What is digital process automation (DPA)?
Digital process automation (DPA) is the use of software to run multi-step business processes end to end – routing work, applying rules, moving data between systems and involving people only where judgement is needed. Typical examples are customer onboarding, purchase approvals, claims handling and employee onboarding. DPA focuses on the whole process and its outcome, not on automating single clicks.
Key takeaways
- DPA automates whole workflows; RPA automates individual screen tasks.
- The best candidates are frequent, rules-based processes that cross several systems.
- Map and simplify the process before automating it.
- AI adds understanding of documents and messages, turning DPA into intelligent automation.
How does DPA compare with RPA and BPM?
| Approach | What it automates | Best for |
|---|---|---|
| Business process management (BPM) | Designs and governs processes | Standardising how work should flow |
| Robotic process automation (RPA) | Repetitive clicks and keystrokes in existing apps | Legacy systems without APIs |
| Digital process automation (DPA) | Entire workflows across systems and people | Customer- and employee-facing processes |
| Intelligent automation / AI agents | Judgement-heavy steps: reading documents, classifying requests | Unstructured inputs such as emails and PDFs |
Which processes should you automate first?
- High volume: the process runs many times a week.
- Clear rules: most decisions follow known criteria.
- Multiple systems: data is re-typed between tools.
- Measurable: you can track cycle time, errors or cost.
Key figures
- McKinsey estimates that generative AI and other technologies could automate work activities that absorb 60 to 70 percent of employees’ time today. (McKinsey Global Institute, 2023)
- Forrester estimates the combined low-code and digital process automation market reached $13.2 billion by the end of 2023. (Forrester, 2024)
- Only 29% of applications are typically connected within organisations, according to a survey of 1,050 IT leaders. (MuleSoft Connectivity Benchmark, 2025)
"Automating a broken process just makes the mistakes faster. Simplify first, then automate."
How do you implement DPA step by step?
- Map the current process with the people who run it, including exceptions.
- Simplify: remove steps and approvals that add no value.
- Define rules and hand-offs: who decides what, and when.
- Integrate systems through APIs so data moves without re-typing.
- Automate and pilot with a small group, monitoring results.
- Measure and expand to the next process.
Where do AI agents fit?
Classic DPA struggles with unstructured input. AI can read an email or invoice, extract the relevant fields, classify the request and draft a response, then hand it to the automated workflow. Keeping a person in the loop for high-impact decisions keeps the process safe and auditable.
What are the benefits?
- Shorter cycle times and faster customer response.
- Fewer errors from manual data entry.
- Clear audit trails for compliance.
- Staff time freed for higher-value work.
Frequently asked questions
What is the difference between DPA and RPA?
RPA mimics a person clicking through applications. DPA redesigns and runs the whole process across systems, usually through APIs, with people involved only where needed.
Do we need to replace our systems to use DPA?
No. DPA usually connects the systems you have through APIs or, where none exist, RPA bots.
How long does a DPA project take?
A first process can often be automated in 4–8 weeks, depending on integrations and the number of exceptions.
Can AI make decisions in an automated process?
It can recommend or decide low-risk steps. For high-impact decisions, best practice is to keep a human approval step and log every action.
How Assystant can help
Assystant builds automation that connects your systems and adds AI where it helps – for example the AI chatbot that negotiates bulk-order pricing for Nutritionplanet. See our automation services or talk to us.