the workforce
now for roughly 27 years.
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And I've always been entrepreneurial
minded because of family upbringing.
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And I've always had this insatiable
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appetite for curiosity and
different cultures, et cetera.
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So I think that has ignited a growth
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mindset and constant
questioning of different
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operating models and
business environments.
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And so, yes, I started
out in HR and then I
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ended up taking a role in Asia,
moved to Hong Kong and got exposed
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to M&A type of work, which was
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fascinating, hyper-competitive,
especially in that part of the world.
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That only continued to spur my
curiosity for getting into business.
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And then I went to KPMG, where a year into
the role, I found myself also then leading
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finance, which was never in the cards,
but it certainly gave me a different lens.
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I went back into HR.
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Then I went to run a dating
app with the founder.
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That was phenomenal.
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That's probably a different
podcast on its own.
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You go along with these different
tours of duty and pick up
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not only a lens, but different
skills, different points of
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understanding around how to lead a team
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of engineers or how to elevate the role
that finance plays an organization.
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that kind
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of has been a pattern in my role.
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And then most recently, I was in the head
office of Adidas in a head of talent role.
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And my CEO asked me to take on
the president of Adidas Canada,
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which was phenomenal because
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especially the senior you get
transferring to that kind of organization.
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role is very rare and the
stakes are probably higher.
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But I did it nonetheless.
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And not only
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that, it was in the midst of COVID, it was
in the midst of supply chain disruption.
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So lots of
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opportunity for crucibles
and really learning.
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But now I find myself back in HR.
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My passion is people
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and culture, but I feel that because
of the different business rotations
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I've done, I can bring a unique lens
and elevate in doing so as well.
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Thomas Kunjappu: When you talk through
that trajectory, the question of
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identity almost comes to mind for me.
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a lot of folks define themselves
as let's say, I'm a student
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or I am an HR professional or an
athlete a specific in the work world.
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Like been in a specific function
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and I'm entrenched and really investing
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in what's happening in
this particular expertise.
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And how do you think of yourself?
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And maybe this is more belying my biases
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because maybe you don't
even think in this way
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in the professional world
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and you're talking about curiosity.
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But how do you, especially as you
go through these moments of pivot
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in terms of what you're actually
doing, did you find the way you
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identify yourself a shift in any major way
or did that, was that not even a question?
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Alim Dhanji: Probably
not an overt question.
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I think if anything, if I had to
pick a title, it would be student.
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It's lifelong learning.
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And having gone from large
corporates like Citigroup, where
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you've got nearly 300,000 people
across 180 countries, to a
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startup with 100 people, you've
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got to be agile and thoughtful
around how you show up and how
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you open yourself for learning.
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I went to KPMG, where it's a partnership
and across different sectors.
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So I think when you're
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doing that,
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the underlying red thread
is that you're a student.
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You're constantly learning and picking
up best practices and giving back.
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But I guess, yeah, I guess to
your question more specifically,
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am proud to be an HR leader.
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And the funny thing is when
I left HR to go to business
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and then came back to HR,
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a lot of the people in HR
said, why would you do that?
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Almost like it's a
negative to go back to HR.
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And the reality is where that is
where a lot of the change in the
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forward-looking business models are going.
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Think about the impact of AI,
demographic changes, geopolitics.
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They all have a massive influence
around how people show up.
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So being in HR, I think that this
is the perfect time to be in HR.
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Thomas Kunjappu: That's
a great perspective.
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And maybe another way to get at
the question is you mentioned the
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concept of tours of duty and
came from the military, but
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also in the corporate setting.
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Your typical employee is not
doing 25 years on a watch.
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You're going in, which was
the career path, right?
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You could start off right out of
high school or college and you work
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your way through to retirement.
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And there's a clear trajectory
and a career ladder.
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Companies have career ladders now,
but it's not for a specific person.
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It's more for the organization because...
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because people are coming in and
out and doing these tours of duty.
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Do you think that is becoming a
more central part, central to how
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HR professionals are developing?
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Alim Dhanji: I think so.
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I talk about tours of duty, they
can be within one organization.
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If you've got a large organization,
you can go from corporate
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functions to a P&L role,
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or you can go through different
functions to a P&L role, or you
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can go through different rotations
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within a corporate function.
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Also, I think you can go
to different countries
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if you're global environment.
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And so the learning can be constant.
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And it's not so much about a ladder,
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it's more about a lattice.
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It's about navigating the organization
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and picking up new capabilities
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and expanding your
employability in doing so as
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well.
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I do think that is a new generation.
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The new generation is also thinking about
leaving the company and coming back.
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So lots of boomerangs, then
there's gig works and portfolio.
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So this whole notion of portfolio
life, which is fascinating.
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So I do think that the
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traditional one organization
career ladder is no
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longer case.
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Thomas Kunjappu: So let's talk
about business impact and how
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the HR role is changing a little
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bit.
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And especially with the lens that you've
had coming in and that title, do you think
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your experience is shaping your
view of like HR's role specifically
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within the organization?
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Alim Dhanji: Yeah.
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So on one hand, when I stepped into the
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President of Adidas Canada role,
I was now on the receiving end of
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what I was pushing out from the
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talent role.
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And the team is fantastic.
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think that the team
produced ton of great value.
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But sometimes when you're removed from
the front line, you focus more on best
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practice and conceptual and strategy.
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And so what I found now is I was
receiving those best practices.
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But at the end of the day, the store
manager in their mid-20s has half
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an hour a week to absorb corporate
functions are putting on the
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marketing, loss prevention, finance.
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Everyone's giving them something.
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So my 30-page or 20-page
deck is not going to land.
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It's got to be pragmatic.
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It's got to be simple.
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It's got to be executable.
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And so I think lens by which I
look at how HR is being delivered
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has changed phenomenally,
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like fundamentally.
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it is about simplification.
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It is about impact and driving results,
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not just about best practice.
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Thomas Kunjappu: love this framing
and I'd love to push you to go, if
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you can give me any kind of specifics,
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is there something, if you want
to put yourself in the hot seat,
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something that you were
delivering in an earlier time
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as on the HR side to the business side
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that you feel like, oh, if
it was done this way instead,
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the impact would be more direct
or more actionable or more useful?
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Alim Dhanji: I think
there could be a range of
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products.
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I just pick on one, program
like onboarding, right?
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All the best practice say
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that when someone comes into
the organization, it's about
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balancing the hearts and minds and
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culture and what is the
company about, et cetera.
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Yes, that is true, but it
is also true that person
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who's coming in to sell shoes and
shirts needs to be operational
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within the hour kind of thing.
