The Human Element

Human-Centered AI, Built on Culture and Curiosity

In this episode of The Human Element, Zapier’s Chief People and AI Transformation Officer, Brandon Sammut, reframes AI as a human potential accelerator—not a replacement. Drawing on his roots in education, he views HR as the “human potential business,” where change, learning, and growth all share the same foundation: curiosity.

Brandon shares Zapier’s approach to building ROI-driven automation that improves both business outcomes and employee experience—starting with frontline HR ticketing that now resolves 80% of questions automatically while maintaining high satisfaction scores. He explains why HR’s job is to redesign the container, not the people inside it, freeing talent to take on higher-value work.

Beyond tools, Brandon underscores the cultural groundwork required for success: mission clarity, trust in leadership, and psychological safety for experimentation. He details Zapier’s AI Fluency Framework, open-sourced for the HR community, and its focus on curiosity as the baseline for capability. And he makes the case for rethinking mentorship in the AI era—pairing early-career, AI-native talent with seasoned leaders to accelerate judgment and mutual learning.

His takeaway: AI adoption succeeds when HR leads with curiosity, cultural safety, and hands-on experimentation from the top.

Show Notes

Guest: Brandon Sammut, Chief People & AI Transformation Officer, Zapier
Host: Barb Bidan, host of The Human Element

Key Takeaways

• Automate frontline HR Q&A to deflect ~80% of inquiries, measure CSAT, and redeploy talent to higher-impact work.
• Anchor AI efforts in clear mission, strategy, and goals; create psychological safety for experimentation and learning.
• Adopt an AI fluency framework to set expectations, reward curiosity, and grow capability progressively across roles.
• Strengthen the CPO–CEO pact around business outcomes and culture stewardship—and act decisively in moments that matter.
• Bet on early-career, AI-native talent and pair them with experienced leaders in cross-mentoring to speed judgment development.
• Lead from the front: set up personal AI agents (e.g., a weekly AI + talent digest) and model hands-on experimentation for your team.

Key Timestamps
[00:58] – Introduction to Brandon and people ops as the “human potential” business
[03:50] – Matching potential to opportunity with AI—and the “triple win” (business, end user, employees)
[07:15] – HR ticketing automation: 80% deflection with high CSAT; freeing people ops for higher-impact work
[13:45] – Culture before tooling: mission, goals, safety to experiment, and trusted management
[17:30] – Zapier’s AI Fluency Framework: open-sourced levels, curiosity as the baseline
[18:42] – CPO–CEO partnership: mutual empathy for the craft and a decisive culture moment
[21:28] – Early-career talent in the AI era: accelerating judgment and cross-mentoring with veterans
[25:37] – Lightning round: build a weekly AI digest agent, start with HR Q&A automation, lead with a “sense of possibility,” and choose data (broadly defined) over intuition

Transcription

Barb Bidan:
Welcome to The Human Element, presented by Wisq. I’m your host, Barb Bidan, and in each episode, I sit down with CHROs and senior HR leaders to explore how AI innovation and human insight are reshaping the future of HR.

We’ll explore how technology is reshaping leadership strategy and the role of HR by sharing candid stories, practical ideas, and strategic perspectives to help you shape the future.

The Human Element is brought to you by Wisq, the leader in agentic HR and creator of Harper, the world’s first AI HR Generalist. Learn how Harper can resolve up to 80% of routine HR tasks autonomously. Learn more at wisq.com.

Today, I have Brandon Sammut with me, the Chief People Officer at Zapier. Brandon is a mission-driven leader who uses technology to connect human potential with opportunity.

Brandon started his career with Teach for America and later became a first-time CPO for a public company, where he built high-performing teams and scaled culture through rapid growth. At Zapier, he focuses on practical AI adoption that enhances human capability rather than replaces it.

And Brandon, you inspire us all because I’ve watched your other podcasts, and I’m a fan of the product, so I’m really looking forward to talking today. Thanks for joining.

