Welcome to Richard Rosenow's keynote presentation at People Analytics World 2025. In this talk, Richard draws parallels between art and HR, emphasizing the need for a blend of creativity and analytical rigor.
As AI technology advances, he advocates for elevating human roles within HR, moving away from rigid systems to embrace flexibility and strategic thinking. He underscores the necessity for HR leaders to be fluent in business operations and to engage in meaningful dialogues rather than relying solely on data.
Listen in or read our lightly edited transcript:
Kicking Off the Future of People Analytics
What a great way to start the day. I am delighted to be back. I love the People Analytics World series because it brings together a group of people passionate about this field. We get to have phenomenal, nerdy conversations all day, today and tomorrow. I can't wait.
Today I'm going to put forward something a little bit different.
People Analytics World helps us stay on top of what’s happening in the space—trends, changes. One of the best talks I heard last year wasn't on data science or AI—it was on power. A phenomenal talk by Amit Mohindra, worth looking up if you missed it. It changed how we think about People Analytics and what’s shifting in this space.
Postmodern Inspiration from an Artist Brother
Let’s start with this piece: a laser-cut relief collage, which includes screenshots from a Reddit discussion about Israel and Palestine. It explores the gap between what happens in life and the emotional flattening of the news. The closer you get, the bear disappears, and you begin to see the words. It's an interplay of perspective. It’s by Tom Rosenow—my younger brother. He’s graduating from his MFA program next week, which I’m incredibly proud of.
In conversations with Tom, I've learned this piece is a good example of postmodernism. The interplay with interpretation, understanding, and layered meaning. We talked about what postmodernism is—and I found there are lessons we can bring back to People Analytics and HR.
The Fusion of Art, Science, and Analytics
But first, let’s talk a little bit more about my brother and myself.
We were raised by two engineers—civil and industrial—who ran a small machine shop. We actually had computer-controlled machines in our garage. That might explain a bit about who I am, if you know me. When I went to my undergrad, I studied sociology. (Where psychology is person-based, sociology studies the systems of a culture; understanding the system in order to understand the people). When Tom went to undergrad, he studied fine arts. He was an oil painter who did some tremendous work.
So our engineering parents were very understanding when their sons pursued traditionally soft sciences. But throughout our careers, we both returned to our original passions, but in very different ways than we started.
For example, Tom does some really interesting work here. This is actually a copper plate, about 3 ft by 3 ft. These things are massive. He has learned more about sanding and metals than I ever would have expected from an MFA program. Here's another one of his pieces. This is an aquatint in cyanide. Cyanide? No. Yes. Cyanotype. Uh-oh. Art history majors. Keep me in check here. It's a fantastic piece. It's another massive collage, but it is an incredibly mechanical process. It almost takes alchemy to create this. He etches it in, dips it in acid, then applies the ink. It's a massive process.
This is not art as I knew it. I knew art as painting, and I'm not an artist by any means. He got all of the talent there. But what I love is the blend between this art and this science.
I have a similar story. I was one of the few people deliberately trying to break into the People Analytics space. I’m passionate about it and excited about where it’s going. But I found art and science coming together there, too.
And a lot of you in the room have found that too. Into this traditionally soft domain of HR, we brought this harder edge. We brought the math. We brought the science. We brought these things together in a very unique way, like with this people overview by Tony Ashton, our Chief Product Officer. It's available at our demo booth.
So from talking to my brother about this and seeing where art has gone and where his art exists within the space of postmodernism, I'm gonna walk us through a couple of the eras of art and some things we can learn along the way when it comes back to HR and People Analytics.
Art through the Eras: From Romanticism to Postmodernism
When Tom went for his MFA in fine art, I thought he was going to create these grand, beautiful expanses of understanding nature and intense emotions. I was thinking of romanticism—emotional, heroic, grounded in human nature. Like "Wanderer Above the Sea of Fog" by Casper David Friedrich, that really shows off human nature and the heroism of the space.
Then came modern art—logical, orderly, rule-based. Artists asked: What makes this art? What’s the wiring here? How do we play with that and have people experience it in different ways? This particular piece, "Composition with Red, Blue, and Yellow" by Piet Mondrin - I don’t think he made it in Excel, but he could’ve—there are some parallels here. No, it’s a tremendous piece. But it was a rejection of the incredible romantic era.
I think some of you are starting to see where I'm going with this. In this art evolution, there wasn’t a debate about Which one is the real art? Which one is most correct? They are art.
Next came postmodern art. This particular piece is “Crushed” by Andy Warhol, a great example of postmodern art.