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we don't always have the luxury in
all roles to embed yourself in a
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week long learning about the culture.
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So I think that now, especially
with technology, we can reimagine
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what is onboarding and how
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does it start before you even
show up on the first day so
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that you give micro learnings
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in advance.
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But also, perhaps it's getting
them operational first, and
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then throughout their journey,
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Perhaps it's getting them operational
first and then throughout their
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journey, give them the right doses
of culture, inspiration, or what
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is the company about, rather than
bombarding them just from the start.
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Just one practical example.
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And it's not necessarily a profound thing,
but when you have a number of different
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HR programs, they start to compound.
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this is one way to simplify.
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Thomas Kunjappu: And looking at it
from the customer's point of view,
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it's like when they start to compound,
you look at it from store clerk's
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point of view, what just happened.
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I just spent a
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week in a room consuming all these like
PowerPoints, which then you forget about.
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That's a classic way to do it.
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So then let's talk about
AI a little bit more.
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How do you see just AI
changing the way HR is done?
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Alim Dhanji: You can't have a discussion
any day of the week without talking
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about AI.
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And it's, yes, there's a lot of AI
opportunity within HR, but quite frankly,
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permeating right across the organization
in every function, country, every role.
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But if I look
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at HR specifically, I started
this role about 16 months ago.
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And within the first 90 days, of course,
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after listening and paying attention
to what people need in the company,
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I got together with my senior
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HR leadership team and
we created a bold vision.
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And it started off with,
we will be an AI first
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digitally enabled HR function.
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And my entire team was not with me.
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They rejected that and I
didn't want to be directive,
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so I let it simmer for a couple of months.
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But as time went on and
everything that's happening now
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around how HR is absorbing AI,
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whether it's recruitment
or learning or onboarding,
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it's becoming real.
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And so I didn't force it
through, but I did set the bar.
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And what I found was that the
HR team grabbed onto the AI
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first digitally enabled concept.
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And now they love it, right?
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Because it set the tone around
how we support the business.
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And every product that we look at, so
look at HR as a series of products.
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And therefore, how do
you manage each product?
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And what is the design
thinking, et cetera?
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business.
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And every product that we look
at, so I look at HR as a series
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of products and therefore
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how do you manage each product and
what is the design thinking, et cetera.
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So we're looking literally at every
product to say, if we had to scrap
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this product and rebuild it, how would
we look at it with an AI first lens?
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done that with learning.
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We're now doing that with recruitment.
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And I can't wait to get started
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on performance because I think
that is going to be such a huge
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unlock around how we think about AI
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enablement through performance.
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But I could go on and on.
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The biggest area I think is probably
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unlocking transactional services
that HR is just so mired in.
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And there are so many platforms out there,
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but that look at automating and digitizing
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and creating consumer-grade experiences
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for your workforce to
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transact within, with the company,
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that just then creates all this capacity
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for HR to do different things.
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So there's both an effectiveness
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and an efficiency agenda for HR when
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it comes to AI.
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Thomas Kunjappu: Like with some of
the examples around like learning
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or recruitment, like there's,
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you could improve the candidate
or employee experience through
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these programs beyond what
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you were able to do with the
resources you had available.
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But then on the other hand, for example,
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with HR service delivery and
tickets and answering questions
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that can actually be more efficient,
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but also better for
employees at the same time.
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I want to hone in on a
little sub challenge that
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you've started talking about
there, which is bringing team
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along in a transformation as a
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mindset to be, let's say, be AI
native in this case, which there
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is resistance, I think, across
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the organization.
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Like you said,
287
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AI is impacting every
part of the organization.
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But let's stay specifically within HR.
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How did
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you think about guiding your team in this
direction, being firm, but also open?
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If you're talking to your peers who are
at the CHRO level, have that mindset, and
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at the organization level, there's this
buy-in towards reimagining the function.
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How would you go about translating
that into the organization
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itself or the function itself?
295
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Alim Dhanji: Yeah.
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So I think it's important
always to role model first.
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So I would share in our town halls,
even in our day-to-day interactions,
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how I'm using AI to
make myself productive.
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And it could be the most simple
example or something that's
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just innovative and complex.
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There are AI applications
out there where you
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could take a pretty dense annual report or
financial statement and put it in there.
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And it will produce a two-minute
podcast that you can listen
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to, which is in layman's terms.
305
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So what would normally take you
maybe 90 minutes to absorb and
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dense reading, not so exciting,
307
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you now have the gist of it within
a couple of minutes, which then
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sharpens your financial acumen.
309
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So I think you can go into a
meeting that much more prepared.
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But what else I did is with the team,
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We did a global hackathon.
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Alim Dhanji: This was almost about
eight or nine months ago, but we...
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We gave this challenge over 72 hours
to all HR colleagues around the world
314
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and said, come up with different ideas
of how you could leverage AI, whether
315
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it's efficiency or it's effectiveness.
316
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We want to hear them all.
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had no idea what we were going to get.
318
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I wasn't expecting any silver bullets.
319
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But what was amazing was that everyone
rallied and we got over 100 ideas and
320
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we picked the top 10 that we would then
321
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move forward for potential use cases.
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That is great.
323
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It's great to get that short list of 10,
324
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but what is even greater was just giving
people space and time to experiment
325
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and to try something different
and get comfortable with it.
326
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The resistance comes from the unknown.
327
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And there is a lot of fear because
the immediate thing that people go to
328
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when you talk about AI is it's just
for technologists, which I am not,
329
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or it's going to take over my job.
330
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And so why would I?
331
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I found the experimentation really helped.
332
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And then the third area is
about skills enablement.
333
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And there is no shortage of this.
334
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I don't think you need to
create that internally.
335
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You can go on MIT, Google.
336
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There's so many different options where
you could just go online and learn
337
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for free about different forms of AI.
338
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And if you're just using ChatGPT,
I think you're using like half a
339
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percentage point of what's really
available out there, right?
340
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So I think those three, there's
341
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probably more, but those three, I
would definitely say are fundamental
342
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and foundational in setting the
343
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tone around
344
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AI.
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Thomas Kunjappu: So then have you had
any reactions from the either HR teams or
346
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even we can go broader to the organization
as well, because we're talking about a
347
00:17:18,792 --> 00:17:24,512
whole workforce that is shifting, right,
and adapting to AI in their day to day.
348
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Any stories from the trenches?
349
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Alim Dhanji: Yeah.
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Shortly after I was visiting our
offices in Munich and I sat there
351
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and there were some presentations
and our head of comp for the region
352
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said, Oh, I want to show you.