Brandon Sammut:
Likewise, Barb.

Barb:
So let’s hop right into it. I love where you started your career — in education. In a world where your mission was to expand opportunity through learning, how did that shape how you lead today, especially when you think about being at the intersection of talent and technology?

Brandon:
It’s true, Barb. I’m very thankful to have started my career in education. The work we do as HR leaders is really the “human potential business” at the end of the day, though now with a healthy dose of technology — which we’ll talk about later.

Starting in education was fantastic because the work of education is really an ongoing exercise in change. Whether it’s a young person or an adult learner, you’re starting from a certain place and trying to get to somewhere else.

All those learning moments — those learning journeys — are exercises in change at the individual or classroom level. Nowadays, a lot of us are thinking about this in terms of how we guide our organizations through change — changes in the skills required to succeed, and how technology can help.

So a lot of the ingredients for AI transformation, I think, come fairly intuitively to people from education backgrounds. In fact, that’s one reason I’ve hired a handful of former educators onto the people team here at Zapier.

Barb:
I’ve done that too. Their change management skills are second to none — could not agree more. I think this next question you could probably talk about for 20 minutes — and I’d love it if you did — but how do you see AI helping organizations match human potential to opportunity, without replacing it?

Brandon:
Sure, we can talk about that at a couple of levels.

First, the actual matching itself — the mechanics of understanding what someone cares about and is capable of, and then matching that to opportunity. That’s what pulled me out of education and into software.

I was seeing how technology could start to personalize learning. Then, when it came to job searches or talent markets, I started wondering how we could use technology to match people with job opportunities.

I went back to school in my 30s — got an MBA and a master’s in education in Silicon Valley because I wanted to learn from entrepreneurs building these kinds of products. From job boards and applicant tracking systems to learning platforms — it was a fantastic place to get inspired.

When I finished grad school, I knew I wanted to work in software to understand how products get built and improved over time — and how they might truly help people.

Now, at the time, very few of us saw generative AI coming. So as optimistic as I was about how technology could help match potential to opportunity 12 years ago, I’m even more optimistic now.

Second, technology is a tool, not an outcome. It’s still humans — now and in the future — who define missions, strategies, and standards of excellence. Humans make the judgment calls about how to build and deploy AI systems.

And ideally, we do it in a way that benefits the business, the end user, and the people doing the work. That’s what we call the triple win.

Barb:
That’s awesome. I haven’t heard anyone ask you this next one. You talk about AI as a force multiplier — do you see a difference in capability or output now versus a few years ago?

Brandon:
That’s a great question — and no one’s asked it quite that way before.

I have to give a lot of credit to the people team at Zapier. It’s a diverse group — folks from big and small companies, software and non-software backgrounds. Some managed networks of car washes. Some worked in city government. And they’re spread across the world.

This team is a remarkable example of AI adoption — and of finding that triple win we talked about earlier: better business performance, better employee outcomes, and better jobs for the people doing the work.

One of the first areas I suggest HR teams look at is frontline Q&A with employees — what some call HR ticketing. Every HR team has a version of it. Whether it’s formal or informal, you’re getting questions every day.

Making sure people get quick and helpful answers is important — but traditionally, it takes a lot of time. At Zapier, we saw that too. We had talented people operations generalists spending much of their week answering repeat questions.

When you really look at the questions, most follow patterns. Maybe 10–15% are complex and need human attention. But the rest can be automated.

So, starting more than four years ago, and continuing today, our people ops generalists have automated that workflow. We now deflect over 80% of employee questions automatically — and we measure CSAT to make sure the responses are genuinely helpful.

Our organization has grown, our service levels are better, and the team is working on more meaningful projects. We have the same two people ops generalists we had four years ago — but now they’re focused on high-impact work, like reimagining how we collect employee sentiment beyond traditional surveys.

