How to enhance robotic process automation with AI

How to enhance robotic process automation with AI

Robotic process automation improves efficiency and cuts costs. But RPA bots are hard to create and limited in scope. Here, we show how AI can enhance RPA.

Robotic process automation or RPA is the process of applying automation to repetitive business tasks. RPA can improve efficiency, save costs, and slash wasted effort. However, it suffers from some real issues. Creating a new RPA bot takes significant time and effort. Bots are dumb, so only the most predictable of tasks can be automated. And bots are also hard to chain together to automate more complex processes. Fortunately, some of these problems can be solved through the addition of artificial intelligence. And as we explain at the end, our AI bot factory makes it even easier.

A brief history of automation

Automation is the process of using a machine to perform a task that would otherwise need a human. The earliest forms of automation appeared during the industrial revolution. One of the earliest attempts at automation was the spinning jenny, a multi-spindle device for spinning wool into yarn. This allowed one worker to do the work of 8. However, this wasn’t true automation, since it still required a human to operate it.

Spinning jennies were an early attempt at automation
A spinning jenny

One of the first truly automated machines was the Jacquard loom. This machine transformed cloth production. It was able to weave cloth completely automatically and also allowed patterns to be programmed in. Indeed, it was such an efficient invention that such looms are still used today.

A set of Jacquard looms

World War 2 saw intense efforts made to automate aircraft and arms manufacturing. By the 1950s, companies began developing robots for automating assembly lines. Soon after, computer numerical control (CNC) allowed machines to perform complex machining tasks such as milling engine blocks. Nowadays, automation has produced autonomous mining vehicles, the pick and place machines that make our smartphones, and factories that produce a new car every 2 minutes. 

Pick and place machines are an example of physical robotic process automation
Pick and place machines can assemble complex circuit boards

Robotic process automation

Traditional automation as described above is about automating manufacturing and heavy industry. Factory owners turned to machines because they were faster, more efficient, and more accurate at the job than people. Recently, we have seen similar approaches being applied to automate business processes. For instance, you can use computers to complete simple and repetitive tasks like data entry. This became known as robotic process automation (RPA).

What is RPA

RPA involves you automating a repetitive business task by creating a “bot” or piece of software. This bot can be replicated hundreds of times and deployed across your company. For boring and repetitive tasks, the bot outperforms a human and won’t make mistakes. It also works 24/7 without needing breaks or holidays. As a result, companies are able to cut costs, increase their efficiency, and redeploy staff. 

You can use RPA bots to automate all sorts of processes. Typical applications include: 

  • Onboarding of new employees. 
  • Order processing and despatch. 
  • Stock ordering and stocktaking.
  • Adding a new customer to your books.
  • Processing employee expenses.

All of these tasks require a human to do a number of steps in the correct order. And any mistake can be costly. 

The benefits and drawbacks

RPA bots can provide significant savings for any business. Your bots are always available and require no paid breaks or holidays. Your bots never make mistakes, unlike your human workers. You can quickly duplicate your bots, making it easy to deal with seasonal demands or sudden peaks. Overall, this results in tasks being completed quickly, efficiently, and accurately. 

However, RPA comes with definite drawbacks. For a start, it isn’t trivial to create a bot. Your RPA bot is a pretty sophisticated piece of software that you have to develop and test properly. There are tools that help with this process, but you still need an expert to ensure the bot is designed and implemented well. 

Then there’s the problem of stupidity. RPA bots are inherently dumb. You can only use RPA used to automate certain tasks, and each bot can only automate a single process.

Simple. The task must be easy to break down into steps that can then be replicated. As an example, entering data into a form.

Repetitive. It’s only worth developing a bot for tasks that are very repetitive. In other words, the same task is done thousands of times. 

Predictable. RPA will fail unless you have a process that is identical each time. So, if a step might result in different outcomes, you can’t automate it.

Moreover, if there are multiple steps, you need to create multiple different bots. Most bots don’t play nicely together. So, integrating them is a challenge by itself. Worse still, if your inputs change a lot, RPA won’t work at all. You end up creating a complex rules engine that lists every input state and the correct action to take. 

RPA 2.0—adding intelligence

A couple of years ago, people started to add artificial intelligence to RPA bots. They coined the phrase RPA 2.0. This revolutionized RPA because it allowed you to automate tasks that were more complex and less predictable. For instance, once trained, an intelligent bot is able to cope with varying inputs and outputs. It still needs them to be predictable, but they don’t need to always be the same. 

However, the downside to RPA 2.0 is the need for adding artificial intelligence. AI is based on machine learning, and adding it to an RPA bot requires you to create a unique set of ML models. This is a hard task that can take a skilled data scientist months to get right. As a result, you can no longer use simple tools to create your RPA bots. Indeed, you now need to employ even more experts to help you get them right. And at the end of the day, your bot still can’t easily be chained together with other bots. Indeed, it may even be harder to achieve this. 

Sonasoft NuGene, the AI bot factory

Sonasoft NuGene is a unique unified AI platform. NuGene helps you by autonomously creating intelligent bots that can solve a variety of different tasks. We call it our AI bot factory because it makes it so easy to create bots. The process starts by giving NuGene your raw data. Unlike other platforms, NuGene learns from your data like a skilled data scientist. NuGene identifies patterns, forms hypotheses, and tests for causality. It then tests thousands of machine learning models to find the most accurate one. It then embeds this model into a bot that can solve all manner of business problems, from demand forecasting to anomaly detection and support ticket deflection.

NuGene’s bots are far more capable than the ones generated by RPA 2.0. For a start, the ML models are more robust, allowing the bots to cope with more complex scenarios. For another thing, the bots are easy to chain together, allowing you to automate complex processes. And then there’s the sort of data you can process. Normally, you can only use RPA to process numerical and textual data on a computer screen. But NuGene can also handle images (still and moving) as well as audio inputs. It also understands the concept of time. The upshot is, NuGene takes RPA fully into the AI era.


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