From Leading Teams to Leading AI Agents: The CPO Playbook for the AI Era

What does AI actually change inside the people function?

In this episode of The Leaders in Talent Podcast, Adriaan Kolff sits down with Shlomit Gruman-Navot, a four-time Chief People Officer and transformation executive with 25 years of experience across tech, SaaS, consumer platforms, and banking.

Shlomit shares what changed when she went deep into AI, why this is not just a technology shift but a human transformation, and how leaders should rethink work, judgment, operating models, and AI fluency across the organization.

Timecodes:

01:23 Guest introduction: who is Shlomit Gruman-Navot

02:49 Why Shlomit went deep into AI

03:36 From leading teams to leading AI agents

06:22 How her AI journey actually started

10:11 Where AI is already making an impact in HR

12:18 How to redesign work and drive change inside organizations

15:45 Why HR is uniquely positioned to lead AI transformation

18:26 Advice for CHROs and HR leaders who are too busy to experiment

21:39 Agents vs agentic AI explained simply

24:45 Will AI eliminate junior HR and analyst roles?

29:07 How talent leaders should deal with AI overwhelm

30:48 Shlomit’s new community around making AI work at work

___________________________

Connect with us on LinkedIn: https://www.linkedin.com/company/matchr/

Get in touch with us: https://www.matchr.io/who-we-are/contact/

____________

Connect with Shlomit Gruman-Navot: https://www.linkedin.com/in/shlomit-gruman-navot/

Connect with Adriaan Kolff: https://www.linkedin.com/in/adriaankolff/

___________________________

“

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Transcript

[00:00:05] Shlomit: As a chief people officer, especially in the environments where I work, there has always been tons of change.
So it was always about adjusting, building, rebuilding, transformations, hypergrowth, digital transformation, agile transformation.
Only working with agents, only working with AI tools. So before, I was leading teams. Now I’m working, I’m leading agents.
Whether it’s one hour a day, start small, but make sure that you have the time every day to experiment with something that is AI-related, based on your work, based on your task.
If you’re a leader today in an organization that has to navigate this change, this is a human transformation.
This is not a technology transformation. This is a human change, and it has all the ingredients, like ever before, that were there when we need to go through change: support people, communicate constantly.
There’s a lot of FOMO. I have this FOMO all the time, and the secret is: start small and embed it in your day-to-day activities, but do it all the time because then you’ll see the magic. You’ll know, actually, what the impact is.

[00:01:23] Adriaan: Ladies and gentlemen, welcome to another episode of The Leaders in Talent Podcast. Today, my guest is Shlomit Gruman-Navot. Shlomit is a transformation and people executive with 25 years of experience building, scaling, and transforming organizations across tech, SaaS, consumer platforms, and banking, and has worked for companies like Alpha Bank, OLX, and Miro.
As a four-time CPO, she has lived and worked across five countries and led global teams spanning over 30 markets. Today, in her current role, she works with CEOs and leadership teams on operating models, organizational effectiveness, and AI-driven work redesign. Shlomit, welcome to the podcast.

[00:02:19] Shlomit: Thank you, Adriaan, and you did a perfect introduction, I have to say. Great.

[00:02:25] Adriaan: Great. I think it helped that I lived in Ukraine and started Matchr Ukraine in 2018, where names that are unusual, at least in the language, were the common denominator, right?
So I had to learn the hard way how to pronounce surnames. So I’m happy that you’re giving me some credit that I did well.

[00:02:46] Shlomit: Perfect. Great. Thank you very much for having me.

[00:02:49] Adriaan: Great. Shlomit, you have such an interesting experience. You’ve led multiple large-scale organizations as a CPO, but over the last year and a half or so, you’ve gone really deep into AI. With your knowledge as a CPO and AI, you are really at the centerpiece of what AI is doing to the people function.
How should organizations look at how to redesign their org charts with regard to AI? And what does the people and talent function look like in the next few years? I don’t think anyone has a crystal ball.
But I’m excited to explore a little bit more about what you’ve seen, what your journey has been, and some of the things that people can take away from this call, what they can do in their day-to-day. Great.

[00:03:36] Shlomit: So, of course, as a chief people officer, especially in the environments where I work, there has always been tons of change.
So it was always about adjusting, building, rebuilding, transformations, hypergrowth, digital transformation, agile transformation. So constantly having to adapt and dealing with a lot of uncertainty, ambiguity, and complexity. So all of that is obviously not new to me.
I also worked in very diverse environments and across different geographies. So you can say, from a judgment point of view, I’ve seen a lot of use cases.
And of course, also when I was in organizations, I worked with AI, and also when Gen AI was introduced. So I built things like chatbots, where you use company information to help people with requests and answers.
Of course, implementing tools with AI already embedded, but really only in the last eight months or so, when I went into advisory work, I completely immersed myself in AI.
And what I mean by that is only working with agents, only working with AI tools. So before, I was leading teams. Now I’m working, I’m leading agents.

