How AI and process orchestration bring us a giant leap closer to the autonomous enterprise

The concept of the “autonomous enterprise'' has been thrown around for at least a decade. Back in 2014, Gartner was already talking about autonomous business as the ultimate destination on its Digital Business Development Path. But recent advances in artificial intelligence (AI) and automation have provided fuel for the autonomous-enterprise fire, and orchestration has brought that vision closer to reality than ever before.

So what are autonomous enterprises, how close are we to making them a reality, and what will it take to get there?

What is the Autonomous Enterprise?

Definitions of the autonomous enterprise are numerous, including these from Forbes and Gartner:

• Forbes: An autonomous enterprise can be defined as an organization that applies AI and automation to engagement, servicing, and operations to achieve what is essentially a self-driving business.
• Gartner: Autonomous business is a characterization of the “post-digital-business” period. It is a style of business partly governed and majority-operated by self-learning software agents, that provides smart products and services to machine-customer-prevalent markets, operating in a programmable economy.

An autonomous enterprise doesn’t necessarily operate without people altogether. Instead it enables humans to remove themselves from certain parts of the business ecosystem (while retaining ultimate control) so the processes within those parts of the business can self-optimize. An autonomous enterprise is able to detect events, anomalies and opportunities, and continually adjust processes, in real-time, to resolve those issues or seize those opportunities–maximizing performance against key metrics.

Two ingredients for autonomous business

Creating an autonomous enterprise requires two key ingredients. The first is a digital twin of the business that delivers an end-to-end view of how it runs, replicating how processes actually work and relate to each other across the entire organization. At Celonis we call this the Process Intelligence Graph, and it’s created by extracting and standardizing data from any source, then layering in decades of process knowledge and the latest AI technologies.

This digital twin enables the second key ingredient, which is process orchestration.

As mentioned earlier, business automation has so far mostly relied on RPA bots. Despite the somewhat misleading name, RPA doesn’t actually automate entire business processes, such as purchase-to-pay or order-to-cash. Instead it automates individual tasks that sit within those processes (and sometimes just individual actions within those tasks). This task automation is incredibly useful when work is repetitive, time consuming, and error-prone. But it’s not process automation.

A truly autonomous enterprise needs process orchestration software that sits above the task level, integrating systems, AI agents, and human work into a single operational fabric. Process orchestration acts as a control tower, with an overview of systems, processes and automations, and the ability to coordinate it all. With process orchestration drawing insights from the digital twin and coordinating the individual task automations, entire end-to-end processes can ultimately run and self-optimize without human intervention. Paradoxically, an intelligent orchestration layer enhances human control of the process by, as mentioned above, allowing people to focus on high-level work that requires deeper knowledge and understanding. In essence, it turns insight into action at scale.

As Celonis Lead Transformation Evangelist, Rudy Kuhn, outlined, RPA-style automations are a little like the individually automated parts of a car: the automatic headlights, windshield wipers, and lane-assist technologies that keep today’s drivers safe. To make the vehicle autonomous, all these individual automation systems (and many more) will need to be controlled and orchestrated by intelligent software, and informed by data from multiple sources, to get to a point where the car can actually drive itself.

AI and the autonomous enterprise

The key terms in the definition of an autonomous enterprise, “self-driving”, “self-learning”, and “self-optimizing”, indicate how autonomous enterprises must be able to learn for themselves to enable continuous improvement. And that’s what makes recent advances in AI so influential on their development.

Developments in AI mean the autonomous enterprise is now an achievable goal.

Until recently, business automation usually meant using Robotic Process Automation (RPA) – largely restricted to recurring, rule-based tasks that relied on structured data. Humans were still required for more complex tasks that needed experience and deeper expertise.

Now, with the advent of generative artificial intelligence (GenAI), AI is capable of extracting unstructured information, converting it into a structured form, and using it for decision-making. It can make decisions based on the sum of information, rather than individual pieces of data, effectively drawing on its own experience.

Developments in AI don’t just enhance existing automation opportunities. They allow automation to be expanded across organizations, with new use cases continually emerging for example in supply chain sourcing and procurement, finance and shared services, and business operations.

Introducing the Celonis Orchestration Engine

Process Orchestration is a strategic software category that serves as a real-time process framework and codifies business rules to steer processes live at scale. It fuses BPA (business process automation), RPA, and iPaaS (integration Platform as a Service) to seamlessly integrate systems and orchestrate processes along the entire value creation chain, ensuring operations flow smoothly end-to-end.

The Celonis Orchestration Engine coordinates complex workflows involving multiple AI agents, human tasks, and system automations across the enterprise. Celonis launched the Orchestration Engine over a year ago together with our partner Emporix to enable customers to digitize, connect and run end-to-end processes. In May 2025 at its Celonis:Next product showcase, Celonis announced that it had acquired the product from Emporix, to double down on its mission of helping companies successfully deploy and manage their AI and automation strategies.

Today, the Celonis Orchestration Engine is now generally available as a core capability of the Celonis platform.

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Process insights from the Celonis Process Intelligence Graph enable the Orchestration Engine to intelligently steer processes and make dynamic decisions at key points in a process. It’s a comprehensive solution for obtaining, working with, and using insights to drive business improvements. It’s also cloud-native, so it is built for scale and capable of managing millions of process iterations in parallel.

Unlike task automation tools, the Orchestration Engine is built for long-running, high-volume, and complex processes that span multiple systems and teams–making it foundational to agentic automation strategies.

How does the Orchestration Engine work?

The Celonis Process Intelligence Graph acts as the digital twin of the enterprise and feeds insights–known as trigger events–into the Orchestration Engine.

These trigger events drive an almost instant response and act as a starting point for executing a series of subsequent conditional layered sequences of tasks or automations. Using customized execution templates, the Orchestration Engine automatically and dynamically orchestrates actions within associated tools and systems–which could include Celonis Action Flows–to optimize performance against set business objectives.

The Orchestration Engine also monitors how the orchestrations actually execute and the results that are achieved, which are fed back into the Celonis platform to enable a process of continuous improvement . A Management Dashboard, with customizable execution templates, allows businesses to design and manage digital processes easily and quickly, without writing code.

A retail use case for the Orchestration Engine

The Orchestration Engine can be used to trigger automations and optimizations for a variety of business scenarios. Imagine, for instance, a retailer has an online marketplace, and wants to deliver a seamless customer experience, while also hitting targets around working capital and cost-cutting. The Orchestration Engine could be used to monitor and respond to realities revealed by the retailer’s back-end system data in the following ways:

• Improve inventory turns: Promotions or discounts could be automatically triggered to drive sales when there are excess stock levels for a certain product.
• Trigger spot buys or stock transfers: If the customer wants a product that is out of stock in one location, a stock transfer from another location or a spot-buy from the manufacturer can be triggered.
• Suggest alternative products: Customers or sales reps can receive proactive recommendations for substitutes when products cannot be fulfilled in time to meet the customer’s needs.
• Restrict payment options: When customers have a poor payment track record, their payment options can be automatically restricted, ensuring they pay upfront and the retailer is protected.

Leading companies like IVECO, Signify, and many others are already generating significant value with Orchestration Engine. For example, Vinmar International, a global chemical and plastics distributor, uses Celonis Orchestration Engine to optimize supply chain operations across offices in more than 40 countries supplying to over 100 nations.

“We've been looking for ways to drive automation and free up time in strategic processes,” said Abhi Banerjee, Director of Digital Transformation, Vinmar. “We identified the Tender for Shipment process as a great opportunity to reduce manual effort and cost. We’re already looking at new processes to orchestrate and will apply the learnings from this one.”