353
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I just created our own
little GPT for comp.
354
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And that excited me.
355
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And what he did was one of the things
that comp people get quite often are
356
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job reviews, position profiles, because,
you know, you're going to reevaluate
357
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them and reassign a grade and then
attach a comp profile against it.
358
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And it's rinse and
repeat type of analysis.
359
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But now a GPT can do this.
360
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You load the job description,
it will analyze it against a set
361
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of variables that are defined.
362
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And then with the data from comp
surveys say, this job really looks
363
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like it's this grade.
364
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And if it's this grade, then
it'll be this comp range, right?
365
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So normally human intervention, probably a
couple hours with GPT, it's probably five
366
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to 10 minutes of some back
and forth, which then frees up
367
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capacity for the comp person
368
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and delights the manager that's.
369
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requesting it because they
get it really quickly.
370
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And probably you're
going to get additional
371
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intelligence from that chat interface
that you might not have had.
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So that was one really great
373
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example.
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On the other hand, I also got
feedback that, oh, wow, I'm
375
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scared because my job all day
376
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is to write job profiles.
377
00:18:51,998 --> 00:18:54,828
And now ChatGPT can
write it in 30 seconds.
378
00:18:55,238 --> 00:18:57,868
So that gives an opportunity
for us to have an open dialogue.
379
00:18:58,818 --> 00:19:00,958
And I don't want it to be threatening.
380
00:19:00,958 --> 00:19:04,688
So I don't want them to feel that
they're going to be exited next week.
381
00:19:05,378 --> 00:19:07,948
I want to give them time
and capacity to reskill.
382
00:19:08,868 --> 00:19:16,278
And I think that is an accountability and
something that leaders need to lean into
383
00:19:16,758 --> 00:19:18,308
so that we make sure that re-skilling
384
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is a benefit.
385
00:19:21,698 --> 00:19:25,948
And I got this from Tanuj,
who is CHRO and had a brand at
386
00:19:26,078 --> 00:19:27,598
Standard Charter, because this
387
00:19:27,598 --> 00:19:33,668
notion of re-skilling as a
benefit for employability is
388
00:19:33,668 --> 00:19:35,308
fascinating, especially now.
389
00:19:35,608 --> 00:19:38,798
If you've got a workforce that's
a bit nervous around what's going
390
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to happen to them, then we have a
responsibility as leaders to reskill
391
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and improve their employability.
392
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This has been a fantastic
conversation so far.
393
00:19:50,557 --> 00:19:53,347
If you haven't already done so,
make sure to join our community.
394
00:19:53,587 --> 00:19:56,257
We are building a network of the
most forward-thinking, HR and
395
00:19:56,257 --> 00:19:59,437
people, operational professionals
who are defining the future.
396
00:19:59,917 --> 00:20:02,527
I will personally be sharing
news and ideas around how we
397
00:20:02,527 --> 00:20:04,537
can all thrive in the age of ai.
398
00:20:04,897 --> 00:20:07,882
You can find it at go cleary.com/cleary
399
00:20:08,312 --> 00:20:08,922
community.
400
00:20:09,547 --> 00:20:10,387
Now back to the show.
401
00:20:12,234 --> 00:20:16,144
Thomas Kunjappu: And while it is
a responsibility, it can also be a
402
00:20:16,144 --> 00:20:21,794
competitive advantage in the labor
market if you are doing it well and are
403
00:20:22,044 --> 00:20:25,564
making that promise, especially in this
market, that's a great point and a good
404
00:20:27,914 --> 00:20:32,064
reframing of reskilling and
actually the L&D work and tying
405
00:20:32,064 --> 00:20:36,754
that HR function does, but
tying that to the engagement and
406
00:20:36,764 --> 00:20:38,204
outcome metrics potentially for
407
00:20:38,204 --> 00:20:39,054
the organization.
408
00:20:39,494 --> 00:20:43,044
But let's talk beyond AI to
just the future of how this
409
00:20:43,044 --> 00:20:43,722
function is kind of moving,
410
00:20:43,722 --> 00:20:48,074
But kind of moving, because in line
with your background of being curious,
411
00:20:48,074 --> 00:20:53,314
being a student, working with the
business as a client in HR, but then
412
00:20:53,314 --> 00:20:57,784
also being on that client side or on
the business owning P&Ls or trying to
413
00:20:58,489 --> 00:21:00,129
make things happen on a tactical level.
414
00:21:00,699 --> 00:21:08,379
How do you think HR professionals can go
from this tactical execution, which is an
415
00:21:08,399 --> 00:21:12,409
administration, which has been the
hallmark for a while, to becoming
416
00:21:12,499 --> 00:21:14,039
more influential, becoming true
417
00:21:14,039 --> 00:21:15,899
business partners within the organization?
418
00:21:16,689 --> 00:21:16,969
Alim Dhanji: Yeah.
419
00:21:16,969 --> 00:21:20,424
So I always think about,
maybe it's the M&A
420
00:21:20,569 --> 00:21:22,479
background in me, but do you divest?
421
00:21:22,479 --> 00:21:23,279
What do you acquire?
422
00:21:23,409 --> 00:21:23,671
What do you give up?
423
00:21:23,729 --> 00:21:25,379
What do you pick up?
424
00:21:26,019 --> 00:21:30,074
And so I do think that we're all
constrained in terms of time.
425
00:21:30,229 --> 00:21:31,564
Finding an hour in the week is
426
00:21:31,564 --> 00:21:32,724
difficult at best.
427
00:21:33,614 --> 00:21:37,524
And so you have to figure out how you're
going to divest and whether, again,
428
00:21:37,524 --> 00:21:42,964
going back to AI, if you can
leverage AI to make yourself more
429
00:21:42,964 --> 00:21:45,184
productive so that you can carve out
430
00:21:45,394 --> 00:21:48,634
an extra hour or 90 minutes in your week,
431
00:21:48,994 --> 00:21:51,334
then that liberates you
to pick up something new.
432
00:21:52,454 --> 00:21:55,914
And if you're sharpening
your P&L or financial
433
00:21:55,914 --> 00:21:59,474
or business acumen, I think
the one greatest benefit of
434
00:21:59,474 --> 00:22:01,714
AI is that it has technology.
435
00:22:01,724 --> 00:22:05,924
taken down the gatekeeping
of technical expertise.
436
00:22:07,394 --> 00:22:07,694
Right?
