We have an opportunity to rewire how an enterprise operates, and in the process, rewire work itself.
Gerrit Kazmaier
President, Product and Technology
Workday
AI has started a new, deep innovation cycle that is rapidly transforming work. For the first time, we have computational reasoning—something that we didn’t have before. We needed humans for reasoning. This is huge because machine reasoning is unlimited, and that empowers us to redefine workflows, improve employee experiences and customer outcomes, and tackle problems we never thought imaginable.
This innovation cycle is changing everything about the way we work. We are ushering in an age of unlimited reasoning, and it’s going to create a limitless enterprise—where we are completely unconstrained by everything we knew before.
This innovation cycle is changing everything about the way we work.
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So then, why is it that many organizations are failing to fully capture the impact of their AI investments? It’s because their agents, copilots, and AI tools are spread across disconnected systems and outside the workflows that actually run the business. They’re using bolted-on tools that don’t have the context and data as their core systems, and so accuracy suffers and people get frustrated.
It doesn’t have to be this way. We have an opportunity to bring it into the core systems and processes that run the business. We can rewire how an enterprise operates, and in the process, rewire work itself.
AI by design is probabilistic by nature, predicting and recommending based on patterns. While powerful, this means that applying it to high-stakes enterprise workflows like payroll or closing the books—where the margin of error is zero—creates risk. Trying to use raw AI without processes and context is like running a train without rails. Without proper governance, organizations can unwittingly create “lawless agents” that create risk.
Imagine for a minute sitting down to do your own taxes without any guardrails or structure—just sitting down with a pencil and writing down whatever pops into your head. Would you end up with a dependable outcome? Of course not. To do your taxes, most of us need a tool like a calculator, an expert like a tax accountant, or even some software like TurboTax.
AI models are like that, too. To deliver results with precision, like humans, they need tools, expert systems and APIs to operate accurately.
To deliver results with precision, like humans, AI models need tools, expert systems and APIs to operate accurately.
For AI agents to do real, consequential work in the enterprise, they require more than just a great large language model. They need a strong foundation built on:
A deep understanding of how work actually happens within an organization.
Trusted business processes that act as guardrails for mission-critical work.
The right permissions, controls, and audit trails to ensure compliance.
Purpose build agentic APIs and tools to execute complex tasks
This is why we say the future is not a choice between AI and SaaS systems; it will be hybrid. And it will require agentic AI solutions built to work side-by-side with software.
For the last two decades, enterprise software systems delivered the structure required for business-critical processes. SaaS transformed HR and finance, moving them from paper records to cloud platforms that manage payroll, close the books with precision, and ensure compliance across countries for hundreds of thousands of workers.
But enterprise AI needs a continuous flywheel of data, context and action in order to function. With this flywheel in place, increased data leads to better context, which improves the AI system, and drives more usage.
Building this flywheel is impossible though without a unified model and a clear business process framework. Legacy software systems, having been pieced together as bespoke solutions over years, are too fragmented to feed the flywheel and make AI work well at an enterprise level—creating friction for vendors that are struggling to transform old ways of working into automated, AI-enabled systems.
On top of that, enterprises have high expectations for their systems of record. Our underlying business processes are deterministic by design. They deliver consistent, auditable outcomes, because HR and finance systems need to be right 100% of the time. The margin of error is zero; and AI getting it “almost right” is wrong.
AI, on the other hand, is probabilistic by nature. It reasons, predicts, and recommends based on patterns and likelihoods. In order to get the precision and accountability required for mission-critical work, enterprise AI must be embedded within a trusted foundation, allowing probabilistic AI to deliver deterministic outcomes.
AI demands that we rethink every enterprise process. In the future, everyone will work alongside hundreds of AI agents—each with specialized skills and organized to run continuous end-to-end processes in HR and finance.
That’s why it’s so powerful to pair AI with a system of record, like Workday.
AI demands that we rethink every enterprise process.
With the right rails to run on, agents stop being probabilistic guessing machines and begin operating on deterministic rails—inside trusted business processes, with the same security, permissions, and audit trails customers already rely on.
We can automate back-office work that used to require human judgment alone. We can make possible what simply wasn’t before. And we can change how people experience work altogether.
Imagine a world of work where every candidate has a personal recruiter, every employee has a personal coach, and every CFO has an always-on audit team. We can answer every employee question as soon as it’s asked, and show up for our customers through their toughest moments.
This is the future of HR and finance. This won’t just change how work gets done; it will change how work feels.
We’re heading toward a world where enterprise platforms are evolving from systems of record into systems of action—focused on delivering business outcomes, not just completing processes.
In that world, humans focus on what humans do best: judgment, creativity, empathy, relationships, leadership.
And AI agents handle what machines do best: pattern recognition, workflow processing, compliance checking, scenario modeling, and complex task execution.
Within these secure rails, enterprises that succeed in the AI era will combine intelligence with trust, speed with control, and automation with accountability—forging the path to an entirely new work day that fundamentally changes how we get work done.
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AI has been a gamechanger across nearly every industry and marketplace. But realizing the true value of AI requires buy-in between different stakeholders. In this AI Masterclass, learn how you can make the most of AI for finance, HR, and more.