Postmodernism says I respect that modern art had some rules. But we're gonna play with them, and we're gonna try to understand this more human piece that's coming back around. And it started to layer on top of what modern art had developed, bringing something back about human creativity and meaning. And we started to look and say, Hey, this is a can of soup. Is this art? What does this mean? What does it mean for me?
And even that question, that reflection, that playful interaction is part of the art itself.
Breaking the False Dichotomy
But something was built on top of where "modern" was and where it's going. And I see that a lot.
We hear a lot about art and science as being a pendulum, where things swing between them. We hear about emotion and logic. We hear about people and analytics and how we show up. Are we left brained? Are we right brained? And these things are in contrast in many of our conversations.
And I believe this is a false dichotomy.
What's happening in the world of work today is we need to show up with both. We can't be 80% people and 20% analytics. I can't be just a people person. I can't be an analytics person only.
We have to show up as empathetic nerds.
We have to be 100% people/100% analytics, and we've got to take that forward to something new. So when people ask what’s happening in People Analytics, what are the changes we're seeing?, what I see is how can we can break through to that next thing?. It's not going to be a return to that romantic era of HR. And we're not going to be able to stay in our kind of modern space forever.
There's going to be something next, and we're starting to see hints of that start to emerge on the scene. So I'll lay it out very clearly.
HR through the Eras: From Romanticism to Postmodernism
Artisan HR (Romantic Era)
We began in the artisan HR era—the romantic period. I use the term artisan intentionally, because people think of this time period as qualitative or even anecdotal. Not quite: Qualitative is actually its own scientific discipline and anecdotal HR is kind of mean.
The truth is when I think about the best HR people I've worked with, as they've grown their careers, it really parallels what a lot of artists have done. They lived in the flow of work, and built their careers through the experiences, the apprenticeships, the journey. They really understand the business, and they contribute something powerful through that innate human understanding of the business itself.
As with artists too, there’s a pretty wide range. The incredible ones, and then there's “everybody thinks they're an artist,” as well. This is what makes it tough to manage an HR team. It’s a very human domain.
This piece, “The Fighting Temiar” by Joseph Mallard William Turner is a beautiful example from that romantic era.
People Analytics (Modern Era)
Let's talk about People Analytics, though. I think this is the modern era of HR. This is where we're living. This era is about what comes next…like this beautiful piece, Girl with a Mandolin by Pablo Picasso, which interacts with and starts to set up some of the rules and the structures around this shift.
I think about this a lot because at some point, we're going to reach the edge of what People Analytics does. Ten years ago when we started down this space, a lot of teams were blasting the marketing that People Analytics will fix everything. Just use data.
But we all know, the longer someone has been in this space, the most experienced People Analytics leaders end up talking about power. They talk about different change management. They talk about different dynamics at play, and they bring that extra piece back into the conversation that was missing.
Because we can't data science our way out of HR, we have to bring something back together.
Postmodern HR (Next Era) and Trends that Signal the Shift
That brings us to postmodern HR. Think of "The Brooklyn Rail" by David Salle. It’s about an experience and finding meaning. And the question is how do we bring meaning back to HR and People Analytics?
Originally, HR was about personnel—how to manage and pay people. Then we moved to data—measuring things like sentiment, productivity, engagement. We flattened multidimensional humans into spreadsheets. That was progress.
This new phase is about outcomes. Some of you here will say "We've been knowing outcomes for years.” We’re not going to throw out data - we’re going to build on these things and keep growing. Keep what we need and maybe drop some things that aren’t serving us.
The New HR Skillset
Let's talk about the skills required to thrive in next gen HR. The skillsets required are evolving:
- First, “soft skills”—critical thinking, change management, communication.
These skills were and still are in high demand during change management projects, which are often better served by HR than, say, CHROs. - Then came data literacy—understanding and communicating data.
These skills helped HR teams translate complex datasets into organizational insight, but now AI is learning to speak human, reshaping the role of data literacy in the process. - What’s next? Business fluency.
This goes beyond speaking the language of data. What really differentiates modern HR teams is how fluent they are in the way the business operates. Do you know what it is that drives your business forward? Are you able to speak to business? Are you part of the business?
We need all three.
From Complexity to Nuance: How HR Creates Value
How we create value has changed. Artisan HR understood complexity and did its best with what it had at the time, no technology, no data. People Analytics brought order to the chaos.
What’s coming next is nuance—understanding what’s uniquely true for your people and business.This is where postmodernism really shines. We’re going to this space where it's uniquely about your business, your people. Where those spiky edges of your data model are actually going to give you the difference you need to make change happen.
This next era of HR will be focused on outcomes, grounded in business fluency, powered by nuance, and informed by predictive analytics:
- Predictive analytics won't disappear, but will shift from being the final deliverable to informing more nuanced, forward-looking conversations.
