At a glance
- AI adoption is a leadership challenge, not a technology rollout
- Managers turn AI from abstract potential into everyday impact
- AI creates time and capacity, but managers decide how that value is used
- Even with AI agents in the workflow, accountability stays firmly human
The AI moment HR leaders are living in
Let’s kick off with what most HR leaders are already feeling—AI has moved from optional to unavoidable.
Boards want answers. Executives want productivity gains. Managers want clarity. And team members want to know what AI means for their role, their skills, and their future.
So yes—there’s a real pressure for HR leaders to have a clear point of view on AI.
But we’ve figured out that there’s one thing missing from many of these conversations.
Where does this AI transformation actually happen?
It’s not in strategy decks. It’s not in vendor selections. It’s not even in the boardroom.
It shows up in the everyday decisions managers make with their teams.
That’s the core idea our CEO, Ronni Zehavi, returns to in this first episode of AI Mind Talks. Because AI doesn’t change organizations on its own—people do.
And it’s managers who sit at the very center of that change.
Why this AI wave is different
Ronni has spent more than 25 years in tech, and has seen more than a few hype cycles come and go.
But what stands out about AI, he explains, is not just its speed—but its scope.
AI doesn’t simply optimize existing processes. It changes how work gets done.
As Ronni puts it, it’s “like getting electricity to homes maybe 200 or 300 years ago—the impact of understanding what it means to be with or without electricity. I think AI brings the same experience, the same impact.”
In other words, electricity changed how we operate. It reshaped industry, productivity, and daily life.
And AI has that same potential.
But, as always, there’s a catch.
Electricity only delivered true value once people learned how to properly use it and make the most of what it had to offer. AI follows the same pattern.
For Ronni, this makes AI fundamentally a leadership challenge, not a technology rollout.
Managers are the real change agents
AI creates an “X factor,” as Ronni puts it, which allows organizations to do more.
That’s more output, more impact, more productivity—you name it.
But “doing more” doesn’t happen automatically. Someone has to translate capability into outcomes.
And that someone is the manager.
Managers are the ones who explain what AI augmentation actually means in practice. They decide how AI fits into workflows. And most importantly, they decide what happens with that extra time AI creates.
One example from HiBob makes this all the more real.
After our AI Day, one of our team members responsible for survey analysis figured out she could complete a task that used to take 10 hours in just 11 seconds.
That’s an incredible example of the technology working. Then came the real question.
What do you do with the remaining nine-plus hours you’ve just saved?
Do you just go home earlier? Run more surveys? Go deeper on insights instead of processing data?
That decision doesn’t belong to the AI. It belongs to the manager. And it’s exactly here where many AI strategies quietly break down.
Of course, teams will rightly celebrate the time saved, but they then don’t redefine expectations, priorities, or outcomes. Without clear managerial direction, those efficiency gains never really add up to something bigger.
The evolving AI–human relationship
As AI agents become part of everyday workflows, a new question quickly follows:
Who’s accountable when something goes wrong?
Ronni’s answer is clear—execution may shift, but accountability does not.
AI agents can take on that process-heavy, rules-based work—things like analysis, administration, and repetition. Some workflows can even be fully automated.
But when work involves judgment, experience, engagement, or trade-offs, ownership remains quintessentially human.
This is where the co-pilot model comes in.
AI is about how work gets done, while humans remain responsible for deciding what should be done—meaning these AI agents are there to, as Ronni puts it, “augment the way people work.”
Managers sit at the very center of that relationship.
They decide when to trust outputs and when to challenge them. They set the standards for quality. And they provide the context AI doesn’t have—we’re talking organizational nuance, emotional intelligence, and an understanding of what matters most right now.
The key here is that AI doesn’t reduce or diminish the manager’s role, it actually makes it more important.
Because someone still has to connect capability to outcomes, and tools to real-world expectations. And that someone is a well-trained, people-first manager.
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HiBob’s internal AI journey
That people-first mindset is exactly how we approached AI at HiBob. Early on, we created a deliberate, company-wide moment to reset how people thought about AI.
We called it AI Day, which we touched on earlier.
It wasn’t a product launch or a top-down directive. Instead, AI Day was set up as a shared learning space across the company.
It was a way to build common ground, ease some of the uncertainty people were feeling, and let our team try things out using AI in the context of their own roles.
We brought in external experts, and our leaders were clear about the intent of where we stood with AI. Experimentation was positioned as an investment in long-term careers, with room to explore, question, and learn.
But at the crux of it all, Ronni set the tone with a simple message that quickly became a north star inside the company: “AI is not going to take people’s jobs. Humans who know AI will.”
That mindset shift mattered. It moved the conversation away from fear and toward capability. From replacement to upskilling. And from resistance to curiosity, and maybe even excitement.
From there, our managers played a huge role in spotting real bottlenecks. They paid attention to where work was dragging, where effort wasn’t turning into impact, and where AI could genuinely make a difference.
Some experiments worked. Others didn’t.
But the real goal wasn’t perfection, it was momentum.
Managers as the multiplier
AI is here to stay. That part of the equation is settled.
What’s still being decided is whether AI delivers sustainable value—or short-lived efficiency wins that never compound.
That outcome depends far less on technology than it does on leadership.
Managers are the ones who turn time saved into better decisions. Who translate new capability into meaningful impact, and who ensure accountability stays human, even as work becomes more automated.
For those HR leaders out there who are thinking about AI adoption, remember that investing in tools without investing in managers will only get you so far.
Managers play—and will continue to play—a leading role in the AI transformation.
Because at the end of the day, they’re the real make-or-break X factor that determines whether it all actually works.