437
00:22:07,754 --> 00:22:12,654
If I'm going into a meeting and
I'm, and actually this is a true
438
00:22:12,724 --> 00:22:14,424
scenario where we're redesigning
439
00:22:14,424 --> 00:22:18,414
or reimagining some of our
compensation programs in equity,
440
00:22:18,634 --> 00:22:20,814
which is so hardwired to our financial
441
00:22:20,834 --> 00:22:21,464
metrics.
442
00:22:21,754 --> 00:22:26,944
And we want to be innovative,
but also want to be in compliance
443
00:22:26,964 --> 00:22:28,374
with, we're a public company,
444
00:22:28,374 --> 00:22:29,424
not a private equity.
445
00:22:30,044 --> 00:22:35,714
But I could use chat GPT or
other forms of AI to really
446
00:22:35,714 --> 00:22:38,724
teach myself around why looking
447
00:22:38,724 --> 00:22:45,844
at free cash flow versus return
on equity or certain type of other
448
00:22:45,844 --> 00:22:51,784
financial metric, you can quickly have
a discussion that gives you the right
449
00:22:51,784 --> 00:22:56,064
confidence and capability to
have that sort of debate with
450
00:22:56,244 --> 00:22:57,724
the CFO or other leaders.
451
00:22:57,994 --> 00:22:58,814
So technical
452
00:22:59,534 --> 00:23:02,274
gatekeeping is now no longer an issue.
453
00:23:03,084 --> 00:23:06,214
And so you don't necessarily
have to go to business school.
454
00:23:06,214 --> 00:23:10,684
Sure, going to business school
teaches you things and it gives you a
455
00:23:10,684 --> 00:23:11,584
broader depth.
456
00:23:11,594 --> 00:23:15,789
But if you're at a career level where you
don't want to go back to business school,
457
00:23:16,659 --> 00:23:18,049
I think AI is a big unlock.
458
00:23:18,059 --> 00:23:19,419
And I think that should be leveraged.
459
00:23:20,869 --> 00:23:22,859
Thomas Kunjappu: I just want to go
deeper on this particular use case,
460
00:23:22,859 --> 00:23:25,279
because I think from a couple of angles,
461
00:23:25,289 --> 00:23:28,159
first of all, I think there's a
good example of the kind of thing
462
00:23:28,169 --> 00:23:30,729
that deeper new work that AI,
463
00:23:30,759 --> 00:23:34,239
it's an example potentially of a
new work that AI enables because
464
00:23:34,319 --> 00:23:36,329
it's very easy to think about
465
00:23:36,559 --> 00:23:38,859
the kind of work that we're
doing today that goes away.
466
00:23:39,479 --> 00:23:42,029
But in this case, I would argue there's a
467
00:23:42,029 --> 00:23:45,459
kind of thing that maybe wouldn't
really get done maybe at a public
468
00:23:45,469 --> 00:23:47,729
company with a major huge ROI
469
00:23:47,739 --> 00:23:49,889
to getting the comp
structure exactly right.
470
00:23:50,239 --> 00:23:52,179
But for a lot of other
companies, this kind of work
471
00:23:52,179 --> 00:23:53,219
may not actually ever get done.
472
00:23:53,229 --> 00:23:58,019
Or if it does, in this case,
you're doing some complex modeling
473
00:23:58,029 --> 00:23:59,519
about how the compensation
474
00:23:59,519 --> 00:24:04,479
program might impact free cash
flow or the return on stock.
475
00:24:04,859 --> 00:24:10,359
And those things would really, I
would imagine in yesteryear, involve
476
00:24:10,369 --> 00:24:15,559
meetings, including someone in financial
operations or an analyst who is saying,
477
00:24:15,559 --> 00:24:16,809
okay, now you've got some homework.
478
00:24:16,839 --> 00:24:22,599
Come back with a model or build a
custom spreadsheet where we can make
479
00:24:22,599 --> 00:24:24,789
some tweaks, make some assumptions
and have a bunch of meetings together.
480
00:24:25,049 --> 00:24:28,879
But that could happen by yourself
more dynamically and you can get some
481
00:24:28,899 --> 00:24:32,489
answers more rapidly, which I think
the other part of what you're saying
482
00:24:32,509 --> 00:24:34,099
is it also is helping you.
483
00:24:34,339 --> 00:24:37,509
If you're curious, it's not
just about doing things,
484
00:24:37,519 --> 00:24:39,839
it's also about teaching
you things, right?
485
00:24:39,839 --> 00:24:42,709
So you should be able to
use general purpose AI
486
00:24:43,019 --> 00:24:45,519
to help you learn areas of the business.
487
00:24:45,599 --> 00:24:46,289
I guess in this case,
488
00:24:46,289 --> 00:24:48,469
we're talking about just
how to read a P&L statement
489
00:24:48,499 --> 00:24:51,069
and also the impact of the,
490
00:24:51,439 --> 00:24:54,119
in this case, compensation
and how it would impact that.
491
00:24:54,119 --> 00:24:56,489
But really, arguably
any product, as you say,
492
00:24:56,489 --> 00:24:59,559
or program from HR, if you want
to match it to, or think about
493
00:24:59,769 --> 00:25:01,379
ROI or think about how it impacts
494
00:25:01,859 --> 00:25:06,749
the P&L, you could do a similar
kind of exercise and teach yourself.
495
00:25:07,599 --> 00:25:07,909
that.
496
00:25:07,959 --> 00:25:10,009
Alim Dhanji: And it applies
to so many different areas.
497
00:25:10,099 --> 00:25:13,819
I've implemented value change
initiatives in other companies.
498
00:25:13,819 --> 00:25:17,079
And in the past, especially in
global companies, when you're rolling
499
00:25:17,079 --> 00:25:19,189
out values, it's not just about
500
00:25:19,189 --> 00:25:21,079
the organizational corporate layer.
501
00:25:21,299 --> 00:25:27,139
It is how are those values going to sit
in Mexico versus China versus Botswana.
502
00:25:27,669 --> 00:25:30,919
And typically, you would have
had to spend a small fortune
503
00:25:30,919 --> 00:25:32,469
on an external consultant who
504
00:25:32,469 --> 00:25:37,459
has a background in anthropology
or whatever to stress test it
505
00:25:37,459 --> 00:25:38,979
for you and give you a report
506
00:25:38,989 --> 00:25:42,649
that says, this is where we have concerns
and this is what you should consider.
507
00:25:42,659 --> 00:25:44,049
We just did that.
508
00:25:44,344 --> 00:25:45,494
We implemented our values.
509
00:25:45,494 --> 00:25:47,184
In fact, we're launching them next week.
510
00:25:47,854 --> 00:25:53,644
And before we had the discussion at
the ELT, we put it through a GPT.