It’s so important to separate the work from the person. People are capable of greatness. If you’re not seeing that, it often has as much to do with the container you’ve put them in as their skill or potential.

That’s what’s exciting about AI — it lets us unbound those containers and let people step up.

Barb:
Totally agree. So, beyond the technical side, what are the non-technical ingredients that make AI adoption successful?

Brandon:
The best way I can describe it is that a company’s AI opportunity starts with a health check of its culture and operations. AI is a tool, but it’s not the end goal.

If your mission is unclear, or goals aren’t well defined, even the best AI won’t help. You already need a strong foundation of mission, strategy, and goals for transformation to succeed.

Then come the cultural ingredients: safety to experiment and trust in leadership.

When we began our AI journey two and a half years ago, we started asking new questions in our pulse surveys — about those cultural ingredients. For example: Do you feel safe experimenting? Do you trust leadership?

You can’t scale transformation without that foundation.

Barb:
I want to ask about your AI Fluency Framework — the one you open-sourced. It’s such a helpful tool for setting expectations around AI readiness.

Brandon:
Yes, that’s right. It’s called the AI Fluency Framework. It’s a simple way to assess and build AI readiness across levels.

We start with curiosity as the baseline. You don’t need deep expertise on day one. What matters most is a willingness to explore, experiment, and learn.

That’s the cultural piece that ties back to safety — we want people to feel comfortable trying.

Barb:
You recently co-hosted an AMA on AI transformation with Zapier CEO Wade Foster. What makes your partnership so effective?

Brandon:
Mutual empathy for each other’s jobs. I’ve been fortunate to have strong partnerships with my CEOs, including Wade.

The number one ingredient is that we both care about the other’s craft. Wade genuinely cares about talent and culture — he’s a true culture carrier.

There’s a story from years ago when Zapier was much smaller. We were at an in-person summit with about 100 people, and a comedian was performing. The jokes started getting off-color — not aligned with our values.

Wade stood up, thanked the comedian, and said, “That’s not what we have in mind for tonight.” And he wrapped the session.

That was a culture moment — deeds over words. That’s the kind of CEO you want to work with.

Barb:
You’ve talked about leaders taking bets on people. How does AI change the calculus around talent, especially for early-career professionals?

Brandon:
There’s understandable concern about whether early-career professionals will find jobs. Some data shows it’s taking longer.

But practically, I’d hire early-career folks left and right. They’re AI-native. They grew up with it.

My kids are six and nine, and they make games with coding apps — it’s second nature. For many entering the workforce now, generative AI has been around for years.

It’s also the first technology where one of the best ways to learn it is by using it. You can literally ask the tool to teach you.

The core competencies that matter now — curiosity, adaptability, and learning velocity — are the same across career stages.

The difference is judgment. That’s where pairing early-career talent with experienced mentors is powerful. Veterans bring judgment; early-career people bring fluency. Together, they accelerate development.

Barb:
I couldn’t agree more. Imagine if we cross-mentored early-career AI fluency with veteran experience. That’s exciting. Let’s wrap with a lightning round.

One AI use case every HR leader should pilot this year?

Brandon:
At the individual level, set up an agent that gives you a weekly AI + talent digest — articles, podcasts, summaries. There’s too much information to track manually.

At the team level, automate your HR Q&A. It’s one of the easiest, most impactful places to start.

Barb:
Most underrated skill for AI-era people leaders?

Brandon:
A sense of possibility.

Barb:
Data or intuition?

Brandon:
Data — but broadly defined. That includes sentiment, feelings, hopes, and fears, as well as hard metrics. When you put it all together, it often challenges your intuition and reveals bias.

Barb:
Love that perspective. Thank you so much for joining me, Brandon.

Brandon:
Thank you, Barb — this was great.

Barb:
And thank you to everyone listening to The Human Element, presented by Wisq. If you enjoyed this conversation, follow and subscribe wherever you get your podcasts. I’m Barb Bidan — see you next time.