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Many HR teams hear terms like workflow, AI workflow and AI agent thrown around, but most people are not entirely sure what each one actually means. The language feels technical, but the concepts are far simpler than people realise.
This short clip from our recent webinar with Kristjan and Jessie Schofer breaks the whole topic down clearly, using examples that make sense for everyday HR processes.
Jessie is the founder of Stakkd, a platform built to help HR and talent professionals cut through the noise and find the right tools for their teams. With a growing community of more than 13,000 professionals and more than 320 HR tools, Stakkd has become one of the most trusted spaces for exploring AI in HR.
Traditional automated workflows are deterministic. They follow a fixed sequence of steps triggered by a clear event. Think of something familiar, such as onboarding. When a new hire is confirmed in your ATS or through a form, a workflow might send a welcome email and add the person to your HRIS.
Another common example is contract creation. Once an offer is approved, a traditional workflow can automatically generate the correct contract template, populate the basic fields and send it for e-signing. It does this reliably every time, but it cannot adapt wording or adjust details unless you manually change the template.
Every step happens in a set order. Nothing changes unless you redesign it. The email looks the same every time. The workflow does not understand who the person is or what might need to be adjusted. You get consistency, but you do not get intelligence.
These workflows still have value. They reduce manual work and help teams stay organised. Their limitation is that they cannot adapt to the context surrounding each employee or situation.
An AI workflow looks similar on the surface. It is still step by step and entirely under your control. The difference is that you can place intelligent actions inside it.
For example, instead of sending the same welcome email, an AI step can write a personalised version based on the information you already have about the new hire. It can consider the role, location, previous interactions or anything else in the context window.
You can also add steps that check quality or accuracy. If someone uploads a photo for a background check or Visa application, the AI can validate whether it meets the required standard before the workflow continues.
What matters is that the workflow is still structured. You choose when AI is used, what it should look at and what happens next, and you have a full audit trail so you can see which prompt was used and why the output was generated. You can even pause the workflow and approve the output before it moves forward. HR teams often prefer this human in the loop approach, especially for communications or anything sensitive.
AI workflows give you more flexibility without losing control. They help teams automate the parts that take time but still keep judgement and responsibility where it belongs.
AI agents work in a different way. Instead of following a fixed sequence, an agent decides for itself which actions to take. It can write messages, check validation requirements, create documents and handle tasks in an order that it believes is correct.
Its decisions are guided by its context window, instructions and the tools it has access to. This makes it powerful, but it also means the system is more autonomous. It chooses the path rather than following one that you define step by step.
Agents can work on their own or collaborate with other agents, which is known as an agentic workflow. This is useful for complex situations with many unknowns, but it is not always the right fit for everyday HR processes that require consistency, transparency and control.
Responsible AI matters here, and teams should have a clear understanding of how decisions are made and where human approval is needed.
Agentic systems become more valuable when the task involves many variables or when the order of actions cannot be predetermined. Examples include advanced problem solving, coordinating multiple tasks at once or anything that requires decisions to evolve based on new information.
For most organisations, this is not the first step into AI. It is a future consideration once structured AI workflows are already delivering value and the team understands how to guide and govern them.
Here is the simplest way to understand the differences.
Workflow - A fixed, rules-based process with predictable steps.
AI workflow - The same structured process with intelligent actions built inside it, still fully controlled by the team.
AI agent - A more autonomous system that chooses which actions to take and in what order based on its instructions and context.
Many HR teams find that they do not need to jump into agentic systems to see meaningful results. AI workflows often deliver the strongest returns because they improve processes you already use every day. This could include tasks such as creating contracts from approved templates, coordinating onboarding steps, handling employee requests, managing approvals, guiding managers through probation reviews or coordinating training sign offs. These are everyday processes that benefit from clearer steps and less repetitive manual work.
The real advantage comes from redesigning the workflow itself. With AI, you are no longer restricted by old limitations. You can rethink steps, improve communication quality and reduce repetitive work in a way that feels natural for your organisation.
These smaller, manageable examples are where most teams start to show measurable value, whether that is time saved, smoother experiences or fewer manual follow ups. It is less about the technology you choose and more about how intentionally the workflow is designed.
If you have questions after watching the clip or reading the breakdown, send them our way and we will answer them.