511
00:25:55,594 --> 00:25:58,084
And I said, we operate in these countries.
512
00:25:59,424 --> 00:26:03,284
We want to make sure that our coworkers
understand and connect to the values,
513
00:26:03,294 --> 00:26:09,724
which countries should I anticipate
sensitivity and what I got back was
514
00:26:09,984 --> 00:26:12,574
something amazing and it was a table
515
00:26:12,584 --> 00:26:16,674
that helped me think through things
and I and I met with each of the
516
00:26:16,674 --> 00:26:17,954
presidents in our regions and I
517
00:26:17,954 --> 00:26:21,614
shared them they said yes that's
exactly correct and we should
518
00:26:21,614 --> 00:26:23,164
think about this word being a bit
519
00:26:23,164 --> 00:26:26,974
too aggressive in some parts of
the world this might be perceived
520
00:26:26,974 --> 00:26:29,394
as a dare or we have dare to go
521
00:26:29,684 --> 00:26:31,444
that might be perceived
be perceived as a threat.
522
00:26:31,894 --> 00:26:33,104
So how do we augment that?
523
00:26:33,104 --> 00:26:35,364
And so that it was
together, we dare and go.
524
00:26:35,364 --> 00:26:38,764
And that makes it a
little bit more accepting.
525
00:26:38,854 --> 00:26:42,204
But that piece of work, A,
would have taken us weeks to do.
526
00:26:42,974 --> 00:26:44,604
It would probably cost $100,000.
527
00:26:45,814 --> 00:26:48,074
And we did this in a couple hours.
528
00:26:49,414 --> 00:26:49,654
Right?
529
00:26:49,654 --> 00:26:53,839
So productivity, efficiency,
effectiveness, speed.
530
00:26:53,839 --> 00:26:58,199
So you delight the CEO because you got
this sorted within a short period of time.
531
00:26:58,549 --> 00:27:03,279
I could give you endless examples
of how AI is changing everyone's
532
00:27:03,329 --> 00:27:06,399
role and how they could lean in and
be more effective and efficient.
533
00:27:08,449 --> 00:27:12,279
Thomas Kunjappu: So if you take all
of these, there's so many use cases
534
00:27:12,279 --> 00:27:14,109
and examples that we were just like
535
00:27:14,369 --> 00:27:15,519
peppering in throughout, right?
536
00:27:16,079 --> 00:27:19,379
If you add them up all together
and you look to the future,
537
00:27:19,799 --> 00:27:24,259
what is the function look like?
538
00:27:26,709 --> 00:27:26,929
Do you imagine?
539
00:27:26,929 --> 00:27:29,579
Let's say, give it a
five-year horizon, right?
540
00:27:30,569 --> 00:27:34,249
What is going to be different about what
people are doing tactically, day-to-day?
541
00:27:34,289 --> 00:27:40,529
What's being demanded or what is a demand
sucked in from both employees and boards
542
00:27:40,559 --> 00:27:43,069
and executive teams from the function?
543
00:27:43,709 --> 00:27:46,399
And of course, how can we
all get ready for that.
544
00:27:46,999 --> 00:27:47,329
Alim Dhanji: Yeah.
545
00:27:47,769 --> 00:27:51,719
So the notion of super worker,
I think it is true, but
546
00:27:51,729 --> 00:27:54,579
connecting the super worker to a
547
00:27:54,639 --> 00:28:00,159
unlock of technical gatekeeping
for various disciplines then
548
00:28:00,159 --> 00:28:01,449
creates an opportunity for
549
00:28:01,459 --> 00:28:05,689
those that excel in critical thinking and
550
00:28:05,689 --> 00:28:13,129
change leadership, reasoning, articulating
some information and storytelling.
551
00:28:14,179 --> 00:28:16,999
By the way, those are all
portable capabilities, right?
552
00:28:16,999 --> 00:28:21,439
And not specific to a discipline,
finance or HR or marketing.
553
00:28:21,649 --> 00:28:23,489
Those are general capabilities.
554
00:28:23,984 --> 00:28:29,614
If you have someone with that and then
they're leveraging AI the right way,
555
00:28:30,444 --> 00:28:32,654
you don't need the
expertise in compensation.
556
00:28:33,464 --> 00:28:37,034
You don't need the expertise
of 10, 15 years in learning
557
00:28:37,034 --> 00:28:38,964
and development or in benefits
558
00:28:39,004 --> 00:28:44,074
administration, because AI is going to
be able to make that available to you.
559
00:28:44,584 --> 00:28:46,954
It's about writing the right prompt.
560
00:28:47,674 --> 00:28:50,244
It's about then taking that
information and then applying
561
00:28:50,244 --> 00:28:51,364
critical reasoning saying,
562
00:28:51,864 --> 00:28:52,814
does this make sense?
563
00:28:52,814 --> 00:28:54,634
Is this the right thing
for an organization?
564
00:28:55,094 --> 00:28:56,664
You're still going to
have to implement it.
565
00:28:56,694 --> 00:28:58,804
So then what's the change
leadership around it?
566
00:28:59,964 --> 00:29:02,284
So to me, it is about the super worker
567
00:29:02,664 --> 00:29:05,214
who can take vast amount of information.
568
00:29:06,024 --> 00:29:07,724
They don't have to be
the technical expert.
569
00:29:08,634 --> 00:29:13,324
It is literally the layer of
being able to take information,
570
00:29:13,324 --> 00:29:16,344
storytell it, and make meaning of it
571
00:29:17,544 --> 00:29:19,584
fit for purpose for the
organization that they're in.
572
00:29:19,594 --> 00:29:19,764
Thomas Kunjappu: That
573
00:29:22,554 --> 00:29:25,394
leads to an important question then.
574
00:29:25,544 --> 00:29:30,954
What would, if that's the case, and you're
talking to early career professionals
575
00:29:31,254 --> 00:29:33,314
who are just, or maybe someone who's
576
00:29:33,314 --> 00:29:35,024
just in college at the moment, right?
577
00:29:35,094 --> 00:29:38,084
And they're thinking about getting
into the HR field or that's
578
00:29:38,084 --> 00:29:40,504
what they're like studying for,
maybe even doing a master's in it.
579
00:29:40,949 --> 00:29:42,044
What kind of advice would you
580
00:29:42,044 --> 00:29:44,794
have for those kinds of
folks given that future?
581
00:29:45,904 --> 00:29:46,894
Alim Dhanji: It's a challenge.
