• Traditional automation (RPA) works excellently for predictable processes but hits a wall with exceptions.
• Agentic Automation adds AI agents that interpret information, make choices, and act autonomously within defined boundaries.
• UiPath combines deterministic robots, AI agents, and human oversight in a single managed platform, with Maestro as the central orchestration layer.
• The role of employees shifts from execution to assessment, direction, and improvement.
• Autonomy requires governance, observability, and adjustment. Without control, there is no scale.

Many organizations have heavily invested in automation in recent years. Invoices are processed automatically. Orders are checked by systems. Data moves back and forth between applications, and repetitive tasks are handled by software robots.

Yet, one persistent problem remains in many processes: exceptions. A document doesn’t have the expected structure. A customer asks a question that doesn’t fit into any standard category. An order deviates from the usual agreements. Or an employee must determine the next step based on multiple sources. At that moment, automation stops. An employee takes over, gathers the right information, and decides what needs to be done.

That makes sense. Traditional automation works best when a process is predictable and the rules are clearly defined in advance. This is precisely where the next opportunity lies.

From fixed rules to autonomous action

RPA, or Robotic Process Automation, is built around rules. You specify exactly what needs to happen: open system A, read the data, check a value, fill system B, send a message. As long as the process remains the same, this works perfectly. If the situation changes, someone must adjust the automation.

Agentic Automation works differently. An AI agent doesn’t receive a rigid step-by-step plan for every conceivable situation. Instead, the agent is given a goal, access to the right information, and clear boundaries within which it can operate. The agent can then perceive, reason, plan, and act. This brings automation within reach for processes where not every step can be predicted in advance.

What is Agentic Automation?

Agentic Automation involves deploying AI agents to autonomously execute business processes, including tasks that require interpreting information, making decisions, and involving multiple systems or people.

The difference from traditional automation lies primarily in how the process is executed, rather than the technology itself. In traditional automation, the organization defines every step in advance. In Agentic Automation, the organization sets the goal and boundaries, after which the agent determines the necessary actions within those limits. This enables a completely different type of automation.

It’s important to clarify: this is about automating and orchestrating processes on top of your existing system landscape. This is different from building new mission-critical software from scratch. Both have their place. In this piece, we focus on the automation side, specifically how UiPath addresses it.

How UiPath implements this

UiPath started as an RPA platform and has since 2025 built a full-fledged agentic layer on top of it. The strength lies in the combination: deterministic robots that reliably and predictably execute tasks, AI agents that interpret and decide, and a single management layer that ties everything together. A few building blocks involved include:

Agent Builder in UiPath Studio: here, you build and test agents, low-code or pro-code, in the same environment where robots are created.
IXP (Intelligent Xtraction & Processing): Extraction and Validation Agents extract usable data from unstructured documents, precisely where classic automation falls short.
Maestro: the orchestration layer that guides agents, robots, and people through a process, using process models in BPMN and DMN standards and ready-made case management scenarios, such as for claims.
Autopilot: natural language assistance for builders and end users.
AI Trust Layer: agent guardrails, PII masking, and central audit, so you maintain control over what agents can and cannot do.

The latter is no minor detail. It’s exactly what makes autonomous automation manageable.

Which processes become automatable?

Not every process requires an AI agent. For simple, predictable tasks, classic automation is often the best choice, and there’s no need to add AI. The real value emerges in processes with many exceptions, those that combine multiple systems, use unstructured information, require human judgment, or involve different follow-up steps.

Take an insurance claim, for example. Classic automation checks whether all required fields are filled in. An agent goes further. It interprets documents via IXP, combines information from multiple systems, checks the claim against applicable rules, requests missing data, and determines whether human review is needed. Maestro keeps everything together and escalates to an employee when a case falls outside the defined boundaries.

Or consider a manufacturing company. An agent detects a delayed delivery, checks inventory and order data, determines possible alternatives, and informs the right employee or suggests a next step. The focus is no longer on automating a single action but on an entire process where the situation can change along the way.

From isolated tasks to end-to-end processes

Agentic Automation looks beyond the individual task. The focus shifts to the entire process. An employee no longer needs to open five systems to handle a customer request. An agent retrieves the information, determines the necessary actions, and executes the process largely autonomously. In doing so, an agent collaborates with other agents, systems, and people. This makes end-to-end automation possible.

For organisations, this means the benefit is no longer just in efficiency per task. The greater benefit lies in redesigning processes as a whole.

What changes for employees?

More automation doesn’t mean people become redundant. It changes where people spend their time. When agents handle preparatory and repetitive work, employees focus on what requires human expertise: complex decisions, customer relationships, negotiations, creative solutions, and exceptional situations. The role shifts from executing every process step to assessing, directing, and improving processes.

Agentic Automation requires more than AI

The possibilities are vast, and autonomous automation brings new responsibilities. You can address an employee who makes a mistake. An agent that autonomously executes hundreds of actions requires a different form of control. Three things are essential in this regard.

Governance. Define in advance what an agent can and cannot do. Which decisions can it make autonomously, when is approval needed, and who remains ultimately responsible? In UiPath, you establish this with guardrails and policies in the AI Trust Layer.

Observability. You must be able to see what an agent does: what information was used, what decision was made, what actions were taken. Maestro and the central audit make this visible. Without this insight, it’s difficult to investigate errors or improve processes.

Adjustment. Autonomous processes are never perfect from the start. You test, measure, and adjust as processes change or an agent doesn’t deliver the desired result. Autonomy doesn’t mean letting go of control—it means organising it differently.

How Ciphix views Agentic Automation

At Ciphix, we don’t start by asking which agent we can deploy. We start with the process. During Sprint 0, we investigate where a process currently gets stuck, which systems are involved, and where employees still perform a lot of manual work. Often, the greatest opportunity lies precisely in the exceptions.

Next, we determine the right approach. Sometimes, classic automation is sufficient. Sometimes, better integrations are needed. And for processes with a lot of variation, context, and decision points, an AI agent might be the right solution. Technology is the means. The goal is a process that is faster, smarter, and more scalable.

Agentic Automation does not replace RPA

Agentic Automation doesn’t mean RPA disappears. On the contrary. The strength lies in combining different forms. A simple process runs entirely on fixed rules. An agent steps in when interpretation or decision-making is required. An employee takes over when a situation falls outside the agreed boundaries. This creates a hybrid process where each technology is used where it excels.

The question, therefore, isn’t “should we switch to Agentic Automation?” The better question is: which parts of our processes can we not automate today, and why? That’s often where the greatest opportunity lies.

The next step in automation

For years, organizations have focused on which tasks they could automate. With Agentic Automation, the question shifts from “which action can we automate?” to “which business process can we make smarter?” This difference seems small but has major consequences.

Processes that were previously too unpredictable are now within reach. Employees spend less time on exceptions and manual handoffs. And automation becomes feasible in places where it wasn’t previously cost-effective. The challenge isn’t to deploy as much autonomous AI as possible but to determine where autonomy truly adds value and how to keep it manageable. That’s where successful Agentic Automation begins.

Jeroen Blok is a UiPath specialist at Ciphix. If you’re interested or have any questions, feel free to contact us at ciphix.io/contact