Agentic automation : The path to an orchestrated enterprise

In recent years, the introduction of AI has increased the power and impact of enterprise automation, enabling us to strive for ever-greater efficiency and productivity. At the same time, the processes these automations are empowering have also grown in complexity. Investment has poured into soloed enterprise systems, with the average large company now using over 175 enterprise applications across their workflows. Data has become more soloed and processes more fragmented. Many decisions within a workflow aren’t clear-cut, requiring people to step in—all of which adds to the operational burden. Finally, the complexity of these processes means they cannot cohesively be monitored, optimized, or fully automated.

A new era for automation—agentic automation—provides a new path forward. Combining agents, robots, AI, and people, agentic automation can automate even the longest, most complex processes end to end. Working effortlessly across disparate systems, it will deliver transformational outcomes across the enterprise, making businesses more autonomous and productive while enhancing the experiences of customers and employees. Agents are increasingly taking on the majority of work, while people continue and expand their roles as supervisors, decision makers, and leaders.

What does the agentic and robotic future look like?

Businesses have known and benefitted from robotic process automation (RPA) for years. Robots perform work tasks by interacting with screens, systems, and data like people do. They are rules-based, act predictably, and make deterministic decisions. This makes them highly reliable and efficient for routine tasks that don’t need adaptability or decision making skills—like entering data, processing transactions, or triggering responses.

AI agents are a much newer, emerging technology. Agents are AI-model-based, enabling them to work independently of people and improve over time. There are many different types of agents, but they are generally goal-oriented and able to use context to make proactive and probabilistic decisions. This makes them complementary to robots and ideal for complex processes that require high adaptability. Imagine you need to book a flight for work: an agent could plan the entire trip, comparing flight and hotel prices to get you the best deal before booking everything for you. And it could adhere to company policies, like cost, location, approved airlines and hotels.

Enterprise agents: controlled agency

Agents are core to agentic automation. But enterprises don’t just need autonomous agents who can do things—they need enterprise agents they can trust to do them safely, accurately, and reliably. Speaking at Ui Path FORWARD, our Chief Technology Officer Raghu Malpani put it succinctly: “You don’t just want agents. You want agents you can trust.”

However, there’s a technological challenge in achieving trusted agents. In every capability, there’s always a trade-off between reliability and autonomy. Compare very reliable but low-agency robots with high-agency but low-reliability agents. Traditionally, the more freedom you give a capability to act independently, the less predictable its outputs will be. In enterprise processes, unpredictability can be costly and risky.

Fortunately, there are ways to achieve both autonomy and reliability in agentic automation. We’re building first-class, enterprise agents combining high agency with the reliability we achieved long ago with our robots. We’re bending the curve from autonomous to trusted enterprise agents. We do this by helping customers understand how their agents reason and make decisions, and by giving them the tools to monitor, analyze, and improve their performance.

Agentic orchestration: bringing it all together

However, agentic automation is more than just trusted enterprise agents. It’s about transformative, end-to-end outcomes. That requires effective collaboration between all the components that comprise enterprise workflows and total visibility into how they’re working together. However, that isn’t always easy due to process complexity and limited visibility into those processes.

Agentic automation needs an orchestration layer to seamlessly orchestrate end-to-end processes across humans, systems, robots, and AI agents. This requires a gamut of capabilities like process management, process intelligence, automation, and agentic AI. Agents also need to be a key ingredient in the process management lifecycle, with tools to design, orchestrate, and monitor agentic workflows across systems.

Why is all this orchestration necessary? Consider vendor invoice processing, a common process that can be automated end to end with agentic automation. Dealing with a single invoice is a complex process that crosses numerous systems—from the mailbox to the enterprise resource planning system—and which demands action, reasoning, and decision making at several key stages.