582
00:29:46,904 --> 00:29:52,264
I honestly empathize with new grads
right now because we haven't in
583
00:29:52,264 --> 00:29:54,924
society adopted that superworker
584
00:29:55,304 --> 00:30:00,134
model and we haven't in organizations
created the stratification
585
00:30:00,514 --> 00:30:02,204
of how many humans and how
586
00:30:02,204 --> 00:30:03,294
many agents we need.
587
00:30:04,464 --> 00:30:05,394
I think it's coming.
588
00:30:06,014 --> 00:30:08,714
So we're there right now in
a little bit of a limbo and I
589
00:30:08,714 --> 00:30:12,424
know so many smart people who've
just graduated and cannot find
590
00:30:12,424 --> 00:30:16,364
work because the consulting firms are
not recruiting as much as they used to.
591
00:30:17,054 --> 00:30:18,544
so I think that there's
592
00:30:18,604 --> 00:30:20,094
going to be a period of ambiguity.
593
00:30:20,614 --> 00:30:27,604
What I would say to them is lean in
into those portable capabilities of
594
00:30:28,384 --> 00:30:33,864
critical thinking, understanding how
to leverage and harness storytelling.
595
00:30:33,864 --> 00:30:34,284
These are all
596
00:30:34,284 --> 00:30:37,594
important capabilities that I
think are going to become that
597
00:30:37,594 --> 00:30:39,514
much more critical going forward.
598
00:30:40,644 --> 00:30:45,154
I go back to another experience I had
when I got this Adidas president role.
599
00:30:45,704 --> 00:30:46,964
My then CEO, Casper,
600
00:30:46,964 --> 00:30:50,234
also sent me, and I was
privileged to do this.
601
00:30:50,354 --> 00:30:52,964
It was really difficult, but
I was privileged to go to
602
00:30:53,414 --> 00:30:55,044
Harvard for the AMP program.
603
00:30:56,554 --> 00:31:00,794
And what they do really well
is, we went through 180 cases,
604
00:31:01,194 --> 00:31:05,424
different companies, and you learn
everything about Disney to Starbucks
605
00:31:05,424 --> 00:31:06,964
to all kinds of different cases.
606
00:31:07,354 --> 00:31:08,684
What they're actually teaching
607
00:31:08,684 --> 00:31:13,194
teaching you is not to be an expert
as a technologist or a finance leader.
608
00:31:13,204 --> 00:31:13,524
They're
609
00:31:13,524 --> 00:31:17,664
teaching you critical thinking with
the data that you have available.
610
00:31:17,674 --> 00:31:17,838
Okay.
611
00:31:17,838 --> 00:31:18,978
So now I take that.
612
00:31:20,118 --> 00:31:24,128
And if I've learned some critical
thinking there, that's great.
613
00:31:24,568 --> 00:31:26,008
But the data that you have available
614
00:31:26,008 --> 00:31:29,408
now is endless, right?
615
00:31:29,408 --> 00:31:30,068
Think about that.
616
00:31:30,078 --> 00:31:33,948
So it's not just the data you
have available at your fingertips.
617
00:31:33,948 --> 00:31:34,508
You now
618
00:31:34,508 --> 00:31:39,098
with ChatGPT or any form of AI,
you can get all kinds of data,
619
00:31:40,128 --> 00:31:41,398
but then it's too much data.
620
00:31:41,398 --> 00:31:41,548
So
621
00:31:41,548 --> 00:31:44,238
how do you bring that back and
converge and diverge and make
622
00:31:44,268 --> 00:31:45,668
meaning of it and then implement
623
00:31:45,938 --> 00:31:46,988
a sound strategy?
624
00:31:47,478 --> 00:31:49,458
So it's exciting, but it's also scary.
625
00:31:50,278 --> 00:31:55,903
But I come back to critical thinking
as being the one capability that we
626
00:31:56,208 --> 00:31:57,438
really need to lean into.
627
00:31:59,343 --> 00:32:03,243
Thomas Kunjappu: Let me push back a little
bit on this one concept about not that
628
00:32:03,243 --> 00:32:07,373
critical thinking, storytelling, these
meta cognition skills are not important.
629
00:32:07,383 --> 00:32:08,433
Obviously, they are.
630
00:32:08,943 --> 00:32:12,773
And yet using like software engineering,
for example, like a software engineer
631
00:32:12,983 --> 00:32:18,773
is best positioned to prompt an
AI agent to create software for
632
00:32:18,773 --> 00:32:22,163
them that is not buggy and that's
performant and production ready.
633
00:32:30,043 --> 00:32:34,963
to create an AI agent that will help
them or work with AI in a way that
634
00:32:34,963 --> 00:32:39,413
will produce results that you can
actually reliably stand behind and
635
00:32:39,413 --> 00:32:41,918
recommend in polite conversation.
636
00:32:42,028 --> 00:32:42,798
And even forgetting the
637
00:32:42,798 --> 00:32:47,218
hallucinations, just the idea
that you're able to converse in
638
00:32:47,218 --> 00:32:49,208
depth on this particular field and
639
00:32:49,208 --> 00:32:53,423
topic versus asking maybe more basic
questions if you weren't there.
640
00:32:53,448 --> 00:32:56,043
Isn't there still, I guess
what I'm getting at, isn't
641
00:32:56,043 --> 00:32:59,098
there still role for expertise,
642
00:32:59,128 --> 00:33:02,978
in-depth knowledge beyond
the metacognition skills,
643
00:33:03,008 --> 00:33:06,278
which are important to get
into any particular topic
644
00:33:06,278 --> 00:33:08,788
because there will still
be specialties, right?
645
00:33:08,788 --> 00:33:10,378
And people who are really good
646
00:33:10,378 --> 00:33:12,428
in using the latest technology available
647
00:33:12,428 --> 00:33:15,528
to get outcomes that are best in class.
648
00:33:17,378 --> 00:33:19,688
Alim Dhanji: My hot take is for now, yes.
649
00:33:20,428 --> 00:33:26,038
Because we haven't yet gotten
into a full agentic workforce.
650
00:33:27,118 --> 00:33:28,198
But you're right.
651
00:33:29,068 --> 00:33:34,218
At some point, it'll take a
compensation expert coupled with
652
00:33:34,218 --> 00:33:35,808
someone who's probably a technologist
653
00:33:36,078 --> 00:33:38,858
to create an agent that can do exactly
654
00:33:38,858 --> 00:33:40,188
what that comp person could do.
655
00:33:40,648 --> 00:33:41,518
We're not there yet.
656
00:33:42,198 --> 00:33:47,638
And so right now we're
using general GPTs and AI
657
00:33:47,648 --> 00:33:50,193
to extract knowledge
and make meaning of it.
