Over the past few days, I came across an article by Joe Schmidt a partner at Andreessen Horowitz arguing that the rise of AI-native enterprise software could eventually make platforms like Workday vulnerable for the first time in decades.
The article made several strong points.
It highlighted the operational complexity inside modern HR systems like long implementation cycles, consultant-heavy deployments, fragmented reporting, spreadsheet dependency, rigid workflows, and the enormous cost of maintaining enterprise HR infrastructure.
It also argued that AI is changing enterprise expectations fundamentally enough that a new generation of HR platforms could emerge.
In many ways, I agree with the core premise. But I also think the conversation needs more nuance because while AI is absolutely reshaping enterprise software, the future of HR technology is not simply about replacing legacy systems with chat interfaces and agents. The deeper transformation happening underneath is about something much bigger:
Organizations are moving from administrative software toward organizational intelligence systems.
And this distinction matters.
Why systems like Workday became dominant in the first place
It is easy to criticize enterprise HR systems today as many HR professionals have experienced difficulties working with them. Things like navigating overly complex workflows, relying on spreadsheets outside the platform, coordinating across disconnected systems, waiting on consultants for configuration changes, and spending weeks generating reports that should take minutes.
But it is important to understand why these systems became dominant. Platforms like Workday were not built primarily to be delightful consumer-grade experiences. They were built to solve enterprise coordination problems at scale. At Hafinen we’ve learnt that large organizations require compliance, auditability, access control, payroll reliability, process governance, data consistency, and operational continuity across thousands or hundreds of thousands of employees. This is an extraordinarily difficult problem.
Enterprise HR systems became successful because they created structure, standardization, and operational control in environments where mistakes carry legal, financial, and organizational consequences. The fact that many of these systems remain deeply embedded despite widespread frustration is not accidental.
It reflects the reality that in enterprise infrastructure stability often matters more than elegance.
But AI is changing what organizations expect
What AI changes is not just the interface layer but the expectations. For years, enterprise software was designed around forms, approvals, dashboards, and structured workflows.
Humans interpreted the data.
Humans coordinated the processes.
Humans connected the systems together.
The software primarily acted as a repository and workflow engine. AI is changing that model.
Organizations are now beginning to expect systems that can understand context, surface insights proactively, automate coordination, generate workflows dynamically, support decision-making, and adapt continuously to organizational change.
This is not just a feature evolution but rather an architectural shift.
The same way cloud computing reshaped enterprise infrastructure over the last two decades, AI is reshaping how organizations interact with operational systems today. And it may become one of the most important categories affected by this shift.
The problem with treating HR as pure administration
One of the biggest limitations of traditional HR technology is that most systems were designed to manage administrative processes rather than understand organizations themselves.
They manage records, approvals, permissions, compensation structures, organizational hierarchies, and compliance workflows. But organizations are not static process diagrams.
They are living systems made up of people, relationships, communication patterns, leadership structures, trust dynamics, incentives, collaboration, adaptability, and culture. As organizations become increasingly distributed, fast-moving, and AI-assisted, these human dynamics become even more important.
The companies that succeed over the next decade will not compete solely on operational efficiency. They will compete on alignment, adaptability, leadership effectiveness, workforce intelligence, talent development, and organizational resilience. This requires a different category of software thinking.
AI alone is not the answer
At the same time, I think there is also a dangerous oversimplification happening in the market right now. Many conversations around “AI-native HR” focus almost entirely on automation. But replacing forms with chat interfaces is not enough. Adding agents on top of legacy workflows is not enough. And AI itself is rapidly becoming commoditized.
The long-term value will not come from simply having AI features but rather building systems that deeply understand how organizations function. This means understanding team dynamics, communication patterns, workforce behavior, organizational bottlenecks, leadership effectiveness, hiring alignment, operational friction, and human collaboration at scale.
The next generation of workforce platforms will need to move beyond being systems of record. They will need to become systems of organizational intelligence.
The future is probably hybrid not replacement
I also believe many people underestimate how conservative enterprise HR environments actually are. HR systems sit at the center of payroll, compliance, labor law, identity, performance, benefits, workforce planning, and organizational governance. And large enterprises do not replace those systems casually as the switching risk is enormous.
That means the future may not initially look like wholesale replacement of incumbent systems. Instead, the more realistic near-term evolution is likely stable systems of record underneath, with intelligent operational layers built on top.
We are already seeing this pattern emerge across enterprise software where we have AI layers on top of CRMs, AI copilots on top of analytics systems, AI orchestration on top of operational infrastructure.
HR technology will likely evolve similarly, and the disruption may happen first at the intelligence and interaction layer before it happens at the infrastructure layer. This distinction is important because it changes how companies should think about building.
What we believe at Hafinen
At Hafinen, we believe the future of workforce technology is not simply about digitizing HR workflows more efficiently. It is about helping organizations understand themselves better. We believe the next generation of platforms must help organizations understand alignment, identify operational friction, improve leadership visibility, strengthen collaboration, support employee growth, and adapt continuously as the nature of work evolves.
AI plays an important role in enabling this future , but the goal is not replacing humans. The goal is helping humans work better together inside increasingly complex organizational environments.
This is critical in a world where organizations are beginning to operate with distributed teams, hybrid work environments, autonomous AI agents, cross-functional collaboration structures, and rapidly evolving workforce models. In this world, organizational intelligence becomes infrastructure.
The companies that win the next decade will not simply automate HR operations but rather build systems capable of understanding how organizations actually function. So things like how people collaborate, how teams evolve, how leadership scales, how decisions flow, and how organizations adapt over time. That is the future we believe Hafinen is being built for. And while the enterprise HR landscape may evolve more slowly than many expect, one thing feels increasingly clear: The future of workforce technology will not be defined by forms and approvals alone. It will be defined by intelligence, adaptability, and a deeper understanding of how organizations truly work.