[00:05:07] Adriaan: Yeah.

[00:05:07] Shlomit: So you can imagine my face in the middle. I’m just surrounded by different tools, depending on the use case, or different agents.

[00:05:14] Adriaan: Yeah.

[00:05:15] Shlomit: And I got really fascinated and very passionate about bringing these two worlds together. One is managing change, transformations, operating models, org redesign, and the other is AI.
And what I’ve truly seen very clearly, and also experienced myself, is how much it actually changed the way we work. So on a personal level and then on a company level, it completely transforms the work itself, the job that needs to be done.
I think that many organizations are still figuring it out, and many leaders are still trying to understand what it is really changing.
And going away from just seeing this as tool adoption to understanding that this is a complete rethinking of how we operate. So that has been my passion and my goal, bringing these two worlds together and helping leaders and professionals navigate this new world.

[00:06:22] Adriaan: So, okay, eight months ago, right? Did you have a particular moment, like an aha moment, or was it more gradual? Kind of back and forth with ChatGPT and then using other tools?
Tell me a little bit more, practically, how that journey started, and where you are now. And be specific. When you say “tools,” what tools? Give us the nuggets of what you’re doing right now. And what does it mean to have an army of AI agents?

[00:06:48] Shlomit: So it’s not an army, it’s a team, right? It’s a team.

[00:06:59] Adriaan: Right.

[00:06:59] Shlomit: You don’t need that many, but you need a few that are very good at solving your problems.
So of course, I used ChatGPT before, like anyone else. You ask a question, you get an answer. That’s how most people use it.
But then I started building with AI. It came from curiosity. I was very curious about AI, which I believe is an essential trait in our current times.
Even though I have experience and have built a lot of knowledge over the years, I always approach situations with a mindset of “I don’t know.” That keeps me open-minded and curious.

And that’s how I started the journey. It began with a cohort, a three-week course, very practical, where we went deep into specific use cases.
I was experimenting daily, using tools like ChatGPT, Claude, Gemini, Gamma, Lovable. That’s when I got exposed to tools I had never used before.

And then I started seeing the magic. The magic of augmenting myself with these tools.
Even simple things like creating a document, where you need research, context, synthesis. You still apply your own judgment, but suddenly you have an output almost immediately to work with.

Then I thought: there are many things I don’t enjoy doing. What if I had an agent to handle those?
For example, administrative work, tracking expenses, follow-ups. I built an agent for that.

Or in meetings, I’d take transcripts using a note-taker, then feed them into a Claude project and get feedback on my blind spots. How do I come across? What should I improve?

So these small examples showed me how AI can augment me, help me get faster to outcomes, while still using my own judgment and experience.

[00:10:11] Adriaan: If you look beyond advisory work, where has AI made a significant impact within HR?

[00:10:23] Shlomit: Specifically in HR, there are already strong use cases.
For example, in recruitment, you can use AI note-takers for interviews that assess candidates based on values, behaviors, and mindset.
You can use AI for resume screening, sourcing, and even market analysis to determine where the best talent is.

That’s just one workflow. You can also use AI in performance management to synthesize information and save time.

But where I still see opportunity is not just using tools, but rethinking the work itself.
HR is still organized traditionally. We need to rethink how work is structured.
What stays with humans? What gets augmented? What moves entirely to AI?

And beyond HR, the bigger opportunity is redesigning the entire company. Operating models, decision-making, org design. That’s still largely untapped.

[00:12:18] Adriaan: And how do you approach that? When working with organizations, especially larger ones, how do you drive that change?

[00:12:45] Shlomit: The principles of change remain the same. AI just accelerates everything.

Context matters. The first question is always: why do we need to change?
What do we need to change for our customers in the next 3–5 years?

Then you move into work redesign. And you start small.
Pick one function, one area, like customer support, and transform it completely.

There are already examples where customer service is fully run with agentic AI, agents talking to agents, with high customer satisfaction.

You learn, then scale.

You also need frameworks. Break work down into tasks:

• What stays human
• What gets augmented
• What goes fully to AI

Anything involving judgment, accountability, and decision-making should stay human.
For example, final hiring decisions or bias checks in recruitment.

And then there’s AI fluency. Not everyone needs to know everything, but you need clarity on what different roles need to understand.

[00:15:45] Adriaan: So how should HR leaders think about AI? How can they lead this change?

[00:16:04] Shlomit: This is a golden opportunity for HR.
Because this is not just technology. It’s a complete redesign of work.

HR is best positioned to lead this.

