AI Is Saving Your Team Time. Your Company May Be Taking It Right Back.

Artificial intelligence promises to give people something organisations have spent decades trying to create: more capacity.

But history suggests there is another possibility. The time saved by technology doesn’t necessarily become better work. It can simply become room for more work.

For Mattie Pujol, CMO at brioHR, that makes one question increasingly important: Who decides what reclaimed time is for?

Pujol has spent 15 years working across technology, education, and organisational change, including cloud infrastructure, collaborative tools, machine learning, and now HR technology. Today, at brioHR, an all-in-one HRMS and payroll platform, his work focuses on what happens after technology removes some of HR’s administrative burden.

His answer goes beyond the familiar promise of moving employees towards “higher-value tasks.” Pujol argues that organisations should invest some of that capacity in something far harder to automate: presence—the quality of attention people bring to themselves and one another.

In this piece, he explores whether AI’s productivity dividend could become a burnout problem, why presence may matter more as automation becomes universal, and where companies should deliberately choose human interaction even when technology can do the job faster.

AI Saved an Hour. Who Gets to Decide What Happens to It?

Q: Much of your work at brioHR focuses on what happens after HR teams get their time back. In the AI era, what do you believe organisations should actually be giving people more time for?

A: Let me start with the sequence, because the sequence is the whole story.

brioHR is an all-in-one HRMS and payroll platform. The software automates the administrative heavy lifting: payroll, leave, claims, statutory compliance—the operational weight that quietly consumes HR teams.

That is the first half of the promise: we give HR leaders their time back. My role is the second half: designing what happens with that time through our partner ecosystem and curated HR community.

And here is the first thing I have learned: if you do not decide what the time is for, it will be decided for you.

The standard answer to your question is “higher-value tasks.” I think that answer stays inside the wrong paradigm. It assumes the point of freeing humans from tasks is to hand them better tasks.

Part of it is true: an HR team liberated from admin can finally move up the stack, from workforce administration to performance management to talent engagement. We watch our clients make that climb every week, and it matters.

But the deeper answer is not a task at all.

Organisations should give people time for presence: the quality of attention they bring to themselves and to each other.

The one-to-one that stops getting rescheduled. The manager who notices someone struggling before the resignation letter arrives. The conversation where trust is actually built rather than assumed.

None of this appears on a job description, and all of it determines whether anything on the job description gets done well.

There is a sequence we live by at brioHR: we take care of HR teams, so they can take care of their people, so people can deliver the impact they want.

AI just made that sequence faster. It did not change what it is for.

What If the Productivity Dividend Becomes a Burnout Invoice?

Q: AI promises to eliminate repetitive work and free people for higher-value tasks. But could those productivity gains simply become higher expectations and more work rather than better work?

A: Yes. By default, that is exactly what will happen, and we should be honest about it.

Every technology of the last 30 years made the same promise. Email would give us time back. Smartphones would give us time back. Collaboration software would give us time back.

I spent my career selling several of these categories, so I say this with some tenderness: the time was saved, and then it was immediately refilled, because nobody had designed a destination for it.

When leadership stays silent, the backlog decides, the inbox decides, and expectations quietly ratchet up until the gains are absorbed.

More output, same exhaustion.

So the real question is not whether AI creates capacity. It will. The question is who decides what that capacity is for, and that is a leadership choice, not a technology outcome.

At brioHR, we hold a non-negotiable that speaks directly to this: Impact over Activity.

More output is activity. Better work is impact. They are not the same thing, and confusing them is precisely how a productivity dividend turns into a burnout invoice.

We also hold an equation: Impact ∩ Care. Fifty percent performance, fifty percent human, because that intersection is where flow can emerge. If one side dominates, we fail.

An organisation that takes AI’s dividend and spends all of it on the impact side may enjoy impressive metrics, then pay them back with interest in attrition, disengagement, and stalled initiatives. The gains do not disappear; they leak out somewhere the efficiency dashboard does not look.

The companies that win this era will treat reclaimed time as an asset to invest, not slack to eliminate.

Invest it in judgment, relationships, and the conversations that make the next transformation possible.

That is better work. And it starts with leaders saying out loud: this hour we got back is not for more of the same.

What If the “Soft Stuff” Is Actually Driving the Numbers?

Q: You argue that presence is a mechanism of performance, not a reward for good performance. How do you make that case to leaders who can easily measure AI-driven efficiency but struggle to quantify trust, attention, or human connection?

A: I make it in three moves.

First, I correct the causality.

Most organisations treat trust, empathy, and the quality of attention people give each other as a reward for when times are good—something you can afford once the numbers are healthy.

The causality runs the other way. Presence is how the numbers get healthy, not what healthy numbers make possible.

Second, I stop asking leaders to measure presence and invite them to measure its absence, because they can find it in the P&L.

What does regretted attrition cost you? What did the last failed transformation cost, fully loaded?

Disengagement, rework, escalations, the deal that died because two departments would not talk to each other: every one of these is a line item of absent presence. In its absence, things break, and everything costs more than it should.

Most leaders do not need a study to recognise this. Every leader has seen, at least once, a team that produced something headcount, strategy, and budget could not explain.

