The missing link between AI and business automation? Process intelligence.

In life, there are some things that simply go together. Like salt and pepper, mac and cheese, or peanut butter and jelly.

Over the last few years, AI and automation has emerged as one of these superior pairings. Enterprises across a range of industries are integrating AI and machine learning into their businesses to automate processes – improving productivity, reducing errors, optimizing resources, and driving business outcomes. And who doesn’t want that?

There’s no debate that AI and automation have established themselves as natural partners. But many organizations don’t realize there’s an element missing from the equation – a secret ingredient that transforms AI and automation into super-powered business process management.

AI and automation: a match made in process heaven

A whole industry has sprung up around combining artificial intelligence and automation in the form of Intelligent Process Automation (IPA). The global IPA market is expanding rapidly, valued at $14.55 billion in 2024 and expected to grow at a CAGR of 22.6% between now and 2030.

IPA integrates AI with traditional automation techniques so that, instead of simply automating routine repetitive tasks, companies can bring cognitive technologies like AI agents and copilots into the mix, and explore automations that adapt to business needs. As well as following set instructions, IPA can learn, adapt, and improve over time – essentially thinking for itself. This makes it a step up from Robotic Process Automation (RPA), where bots can’t think beyond the boundaries of their set task.

What’s the difference between AI-powered BPA and RPA?

As the IPA market matures, it’s worth taking a minute to zoom in on its fundamental building blocks – BPA and RPA – as well as how they differ.

First up, Business Process Automation (BPA) has the ability to redesign and orchestrate whole workflows across different systems, using APIs, rules, and human-in-the-loop (HITL) steps. BPA solutions can route work, enforce SLAs, and even handle exceptions, helping to reduce hand-offs, save time, and minimize running costs.

By contrast, RPA targets repetitive rule-based tasks at the UI level, for purposes like data entry, report generation or form filling. As mentioned earlier, RPA is limited to its specific task – so think of BPA as the conductor of the overall journey, who might call up an RPA bot to carry out a particular leg of that journey.

What to look for in an AI-powered BPA solution?

A BPA solution is a fantastic addition to the modern tech stack – enterprises can lean on BPA to orchestrate everything from customer onboarding and KYC checks to Claims Handling, Procure-to-Pay, and Order-to-Cash processes. Here are some qualities and capabilities to be on the look out for when you’re evaluating a BPA platform:

• Integration-first architecture: A wide range of ready-made connectors and APIs, and the ability to call an RPA to perform simple logistical steps.
• HITL and case management: Dynamic routing, approvals, SLA timers, and exception handling that can seamlessly blend automation and human involvement.
• Scalability and reliability: Handles surges in documents, data, and integrations, including re-attempting when certain steps fail (e.g. an outage or timeout).
• Security and governance: Offers roles and permissions, has clear audit trails and encryption, as well as robust compliance options.
• End-to-end observability: Live dashboards offering real-time updates, a wide range of key metrics (e.g. cycle time or first-pass yield), alerts, and “what-if” testing.
• Compatibility with process intelligence platforms: Integrates with leading process intelligence platforms like Celonis, ensuring BPA has access to the unique context of your business processes, to maximize the effectiveness of automation efforts.

So what’s the missing piece of the AI process automation puzzle that process automation needs to be even more effective?

Process intelligence: The missing ingredient

Process intelligence allows AI to speak the language of your business. It combines data from innovative technologies like process mining with standardized process knowledge gained through years of process optimization experience, so AI has the context it needs to understand your business processes end-to-end. The situational awareness enabled by process intelligence gives AI the power to adapt to business needs and drive smarter process automation.

As Etienne Kneschke, Executive Director Business Process Management at KARL STORZ SE & Co KG, explained: “Process intelligence is the foundational enabler of generative AI-based automation in enterprises, as it feeds LLMs with the essential contextual understanding they need, in order to know how the business runs across systems, departments, and regions.”

Without the context provided by process intelligence, AI and automation can be a risky combination. No matter how advanced machine learning algorithms are, if they learn from wrong or incomplete data, they can end up automating sub-optimal processes and ultimately make the situation worse. Without an understanding of end-to-end operations, automating one business process with AI tools can have unintended consequences elsewhere in the organization.

Celonis delivers process intelligence through the Process Intelligence Graph, which extracts data from all your business systems so you can see how objects and events interact, how processes are interconnected, and how your business runs. It layers in standardized process knowledge and AI to form a connective tissue for your business.

Powering AI process automation

When AI is fed with data that has been contextualized with process knowledge, it can power intelligent automation using a variety of tools. The Process Intelligence Graph, for instance, is system-agnostic and can trigger automations in whatever tools are already available in the customer’s tech stack. For Microsoft users this might be Power BI AI and Power Automate, while for others it might be an RPA tool.

In addition to amplifying the effectiveness of any existing automation technology, Celonis has its own AI capabilities and automation solutions:

• Action Flows are used to define and orchestrate process automations. They are fully connected to the Process Intelligence Graph and can be set up in minutes through an intuitive, low-code interface with premade connectors.
• Annotation Builder is a no-code tool that uses generative AI (GenAI) to reason through data, generating decisions and recommendations for actions. Users can define rules in natural language, making this form of process automation particularly accessible.
• LLM for PQL Generation is another GenAI tool that turns user queries into Process Query Language (PQL), the language used to turn process data into process intelligence.
• Process Copilot is an evolution of LLM for PQL Generation that uses Natural Language Processing (NLP) and conversational AI to make interacting with the Celonis platform as simple as chatting to a colleague.
• AgentC is a suite of AI agent tools, integrations, and partnerships that enables users to develop AI agents or use pre-built AI agents, powered by Celonis Process Intelligence (so they truly understand how your business runs).

Explore the different strengths and use cases of AI assistants, copilots, and agents by joining them on an exotic business trip in our e-book, Destination AI: Unpacking AI tools.

AI and automation in action

Process intelligence, AI, and automation can work together to drive new levels of observability and actionability. Intelligent automation use cases can be both reactive, detecting and resolving issues in real time, and proactive, helping businesses take action to avoid or resolve problems before they even arise. Proactive use cases are supported by technologies that help businesses see how processes operate and interact across the organization, such as object-centric process mining (OCPM).

Examples of intelligent automation include:

• B3 implementing an AI agent to automate the entire contract renewals process, from understanding contracts to communicating with suppliers.
• Campari co-developing an AI-powered collaboration agent with Celonis and Rollio to expedite the resolution of blocked sales orders.
• PepsiCo using Action Flows to automate the creation and sending of dunning notes for customers to collect on overdue receivables, helping the teams save valuable time.
• Florida Crystals using intelligent automation to send daily alerts on upcoming cash discounts, so the Accounts Payable team can act upon them.

Moving forward with AI automation

There’s no question today that AI can be used effectively for business process automation. But rushing into AI-powered automation without first creating a layer of data that’s been contextualized with business process knowledge (aka process intelligence) to inform that AI automation can have unforeseen consequences.

The Celonis Process Intelligence Platform provides a common language between teams, systems, and processes. It’s system-agnostic, so it can seamlessly connect to BPA solutions and feed AI the crucial, unique business context it needs to have a real and transformative impact on your organization.

Supported by our Process Intelligence Platform, AI and automation can make processes work across your entire business.

Ready to hear more about the Celonis Process Intelligence Platform, and how it can supercharge your automation initiatives? Get in touch with our team and we’ll arrange for you to talk to an expert.