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A conversation with Leapsome co-founder and co-CEO, Jenny Podewils, on global HR systems, AI adoption and software entering a new era with drastically different expectations.
The HR software market has been slowly converging for years.
Platforms that originally focused on payroll and administrative workflows have steadily expanded upward into talent management. Talent platforms have simultaneously expanded downward into operational HR infrastructure. Buyers increasingly want systems that are unified across the employee lifecycle rather than stitched together through integrations and disconnected workflows.
What made my conversation with Leapsome co-founder Jenny Podewils interesting was hearing how differently the company arrived at that same destination.
Many HR systems began with the administrative layer first. Employee records, payroll workflows, approvals, and compliance formed the center of the platform.
Leapsome approached the market from the opposite direction, beginning with performance management, engagement, learning, and manager enablement before expanding deeper into HRIS capabilities.
That starting point still shapes how the company thinks about the market today, and it helps explain why organizations like Notion, Bumble, and The Cleveland Guardians have gravitated toward Leapsome as they’ve tried to create more connected employee experiences across increasingly global workforces.
“So many of these full-suite HR platforms started more from the administrative side,” Jenny said during our conversation. “We started much more from the talent and people enablement side.”
That distinction sounds subtle, but it changes the philosophy of the system in meaningful ways.
Many legacy HR platforms were originally designed around transactions and recordkeeping. Employees and managers existed inside the system, but they were often secondary to the underlying administrative engine. The core workflows centered around storing information, processing approvals, and maintaining operational consistency.
Leapsome’s original focus was much closer to the day-to-day experience of managers and employees themselves. Development conversations, engagement, feedback, learning, and organizational effectiveness sat at the center of the product from the beginning.
As Jenny described the company’s expansion into HRIS, it became clear that Leapsome does not see operational HR and talent management as separate categories anymore.
Organizations themselves do not experience those functions separately. Managers are not thinking about whether a workflow belongs inside “core HR” or “talent management.” They are simply trying to run their teams effectively.
That orientation increasingly resonates with modern companies that want their HR systems to feel less like back-office infrastructure and more like operational systems that actively improve how teams work together.
One of the strongest sections of the conversation came when Jenny discussed how Leapsome is thinking about AI internally.
“We think a lot these days in jobs-to-be-done,” she said.
That framing feels increasingly important because AI is beginning to reorganize software around workflows rather than modules.
Historically, enterprise software evolved by adding features, dashboards, and increasingly specialized products. HR teams assembled stacks of systems that each solved a narrow part of the broader employee experience. One system handled engagement surveys. Another handled performance reviews. Another handled learning. Another managed employee records.
The friction often came from connecting all of those workflows together manually.
Managers preparing for performance conversations needed to gather information across multiple systems. HR leaders trying to identify organizational risks had to piece together fragmented context from disconnected tools. Even relatively simple workflows required substantial administrative coordination.
Jenny repeatedly returned to the idea of helping organizations move through those workflows faster and more effectively. The goal is reducing the amount of repetitive synthesis and administrative work surrounding the decisions humans still need to make themselves.
Many of the strongest AI use cases inside HR are not fully autonomous workflows. They are systems that help managers prepare more effectively, help HR teams surface patterns earlier, and help organizations move through operational processes with better context and less friction.
Another interesting part of the conversation centered around Leapsome’s global product philosophy.
At one point, Jenny joked that Leapsome tries to combine “the best of German engineering and best-in-class UX, ” which is critical in the US market.
Many HR platforms that originated in the United States were initially designed around US-specific assumptions about labor structures, management styles, workflows, and compliance requirements. International support often came later through localization layers or acquired infrastructure.
Leapsome’s European roots created a different starting point.
Jenny talked about how even workflows like performance management can vary substantially across regions and cultures. Expectations around feedback, hierarchy, communication, and employee development are not universal. Systems that feel intuitive in one country may feel unnatural in another.
That creates a much harder product-design challenge than translation alone.
Organizations increasingly want unified global systems, but employees still expect those systems to reflect local norms and operational realities. The challenge is not simply supporting multiple countries technically. The challenge is designing workflows that feel locally intuitive while still operating consistently across a global organization.
That becomes especially relevant for globally distributed organizations like Notion, where maintaining consistency across teams cannot come at the expense of local nuance and employee experience.
Listening to Jenny describe those decisions, it became clear how much global product design influences the underlying assumptions embedded into the system itself.
Toward the end of the conversation, Jenny talked about the importance of companies experimenting directly with LLMs and becoming comfortable with the technology themselves.
At the same time, she emphasized that organizations increasingly need to understand the philosophy of the vendors they partner with because the assumptions behind AI implementation matter just as much as the visible features.
We are moving into a world where most vendors can now demonstrate AI capabilities, and most can generate summaries, recommendations, copilots, or workflow automation.
The question is no longer ‘Does my vendor offer AI?’ Instead, it is, “Does my vendor’s design principles and AI philosophy resonate with my goals?”
How aggressively should systems automate sensitive workflows? Where should humans remain involved? How thoughtfully does the company approach employee data and organizational context? How much operational maturity exists underneath the AI layer itself?
Those questions are becoming strategic buying criteria.
By the end of the conversation, the broader throughline became fairly clear.
The historical separation between operational HR systems and talent systems is fading. AI is accelerating that convergence because workflows increasingly depend on unified context across the employee lifecycle. Managers want systems that help them operate more effectively, not just systems that store information. Employees expect software that feels connected and intuitive regardless of geography or organizational structure.
Leapsome’s positioning sits directly in the middle of that shift.
A platform that originally started from the people enablement layer is now expanding deeper into operational HR infrastructure while simultaneously rethinking how AI changes the workflows built on top of those systems.
Jenny kept returning to a simple idea throughout the conversation: HR software should do more than help teams administer processes. At its best, it should help managers lead better, employees grow faster, and organizations understand where they need to improve.