- Dashboards become dialogues
- Insights become recommendations
- Human judgment is elevated, not replaced
At a recent CHRO panel discussion, they made it clear that they don’t want data or even “insights.” They need to know what action to take. People Analytics teams can create insights and pass them on and hope they make change happen. But this next phase is going to be around answers. And that means human judgment will be elevated, not replaced.
We’ve seen marketing materials that claim their tool can replace your whole HR team. But at the end of the day, we need those HR people in those human positions, pushing towards finding meaning and using that to drive change forward. And this is how People Analytics becomes a strategic function.
This is the carrot, but there’s a stick, too: AI is coming. Fast.
The AI Moment: A Turning Point
AI is getting pretty good at what we’ve been doing for the past ten years. This piece was generated by me and ChatGPT. This is a people analyst. I love this piece. I shared this with my brother. He said it was horrible. He hated it. So I'm gonna print out a bunch, and I'll sign them at the booth. But, truly, anyone that's played with ChatGPT and other AI tools for a minute knows what it's capable of doing. But what it's really good at is when we've structured things, when we have order, when we have a checklist - a lot of the stuff we’ve built up our credibility on and even our own careers within People Analytics.
ChatGPT will come for us before the HRVP. And so we’ve got to start looking ahead. And this is why:
This is an internal company demo from One Model. Our Chief Data Scientist showed me 6 months ago what we were working on. I got permission to talk about it. This isn’t a flashy, product demo. It was a raw internal tool. But when I first saw it, it gave me a “before and after” moment in my own thinking. I had worked in data foundations, partnered with engineering teams, built and scaled product. And yet, watching this demo made me realize: If I went back to practice, my job is not going to be there. So I knew this is really important for me. I’ve got to stay on top of this, keep moving forward.
The demo we’re going to see is of AI ingesting Workday and Greenhouse data, standardizing it, creating an entity relationship diagram, and writing 2,000 lines of code—all in under three minutes. (I trimmed it to two minutes by removing file navigation and background setup, but the actual processing time is unchanged.)
It starts with a simple prompt: “Please load these new files and combine them to a new event fact table called job event open.” The user selects files from Greenhouse and hiring manager data. The tool recognizes the content, standardizes the structure, and proposes a plan. It automatically looks at it and understands in a way that a senior data engineer could still manipulate.
Then the AI begins building out a full project plan. It determines what internal tools to use and how to organize the work. It’s that idea that if you had a hundred hours to cut down a tree, you’d spend ninety sharpening the axe. The AI isn’t rushing. It’s setting up something defensible and deliberate. And, again, this is something that a senior data engineer will be monitoring, watching, confirming.
Once the plan is confirmed, the tool gets to work. It creates an entity relationship diagram—yes, fully AI-generated. If you've ever tried to get a data engineer to build one manually, you know how significant this is. The diagram clearly shows what’s new, what’s modified, and how everything connects.
The stuff in yellow is what's gonna change. The stuff in green are the new files. It asks, Does this look right? Can we start?
After that, it writes the code. Two thousand lines of it. In seconds. This code would typically take a skilled team days or weeks to deliver. But here, it’s done and ready to audit almost immediately.
What once took weeks or months can now happen in minutes. The impact of this shift is impossible to ignore.
When I saw this demo, I remembered every fight I've had with IT.
And I remembered how many months it would take to get a new file.
How One Model Fits the Postmodern HR Vision
We’ve built One Model for this moment. Our company was founded on the idea that data engineering, architecture, and ingestion are critical to making People Analytics work. We've spent 10 years solving those tough foundational problems, building robust tools and assembling a team of some of the world’s best data engineers.
These tools were originally created to support our own team. But here’s what’s changed: when AI uses those tools, it becomes fast, powerful, and consistent. The results are auditable and repeatable—exactly what you need in a business-critical function.
So what does that mean for HR and People Analytics teams?
First, it means we can elevate our humans. If your team is still stuck managing pipelines manually, doing repetitive file loads, or serving as the human API between systems—it’s time to move them out of that invisible work. Not only is that work automatable, it’s also where AI is making the fastest inroads.
Second, we believe it’s time to reject rigid systems. Too often, teams are forced to fit their unique organizational realities into someone else's template. One Model offers one flexible data model per customer. We don’t expect you to conform to our structure—we adapt to yours. We represent your business the way it actually operates.
And third, we fully embrace generative AI. That means building AI-first tools, promoting an AI-first mindset, and encouraging teams to ask: could the AI do this first? Only then should we assign it to a person.
This is how we support postmodern HR teams—by freeing them from invisible work, respecting the uniqueness of their business, and empowering them to thrive in an AI-driven future.
Thank you.
