Hyperautomation: RPA, AI and process management combined
A software robot here, a smart integration there and, since recently, an AI assistant that sorts emails. Many organisations are already automating bits of their processes. The result is often a patchwork of separate solutions that each do their own job well, but do not work together. Hyperautomation is the answer to that. It combines RPA, AI, low-code and process management into one coherent approach, in which you automate processes from start to finish.
What is hyperautomation?
Hyperautomation is a company-wide approach to automating as many processes as possible by combining multiple technologies smartly. It is not about one tool, but about a strategy. You first map out how your processes really run, decide which technology works best where and then let those technologies work together.
The term was introduced by research firm Gartner, which has ranked hyperautomation among the most important technology trends for years. You can find the official definition in Gartner's IT glossary.
The difference between hyperautomation and RPA
RPA is one of the building blocks of hyperautomation, but not the same thing. A software robot automates a clearly defined task, such as transferring orders from a portal. Hyperautomation looks at the whole process that task is part of: how the order comes in, who assesses it, how it is processed and how the customer is kept informed.
| RPA | Hyperautomation | |
|---|---|---|
| Scope | One task or sub-process | Complete processes, from start to finish |
| Technology | Software robots | RPA, AI, low-code, API integrations, process mining |
| Starting point | Automating an existing process | Analysing the process, improving it and then automating it |
| Nature | Tactical: solving a specific task | Strategic: an organisation-wide approach |
You can see RPA as a tool, and hyperautomation as the blueprint in which that tool is used in the right place. You can read more about the basics of software robots on our page about robotic process automation.
The building blocks of hyperautomation
Hyperautomation consists of a number of technologies that each have their own role. Only when they work together do you get a fully automated process.
Which technology you use for which part depends on your systems and processes. In RPA vs API you will find a decision guide that helps with this.
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Process mining and process analysis
Before you automate anything, you want to know how your processes actually run. Process mining extracts that insight from the data in your systems. You can read more about this further on.
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Robotic process automation
Software robots take over repetitive tasks, especially in systems without an integration. They are the hands of the approach. You can read how to do this well in Implementing RPA.
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Artificial intelligence
AI understands language, reads documents and weighs up options. This means you can also automate processes in which free text or judgement plays a role. AI agents go one step further and independently direct parts of a process.
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API integrations and integration platforms
Where systems have an API, they exchange data directly and reliably. An integration platform such as Zoho Flow makes it easier to manage those integrations.
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Low-code and process management
With a low-code platform you redesign processes, build your own applications and set up workflows and approvals. Platforms such as Zoho Creator and Creatio are often the heart of the approach, because that is where the process itself is controlled.
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Monitoring and analysis
Dashboards show how processes are performing, where delays occur and what the automation delivers. That way you keep improving.
Process mining: knowing how your processes really run
Ask three colleagues how a process runs, and you often get three different answers. The process on paper is rarely the process in practice. There are detours, exceptions and steps that everyone carries out differently. If you automate such a process without knowing that, you automate the wrong things.
Process mining solves that. Every action in your systems leaves a digital trail: an order is created, an invoice approved, a ticket closed. Process mining software reads those trails and uses them to reconstruct how your processes actually run. You can see where delays occur, which steps are skipped and where work piles up.
That insight is the foundation of hyperautomation. You can see exactly which steps lend themselves to a robot, where an integration is missing and which parts you need to improve first before automation makes sense. For SMEs, this often starts more simply: with a structured process analysis together with the people who do the work, supplemented by reports from your existing systems.
The role of AI in hyperautomation
AI makes the difference between automating tasks and automating processes. Without AI, you are limited to steps with fixed rules and structured data. With AI, you can also automate the parts where interpretation is needed.
Think of reading and classifying incoming emails, extracting data from invoices with varying layouts, summarising case files or proposing a decision based on previous cases. AI agents can even independently direct part of the process and use software robots for the execution. This combination of RPA and AI is called intelligent automation. You can read more about it in RPA vs AI agents and on our page about AI agents.
Hyperautomation in practice: from customer request to invoice
What does hyperautomation look like in concrete terms? Take an installation company that receives service requests every day by email, by phone and through a web form. Without automation, each request takes up a lot of an employee's time: reading, scheduling, transferring data, invoicing. With hyperautomation, the process runs like this:
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Intake
An AI agent reads every request, recognises the type of fault and the urgency and extracts the customer details and address.
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Registration
Via an API integration, the request is automatically created in the CRM, linked to the right customer record.
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Scheduling
A low-code workflow decides which engineer gets the job based on region, type of fault and availability, and sends the customer a confirmation with a time slot.
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Suppliers
If parts need to be ordered from a wholesaler without an integration, a software robot logs in to the ordering portal and places the order.
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Completion
After the visit, the engineer records the work carried out in an app. The workflow prepares the invoice and a robot processes it in the accounting package.