658
00:33:51,473 --> 00:33:54,493
But we're fast moving towards
agentic opportunities.
659
00:33:54,513 --> 00:33:55,833
And so when we get there,
660
00:33:56,923 --> 00:34:00,013
I do think that the technical
roles will no longer be needed.
661
00:34:00,023 --> 00:34:04,593
You're going to focus more on
what do you do with the outcome
662
00:34:04,593 --> 00:34:06,043
of what that agent's producing.
663
00:34:06,053 --> 00:34:12,973
Again, I'm not a futurist, but
that's what I'm seeing, the trend.
664
00:34:13,092 --> 00:34:13,963
go towards.
665
00:34:14,543 --> 00:34:20,723
I'm not a lawyer, but I worked
through just more recently
666
00:34:20,723 --> 00:34:22,233
creating a power attorney for
667
00:34:22,233 --> 00:34:22,822
my mother.
668
00:34:22,833 --> 00:34:25,922
Normally I'd go and pay 500
bucks and have it written.
669
00:34:26,733 --> 00:34:27,443
I wrote it.
670
00:34:28,103 --> 00:34:29,473
Now, again, I don't
671
00:34:29,473 --> 00:34:33,322
know if it's hallucinating or not,
but I wrote it in minutes, tweaked it.
672
00:34:33,652 --> 00:34:34,373
And then I have a phone
673
00:34:34,373 --> 00:34:34,922
a friend, right?
674
00:34:34,922 --> 00:34:36,713
So right now I just send
it to lawyer friend.
675
00:34:36,713 --> 00:34:38,072
I said, I don't want to pay.
676
00:34:38,533 --> 00:34:38,632
Can
677
00:34:38,632 --> 00:34:39,443
you take a look at it?
678
00:34:39,463 --> 00:34:40,963
And they did.
679
00:34:40,963 --> 00:34:42,253
And so it's pretty sound.
680
00:34:42,723 --> 00:34:43,023
Thomas Kunjappu: Yeah.
681
00:34:43,043 --> 00:34:43,853
Alim Dhanji: You know, it's pretty
682
00:34:43,853 --> 00:34:44,233
sound.
683
00:34:44,243 --> 00:34:45,973
So why would I go?
684
00:34:46,243 --> 00:34:49,233
So I think this is going to
continue to proliferate at the point
685
00:34:49,233 --> 00:34:52,663
where you're going to probably
have an agent that specializes
686
00:34:52,663 --> 00:34:54,303
in power of attorneys.
687
00:34:56,822 --> 00:34:57,373
Thomas Kunjappu: It makes sense.
688
00:34:57,373 --> 00:35:01,953
And at some point, the burden of proof is,
right now, the burden of proof is on the
689
00:35:04,703 --> 00:35:07,043
LLM for anything that is of import.
690
00:35:07,073 --> 00:35:09,683
So in this case, you want to get
this right if you're going to
691
00:35:09,693 --> 00:35:11,623
actually get this document signed.
692
00:35:11,623 --> 00:35:13,323
So you're putting a human in the loop.
693
00:35:13,553 --> 00:35:18,013
But maybe at some point, that
will be 9,999 times out of 10,000.
694
00:35:18,933 --> 00:35:23,103
It's just just getting it right and
so people flip to it being completely
695
00:35:23,403 --> 00:35:23,763
autonomous
696
00:35:24,623 --> 00:35:26,653
Alim Dhanji: yeah it's that it's that
validation rule right now there's
697
00:35:26,653 --> 00:35:31,143
definitely validation we are exploring
for example we do hundreds of rfps
698
00:35:31,143 --> 00:35:32,963
and rfps if you've ever written one
699
00:35:33,513 --> 00:35:37,143
two to three weeks at least right
depending on the how big the
700
00:35:37,143 --> 00:35:39,983
initiative is yeah i can literally do
701
00:35:39,983 --> 00:35:43,053
that now in an hour with
some back and forth.
702
00:35:43,663 --> 00:35:44,403
But I would
703
00:35:44,413 --> 00:35:49,263
be uncomfortable putting out an
RFP, responding to a client with
704
00:35:49,263 --> 00:35:51,123
it just going through our system
705
00:35:51,813 --> 00:35:54,393
and not having being reviewed by a human.
706
00:35:54,613 --> 00:35:56,433
So you still need a validation layer.
707
00:35:56,963 --> 00:35:57,743
And that might be
708
00:35:57,743 --> 00:36:02,123
a lawyer, that might be a salesperson
or a marketing person in future.
709
00:36:02,163 --> 00:36:02,583
I don't know.
710
00:36:02,633 --> 00:36:06,243
I think that a number of agents will
look at that RFP and comment on it.
711
00:36:06,783 --> 00:36:09,333
There might be some kind of DocuSign.
712
00:36:09,403 --> 00:36:11,773
There's got to be, that's
got to be where we're going.
713
00:36:13,803 --> 00:36:16,603
There are pros and cons to it
from a society perspective,
714
00:36:16,603 --> 00:36:19,093
from what this means for jobs.
715
00:36:19,093 --> 00:36:20,818
I'm not advocating for it.
716
00:36:22,188 --> 00:36:24,188
But I also have to accept that's
717
00:36:24,228 --> 00:36:25,378
probably where we're going.
718
00:36:25,708 --> 00:36:28,328
And so we have to think about
what are the implications.
719
00:36:29,398 --> 00:36:29,568
Thomas Kunjappu: Right.
720
00:36:29,698 --> 00:36:32,838
And the time horizon for that could
be, there's a lot of debate about that.
721
00:36:33,128 --> 00:36:33,568
We're talking
722
00:36:33,568 --> 00:36:38,438
about like fully agentic and not
to mention like AGI, but there's
723
00:36:38,438 --> 00:36:40,108
a clear trajectory that we can't
724
00:36:40,118 --> 00:36:40,608
ignore.
725
00:36:40,908 --> 00:36:43,748
And we've also talked about a lot of
things short term that we should be
726
00:36:43,748 --> 00:36:48,438
doing right away within the HR function
or not to future proof ourselves.
727
00:36:48,488 --> 00:36:53,228
Now, just to close out, you brought
up this concept of a super worker.
728
00:36:53,918 --> 00:36:57,048
Could you just explore that concept
a little bit more in depth for us?
729
00:36:58,223 --> 00:37:02,123
Alim Dhanji: think there are probably
multiple definitions and someone's
730
00:37:02,123 --> 00:37:02,823
probably got the right definition.