Ask them what that team had.

Nobody ever answers, “a better dashboard.”

Third, I concede the point that seems strongest and is actually weakest: no, you cannot put presence in a spreadsheet cell.

You cannot measure health directly either; we track indicators, and nobody concludes that health is not real.

This is the conversation I have most often with the HR leaders in our community, and here is where AI changes the argument in my favour.

As automation becomes cheap and universal, efficiency stops being a differentiator. When every company runs the same models at the same speed, the remaining variable is human: judgment, trust, the quality of collaboration.

Presence stops being the soft stuff. It becomes the last competitive advantage that cannot be copied and pasted.

Just Because You Can Automate It, Should You?

Q: As AI becomes embedded in HR, from recruitment and performance management to employee support, where should organisations deliberately choose “human inefficiency” over automation because the interaction itself has value?

A: First, a small correction to the premise: those moments are not inefficient.

They only look inefficient if you believe an interaction’s job is to transfer information. In the moments that matter, the interaction is the message.

My test is simple.

If a moment merely transfers information, automate it without guilt. Nobody’s dignity depends on how their leave balance is calculated, which is why brioHR automates payroll, claims, and compliance end-to-end.

But if a moment shapes trust, belonging, or dignity, keep a human in it, even when a machine could do it faster and cheaper.

Where does that apply in HR?

In the moments people remember for years.

Delivering difficult news: a termination, a rejection to a candidate who gave you three rounds of interviews, a performance conversation that stings.

Conflict and grievances, where feeling heard is half the resolution.

The first day of onboarding, when a person decides whether they joined a company or a system.

Recognition, which lands differently when a human chose to give it.

And the moments of personal crisis: bereavement, illness, burnout.

Automate the workflow around these moments. Never automate the moment itself.

There is a signal here that companies underestimate. Choosing the human option when the automated one is cheaper is one of the few remaining ways to prove that your values cost you something.

Employees notice. Candidates notice. Clients notice.

We apply the rule to ourselves. On brioHR’s internal list of what we refuse to become, “cold automation” is written explicitly.

No matter how intuitive software is, sometimes you want to talk to someone, and sometimes you need to. When that happens, the speed and kindness of the answer is the product.

So we recruit people who genuinely want to help, and you can feel it.

In the AI era, that is not inefficiency.

That is the moat.

Why Do We Know What Needs to Change—and Still Not Change?

Q: Across your career, you’ve repeatedly worked at the intersection of technology and organisational change. What has that journey taught you about why knowing what needs to change so rarely translates into actually changing?

A: This is the question that would not leave me alone for 15 years.

Cloud infrastructure, collaborative tools, machine learning, and now HR technology: the category changed every cycle, but the work never did.

It was always education and change management. Always helping organisations become what they already knew they should be.

Read that sentence again: they already knew.

Knowledge was never the missing piece.

Every failed transformation I witnessed had the strategy deck, the business case, the training plan. What it lacked was not information.

For years, I searched for the answer in systems and processes. Better frameworks, better communication plans, better incentives. They help, but they turned out to be the superficial layer.

Transformation happens, or does not, at the level underneath: mindsets, daily practices, the quality of awareness people bring to themselves and each other.

What stops the knowing from becoming the doing?

The being.

I did not arrive at this through research. I arrived through failure.

While my career in transformation was succeeding, I was living a parallel failure: the inability to sustain meaningful personal change. To be less impulsive, more caring, more present.

I knew exactly what needed to change, for years, and the knowing did nothing. Change came late, and it caused loss.

What finally shifted was not a new input. Nothing was added. What changed was the quality of attention I brought to what was already there.

And I learned that transformation is not a line in the sand, not a place you arrive. It is a practice you return to, never finished.

So I have not changed.

I practice.

This is why leaders are both the bottleneck and the unlock. And I am both the bottleneck and the unlock.

You cannot model what you have not become. I cannot model what I have not become. But being visibly in practice is a start.

And sometimes that is what modelling is: admitting failure and weakness, not giving up, trying again. It is actually helpful for others.

A leader who is a work in progress is easier to follow than one who has declared victory, because the change looks accessible. Not an easy ride, but it is the one we are all on.

It is also why we refuse to talk transformation before solving the admin pain. Practice requires time, and time requires liberation from the administrative burden first.

Then transformation happens through your next immediate action, not your next offsite.

A conversation held with full attention.

A decision made with care and impact together.

One adjustment away.

Here. Now.

That is what we mean by Further Together.

Final Thoughts: What Will We Choose to Do With the Time?

For decades, workplace technology has promised to make us more efficient. AI may finally deliver that promise at a scale previous tools could not.

That makes what happens next a leadership question.

Pujol’s argument isn’t that organisations should choose humanity over technology. It is that they should become more deliberate about where each belongs.

There are processes where speed is the value. And there are moments where attention, judgment, dignity, and care are the value.

The distinction may become harder—and more important—as AI gets better at tasks once assumed to require people.

Perhaps the defining question of the AI workplace, then, won’t be how much time companies manage to save.

It will be what they believe that time is worth.

AI is giving us time back. What will we choose to do with it?

Read the Chinese article here.