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.

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:

1. 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. 

2. 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 will require process orchestration software that sits above the task automation level and brings together these individual automations. 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.

As Celonis Lead Transformation Evangelist, Rudy Kuhn, recently outlined, RPA-style automations are a little like the individually automed 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 Emporix Orchestration Engine

Celonis and our technology partner Emporix have co-developed the first process-context-aware orchestration solution in the digital space. The Emporix Orchestration Engine is a process orchestration platform capability that leverages Process Intelligence to automate processes, end-to-end, in real time, helping businesses establish agile data-driven operations and increase overall efficiency. An evolution of the Emporix CXP, it’s a smarter, more layered, and more dynamic way of automating processes than has been possible in the past.

Orchestration Engine dashboard

Using the Celonis Process Intelligence Graph, the Orchestration Engine is able to make dynamic decisions to drive key business outcomes. It’s a comprehensive solution for obtaining, working with, and using insights to drive business improvements and ensure customers have a positive and seamless cross-channel experience.

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 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 inform a process of continual learning. 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 Emporix 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 Optimization 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.

The Autonomous Enterprise is achievable 

A business that operates entirely without humans in the loop is neither realistic nor desirable. But – with combinations like the AI-driven Celonis Process Intelligence Graph and the Emporix Orchestration Engine – enterprises where end-to-end processes can run and continually self-optimize without human intervention are already a reality. In fact, some of the forward-thinking businesses we work with already operate this way today. 

For a more detailed exploration of how Process Intelligence and process automation can make the autonomous enterprise a reality for your business, speak to your Celonis Account Executive and Value Engineer.

Bill Detwiler

Senior Communications Strategist and Editor Celonis Blog

Bill Detwiler is Senior Communications Strategist and Editor of the Celonis blog. He is the former Editor in Chief of TechRepublic, where he hosted the Dynamic Developer podcast and Cracking Open, CNET’s popular online show. Bill is an award-winning journalist, who’s covered the tech industry for more than two decades. Prior to his career in the software industry and tech media, he was an IT professional in the social research and energy industries.