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Insight
A dashboard shows how many requests come in, how quickly they are handled and where delays occur.
Each step uses the technology that suits it best. AI for understanding, APIs for stable exchange, low-code for control and RPA for the systems without an integration. Together they form one continuous process, in which employees only step in where their knowledge is really needed.
What does hyperautomation deliver?
The gains of hyperautomation are not just the sum of separate automations. Because the parts work together, the effect is greater than that of each part on its own.
You can find more background on how larger organisations use hyperautomation in a knowledge article from UiPath.
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Shorter lead times
Processes run on without hand-over moments. A request that used to take days to get through is now handled within hours.
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Fewer errors
Data is recorded once and then passed on automatically, without retyping.
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Overview and control
You see in real time how processes are performing and can make targeted adjustments.
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Scalability
As your organisation grows, the process grows with it without the workload increasing proportionally.
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Better customer experience
Your customers notice faster responses, up-to-date status information and fewer errors straight away.
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More valuable work
Employees spend their time on customer contact, advice and improvement instead of administration.
Hyperautomation as a driver of digital transformation
Digital transformation is about more than new software. It is about an organisation that works differently: data-driven, agile and customer-focused. Hyperautomation is one of the most powerful accelerators of that, because it does not just digitise processes, it also makes them smarter.
The road there usually runs in phases. Organisations start with separate automations, for example a first software robot. Then comes the step towards coherence: integrations between systems, a central platform for workflows and the use of AI. In the final phase, processes are continuously measured and improved. Hyperautomation is then no longer a project, but a way of working.
Is hyperautomation feasible for SMEs?
Hyperautomation sounds like something for multinationals with large IT departments. Yet for SMEs it is often very feasible. The big advantage: you do not have to tie dozens of separate systems together. Many SMEs already work with a platform that brings most of the building blocks together.
You can read which combination suits your organisation best in Choosing RPA software.
The risks of hyperautomation
The more you automate, the more important it becomes to stay in control. These are the pitfalls you want to avoid.
How to get started with hyperautomation
You do not have to do everything at once. A practical route:
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Choose one end-to-end process
Go for a process that takes a lot of time and touches several departments or systems, such as order processing or customer service.
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Map out the process
Include the detours and exceptions too. Use data from your systems where possible.
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Improve and simplify
Do this before you start automating.
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Choose the right technology for each step
You choose from API, RPA, AI or low-code.
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Build, test and measure
Measure the result and set up governance and management.
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Expand
Then tackle the next process, and reuse what you have already built.
You can read step by step how to approach implementing the RPA components in Implementing RPA.
An order now runs from receipt to invoice without anyone having to retype anything. We only step in when something is out of the ordinary.
Take the step from separate automations to hyperautomation
Have you already automated a few processes, but are you missing the coherence? Or do you want to get it right from the start, with an approach that grows with your organisation? Hyperautomation helps you move from separate solutions to processes that work from start to finish.
Mobile XL guides you through every step. We map out your processes, determine which technology delivers the most for each part and build a coherent solution with Zoho RPA, Zia Agents, Zoho Flow, Zoho Creator, Creatio or Collabotics. Step by step, affordable and always GDPR-compliant.
Frequently asked questions about hyperautomation
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Hyperautomation is an organisation-wide approach in which you combine multiple technologies, such as RPA, AI, low-code, API integrations and process mining, to automate processes from start to finish.
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RPA automates a clearly defined task with software robots. Hyperautomation looks at the whole process and uses the technology that suits each step best. That makes RPA one of the building blocks of hyperautomation.
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The main building blocks are process mining and process analysis, RPA, AI and AI agents, API integrations and integration platforms, low-code and process management, and monitoring with dashboards.
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Process mining uses the digital trails in your systems to reconstruct how processes actually run. That shows you where the delays and detours are, so you know exactly what to improve and automate.
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Yes. Many SMEs already work with a platform that brings most of the building blocks together, such as Zoho One with Zoho RPA, Zia Agents, Zoho Flow and Zoho Creator. By working in steps, you keep the investment manageable.
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Choose one end-to-end process that takes a lot of time, map it out, improve it and choose the right technology for each step. Measure the result and then expand to the next process.
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Shorter lead times, fewer errors, real-time insight into your processes, better scalability and a better customer experience. On top of that, employees have more time left for work that adds real value.
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AI makes it possible to also automate steps that require interpretation, such as reading emails or extracting data from documents. AI agents can also independently direct parts of a process.
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The main risks are a proliferation of separate solutions, automating without improving, wanting too much at once, insufficient security and too little attention to the people who work with the processes.
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Hyperautomation is one of the most powerful accelerators of digital transformation. It does not just digitise processes, it also makes them smarter and measurable, so your organisation becomes more agile and data-driven.
Curious which process you could automate end to end first?
Book a no-obligation consultation with one of our specialists.