For a People & Culture practitioner and member of a dedicated Center of Excellence, the promise of AI is easy to overstate and hard to operationalize. Simon Kaczmarek, senior principal management consultant at SimCorp works at the intersection of business, HR, and technology, and his approach to Workday has been deliberately unglamorous: make the technology genuinely useful in everyday operations, and build the data foundation that lets it work.
Creating the conditions for AI to work.
For Kaczmarek, it starts with a clear read on what people want from their work. He sees it come down to four things: meaningful work, visible impact, fair pay, and growth.
Growth was the piece he felt Workday could serve better. It's the question almost every employee is quietly asking: Where am I today, and what skills do I need to go further? Answering it meant investing in technology that could guide employees, without piling more administrative work onto managers or HR.
A strong philosophy about AI sets the tone. Rather than treating it as a replacement for judgment, Kaczmarek uses it as support for better decisions. “You can use AI as a GPS for decision-making,” he said. “I can ask what are the right questions, who to speak with, at what point in time – and get a framework to help me make a decision.” The aim was to give employees that same sense of direction about their own careers.
Building a career-growth engine with Workday.
So the work began: build out a job architecture in Workday, layer in the skills data, job descriptions, and connected systems that make it navigable, then put Workday Career Hub in employees' hands so they could explore where they might go next, on their own terms. That changes career check-in conversations and growth chats with managers. Employees can now be even more active participants and be prepared with informed ambitions.
“It shifts the dynamic entirely. Instead of an employee asking their manager ‘What can you do for me?’, they come in and say: ‘I've seen what's possible, I can see these positions are available to me – can you actively support my journey from A to B?” Kaczmarek explained.
Why clean, connected data and governance come first.
The sequence isn't negotiable: start with data, then clean, connected data, then governance to protect it. “The moment you stop protecting your data, you're back to square one,” Kaczmarek said. “And generating data takes a lot of resources.”
That conviction drove one of the defining design decisions. Rather than build a bespoke, theoretically precise skills taxonomy – which can be cumbersome, resource-heavy, and requires everyone to learn a new syntax – the call was: 70% is good enough. “This isn't banking, it's directional,” Kaczmarek noted.
The approach leaned on language people already know from LinkedIn, CVs, and their own experience, so whether someone wrote “bookkeeping” or “accounting”, the system would still match them to the right opportunity. The decision saved time, cut complexity, and made the whole thing more intuitive to use.
AI earns its keep here too, as an accelerator for content. Job descriptions can be drafted and refined faster – as long as they're built to serve both recruiting and internal clarity, and give context to a skill. “Project management in engineering is very different from project management in communications and branding,” Kaczmarek pointed out. “The job description gives you that context, so people intuitively understand what type of skill is being referenced, and those are the kind of distinctions that matter when the system is making matches,” he concluded.
Workday gives you the flexibility to take smart shortcuts – using language people already know, and AI to create content faster. But none of it works without clean, connected data and governance protecting it.
Senior Principal Management Consultant | Development, People & Culture
Staying inside the core ecosystem.
There's a discipline that holds all of this together: resist the pull of point solutions. “Every time you step out of your ecosystem, there's a penalty. It can be cost, time, or user experience,” Kaczmarek said. He shared that People & Culture teams are especially prone to falling for the next shiny tool, and sometimes one genuinely fills a gap. But the decision has to rest on a real business case. “Stepping outside can impact your data, your governance, your ownership – and it might not yield the results you're looking for,” shared Kaczmarek.
The value of Workday isn't any single feature. It's having people data, governance, and workflows connected in one place, so that when AI is layered on top, it's working with information you already trust.
Senior Principal Management Consultant | Development, People & Culture
Pragmatic optimism for what comes next.
The outlook on AI is optimistic and grounded in equal measure. There's real promise in agentic AI and in Workday's future vision, alongside a clear-eyed view that foundational questions still deserve attention – data ownership, how decisions get made, and the role of human oversight.
“Thoughtful adoption means building trust in these systems over time, and that trust is earned when the data and governance underneath them are sound,” he noted.
That discipline is what makes optimism credible. The goal isn't cutting costs – it's giving people a second brain that helps them produce better outcomes, with human oversight and trusted data underneath.
For Kaczmarek, that's the payoff of the work: Workday as the connective layer where human judgment and trusted AI can finally pull in the same direction.