731
00:37:02,823 --> 00:37:02,831
I think there are probably
multiple definitions and someone's
732
00:37:02,831 --> 00:37:03,283
probably got the right definition.
733
00:37:03,283 --> 00:37:10,273
In my lens, it is someone who is
leveraging AI to make themselves so
734
00:37:10,273 --> 00:37:14,303
much more effective and efficient.
735
00:37:15,273 --> 00:37:17,413
And so what normally you do in
736
00:37:17,573 --> 00:37:23,623
40 hours, you might be able to do
in 30 or 25 hours, but you don't
737
00:37:23,633 --> 00:37:25,133
slack off for the other 10 or 15.
738
00:37:26,223 --> 00:37:27,063
You do more.
739
00:37:27,063 --> 00:37:32,033
And so actually you're
getting expansion, right?
740
00:37:32,033 --> 00:37:34,183
So 40 hour week, if that's
741
00:37:34,183 --> 00:37:38,003
what you're doing, you're probably
doing 70, but you're not working 70.
742
00:37:39,293 --> 00:37:43,563
I think that I see some of those
individuals in our organization who
743
00:37:43,563 --> 00:37:50,193
have just harnessed AI so brilliantly
that they're turning things around much
744
00:37:50,213 --> 00:37:52,063
quicker than they were in the past.
745
00:37:53,223 --> 00:37:55,663
And there's less back and forth.
746
00:37:56,753 --> 00:37:57,983
They're over delivering.
747
00:37:59,143 --> 00:38:01,953
So I do classify them as a super worker.
748
00:38:04,533 --> 00:38:05,433
Thomas Kunjappu: That's great.
749
00:38:05,593 --> 00:38:06,263
Thank you for that.
750
00:38:06,293 --> 00:38:10,333
And for the broader conversation,
Alim, are there any closing
751
00:38:10,333 --> 00:38:11,423
thoughts you want to share
752
00:38:11,423 --> 00:38:16,553
with us as you to mark this moment in
time where we're just in this transition?
753
00:38:17,023 --> 00:38:19,983
You specifically for folks
coming newly into the labor
754
00:38:19,983 --> 00:38:21,153
market, we talked about there's
755
00:38:21,153 --> 00:38:22,703
a lot of uncertainty and
it's really for everyone.
756
00:38:22,733 --> 00:38:26,543
There's uncertainty about where
things are headed specifically.
757
00:38:26,943 --> 00:38:29,313
What do you look forward to the most?
758
00:38:30,973 --> 00:38:32,823
Alim Dhanji: I mean, like all
conversations, they end up
759
00:38:33,383 --> 00:38:34,948
focusing so much more on AI.
760
00:38:35,303 --> 00:38:38,993
And so I do think that is
where the direction is.
761
00:38:39,003 --> 00:38:44,063
But if I raise the aperture there, it
is such an amazing moment to be in HR.
762
00:38:45,323 --> 00:38:48,893
And as I think about other
leaders who've left HR more
763
00:38:48,893 --> 00:38:50,743
recently, like Lina Nair, who left
764
00:38:51,373 --> 00:38:56,118
HR at Unilever now, is a very
successful CEO of Chanel and
765
00:38:56,128 --> 00:38:58,418
blowing the numbers out at the park.
766
00:38:58,468 --> 00:39:01,888
I do think that this is the moment
where HR professionals and HR leaders
767
00:39:02,358 --> 00:39:05,688
can have a greater impact, not only in
768
00:39:05,688 --> 00:39:12,198
business, but helping to channel and shape
some of the implications of AI in society.
769
00:39:12,508 --> 00:39:13,608
We shouldn't forget that.
770
00:39:13,608 --> 00:39:18,288
And I think that creates purpose because
it is going to change the swim lanes
771
00:39:18,288 --> 00:39:22,358
of how people graduate, how people
learn, how many people are employed.
772
00:39:22,758 --> 00:39:24,228
So get really excited about that.
773
00:39:24,268 --> 00:39:28,433
Maybe it's the geek in me, but super
exciting moment for us to be there.
774
00:39:28,613 --> 00:39:29,683
And we shouldn't shy away.
775
00:39:29,683 --> 00:39:29,743
I
776
00:39:29,743 --> 00:39:33,763
think we should just grab it
by the horns and go for it.
777
00:39:34,783 --> 00:39:35,273
Thomas Kunjappu: I love that.
778
00:39:35,283 --> 00:39:36,503
And if you have
779
00:39:36,503 --> 00:39:42,023
a growth mindset, you're a constant
student when the game on the field
780
00:39:42,038 --> 00:39:43,643
is changing, data is changing.
781
00:39:43,973 --> 00:39:46,793
It's just an opportunity to learn more.
782
00:39:46,823 --> 00:39:49,783
And because new knowledge
is available for the taking.
783
00:39:49,958 --> 00:39:52,553
Thank you for this wonderful
conversation, Alim.
784
00:39:52,553 --> 00:39:57,993
I think there's a lot of value for
fellow CHROs and people operations
785
00:39:57,993 --> 00:40:01,443
specialists to the directors of HR.
786
00:40:01,453 --> 00:40:04,903
We're all kind of thinking about
how their roles may change.
787
00:40:04,913 --> 00:40:06,923
And it's a really fascinating background
788
00:40:06,923 --> 00:40:07,883
that you bring into this.
789
00:40:08,363 --> 00:40:11,503
And specifically coming in and out
790
00:40:11,533 --> 00:40:15,283
and back to HR through
all of the transitions.
791
00:40:15,533 --> 00:40:17,583
Thank you once again for the conversation.
792
00:40:17,953 --> 00:40:19,503
To everyone out there who's listening,
793
00:40:19,703 --> 00:40:21,373
I hope you found as much value
794
00:40:21,373 --> 00:40:21,933
as I did.
795
00:40:22,353 --> 00:40:25,683
Good luck as you are future-proofing
your own organizations
796
00:40:25,683 --> 00:40:27,043
and your own HR functions,
797
00:40:27,473 --> 00:40:29,013
and I'll catch you on the next one.
798
00:40:29,793 --> 00:40:30,183
Bye now.
799
00:40:30,523 --> 00:40:31,223
Alim Dhanji: Thanks, Thomas.
800
00:40:33,243 --> 00:40:36,303
Thanks for joining us on this
episode of Future Proof HR.
801
00:40:36,543 --> 00:40:39,153
If you like the discussion, make
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802
00:40:39,153 --> 00:40:42,033
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803
00:40:42,453 --> 00:40:45,393
Or share this with a friend or colleague
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804
00:40:45,693 --> 00:40:50,643
See you next time as we keep our pulse on
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