Start with:

• Where the business is today
• Where it needs to be in 3 years
• How work itself will look, not job titles

Then break work into tasks:

• What is augmented
• What is automated
• What stays human

Leadership matters. Leaders must show by example.
Even simple things like writing documents with AI tools and sharing the outputs.

You also need champions across the company.
People from different functions who experiment and share learnings.

And finally, give people tools and permission to experiment, fail, and learn.

[00:18:26] Adriaan: Shlomit, you started your journey eight months ago, and now you’re an independent consultant. What’s your advice for CHROs who are working 60, 70, maybe 80 hours per week, constantly dealing with operational fires? How can they improve their AI fluency?

[00:18:58] Shlomit: I fully understand how consuming the day-to-day can be, because I’ve been there.
You start the day with one intention, and then the day just happens. You become very reactive.

So the main challenge is time. And you have to dedicate time for this.
Whether it’s one hour a day, start small, but make sure you experiment with AI every day, based on your work.

Build an onboarding plan with AI. Create documents with AI. Build something.
It’s not about using many tools, but using the right tools well, with proper context.

It’s about embedding AI into your daily workflow.
Experiment, iterate, learn, ask questions.

Also understand your level of fluency.
If you’re redesigning operating models, you need to understand things like the difference between agents and agentic AI.
If you’re a regular user, you just need to be comfortable building with tools like ChatGPT or Claude.

And yes, there’s a lot of FOMO. I feel it too.
But the secret is: start small, embed it into your daily work, and be consistent. That’s how you start seeing real impact.

[00:21:39] Adriaan: You mentioned agents and agentic AI. Can you explain the difference?

[00:21:51] Shlomit: Sure. In simple terms:

An agent is a single tool solving a specific task. You interact with it directly.

Agentic AI is when multiple agents work together.
They interact with each other, creating workflows and outcomes with minimal human intervention.

You’re still in the loop, but less involved.

The best examples I’ve seen so far are in customer success.
I spoke to a Chief Product Officer who redesigned their entire customer success operation using agentic AI.

Customer satisfaction went above 95%.

And internally, roles changed dramatically.
Product managers became designers, engineers, and operators in one.

Of course, data and governance are critical. You need to ensure the system behaves correctly.

In HR, I’ve seen agents, but not many strong agentic AI examples yet.

[00:24:45] Adriaan: What about the impact on jobs, especially junior roles? What happens if AI replaces entry-level positions?

[00:25:23] Shlomit: I think about this from two angles.

First, judgment.
Judgment is built through experience, through doing the work.
If AI does everything, how do people develop judgment?

There’s already a concept called “work slope,” where output looks good, but lacks substance.
Nice presentations, but shallow thinking.

That’s a real concern.

Second, AI will reshape the job market.
It will eliminate unnecessary tasks and processes. Some jobs will disappear.

But this also creates space for new value creation.
We don’t yet know what those roles will be.

So the focus should be on mindset:

• Curiosity
• Adaptability
• Resilience
• Continuous learning

That’s what will matter most.

[00:29:07] Adriaan: What’s your advice to talent leaders who feel overwhelmed by all of this?

[00:29:26] Shlomit: Use the tools. That’s it. Full stop.

Stay curious.
Never assume you know everything.

Approach everything with a mindset of “I don’t know,” even if you’re experienced. That keeps you open.

And remember: this is a human transformation, not a technology one.

All the classic change principles still apply:

• Communicate constantly
• Support people
• Repeat messages
• Be transparent

Use the three Rs: repetition, reminders, rituals.

Be clear on the “why.”
If you don’t know something, say it.

Treat people like adults.
Lead with empathy and compassion, because this change is hard.

[00:30:48] Adriaan: What are you excited about right now?

[00:30:55] Shlomit: I’m launching a community focused on making AI work at work.

It’s about people learning together, experimenting, and sharing real use cases.
Helping leaders understand what’s real versus hype.

We’re starting with HR and marketing, but will expand further.

[00:31:52] Adriaan: Who is the community for?

[00:31:56] Shlomit: Professionals, practitioners, leaders.
Different spaces for different levels, but starting with HR and marketing.

[00:32:20] Adriaan: If people want to join, where should they go?

[00:32:29] Shlomit: LinkedIn is the best place.
We’ll also share a landing page where people can sign up and get invited.

[00:32:42] Adriaan: Great. We’ll add that to the show notes.
Shlomit, thank you so much for sharing your insights.

My key takeaway: make time, experiment, and get hands-on with AI.
That’s the only way to stay relevant.

[00:33:07] Shlomit: And mindset.

[00:33:08] Adriaan: And mindset. Stay curious, stay hungry. You never know everything.

[00:33:13] Shlomit: Exactly.

[00:33:13] Adriaan: Shlomit, thank you so much.

[00:33:14] Shlomit: Thank you very much.

“

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