Robotic process automation (RPA) and low-code technologies both belong in your automation plans and tool kit. But how do they differ? How do they complement each other? And how can they help automate everything from routine tasks to complex processes? Much confusion persists, so let’s break it down to help you understand these terms and explain them to others.
With RPA, a software robot imitates the way a human works with a computer to do simple, high-volume, and repetitive tasks. For example, an RPA bot can click around a user interface, browse the web, grab data, and enter keyboard inputs. In other words, RPA can do the kind of tedious work that bores people, freeing them up to do other things. It also works faster than people and eliminates human error. What are some common RPA examples? Areas where business users apply these automation tools for productivity gains include transaction reconciliation, employee and customer onboarding, and billing, just for starters.
But wait, doesn’t that kind of automation sound a lot like AI? Not quite: While RPA mimics what a human does, artificial intelligence (AI) mimics how a human thinks. Also, while many AI tools use technology like machine learning and neural networks to gain intelligence over time from data and experience, RPA tools do not. RPA tools are limited to performing simple, repetitive tasks that don’t require human-like cognitive decision making.
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Low-code platforms help people—professional developers and citizen developers alike—build software applications using intuitive, visual development tools, such as drag-and-drop modelers and point-and-click interfaces. Leading low-code platforms enable the rapid development, deployment, and regular maintenance of powerful business applications.
That means using a low-code approach to development lets IT and business pros collaborate easily on building custom applications using a visual approach to development. And they can build more applications in less time than they could with traditional coding. Because low-code applications can be drawn and configured instead of coded, they offer much greater speed and ease of maintenance. Low-code development platforms also deliver agility and compliance benefits.
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So, you’ve decided RPA would benefit your organization’s business processes. How will you build your bots? This is where low-code platforms come into the picture. It’s easy to gloss over the fact that both AI and RPA are sophisticated business process automation technologies that, when taking a traditional high-code approach, require expertise with many specialized technical concepts, like data engineering, machine learning, browser automation, and operating system integration. Recruiting and retaining talented people for AI and other kinds of automation work remains a pain point for many IT organizations. If you don’t happen to be sitting on a pile of highly skilled software engineers looking for work, you’ll need help designing and implementing high-code automation.
Low-code provides a compelling solution to this problem. It strikes a balance between traditional high-code and no-code technology. With a low-code platform, you don’t need highly specialized AI software developers to build your automations, but you keep the extensibility that code can provide—you maintain the ability to use code to customize automations to fit your business needs, if you so choose.
[ Read our related article: Low-Code vs No-Code: The Differences & Similarities. ]
More importantly, low-code is much faster and more agile than high-code software development, which is imperative when adjusting to constant changes in markets, processes, and external regulations. That’s why agility is a top goal of many digital transformation projects.
Making low-code part of your automation strategy, often alongside both RPA and AI, ensures rapid, agile development and maximizes your ability to quickly make changes over time. Look for an AI-powered process platform (also known as a hyperautomation platform) that brings together all of these technologies, along with data fabric capabilities, to reap additional speed, agility, and maintenance benefits.
[ Learn how to successfully implement end-to-end process automation strategies. Get the Process Automation Guide. ]