RPA vs AI (and Everything in Between)

RPA vs AI (and Everything in Between)

As technology advances, it comes with more jargon and specialist terminology than ever before. What is RPA? What is AI? And what is cognitive automation?

Today’s business environment can be a daunting one. Technology is moving at a rapid pace, and there are lots of jargon terms in use which can confuse matters even more. There are two terms in particular which are causing confusion in many sectors – RPA and AI. While some people are under the impression that these two things are the same, in fact this isn’t the case at all. Here, we take a look at what these two terms mean so you can have a better understanding of the latest technologies and how they can help your business to grow, thrive and be more competitive within its sector.

What is RPA? And what is AI?

We can’t address the differences between RPA and AI without knowing precisely what these terms mean. Let’s take a look at RPA first:

RPA stands for Robotic Process Automation. In short, it is a software robot which can mimic human actions. It uses preconfigured software which utilizes pre-defined activity and business rules to autonomously execute a combination of activities, tasks, transactions and processes across software systems to deliver the service or desired result without the need for human management.

So how is this different to AI?

AI, or Artificial Intelligence, is a term which refers to machines which can simulate human intelligence. It involves combining cognitive automation with machine learning, hypothesis generation, analysis, language processing and algorithm mutation to produce analytics and insights at the same capability level as a human, or even higher.

The intelligent automation continuum

RPA and AI are opposite ends of the IA (or Intelligent Automation) continuum, which also comprises cognitive intelligence and machine learning. It’s important for businesses to recognize that RPA and AI are all part of a single spectrum and there is no need to race to the end of it. All elements of the IA continuum have a part to play in today’s industries and they can all benefit companies when harnessed correctly.

A closer look At RPA

RPA is arguably the latest development in automation technology. As a super-fast programming method, it executes, scales and deploys rapidly. RPA also allows companies to extend their reach successfully. Since it isn’t restricted to a single physical location, RPA works via the application’s UI, grabbing and clicking information in exactly the same way as a human. RPA works with recent and legacy apps and can adjust its automated tasks almost instantly as soon as the applications which are using it change or update.

The additional speed which RPA adds to process execution gives companies an added advantage. RPA executes processes without errors and with consistency which enables the human workforce to focus their efforts on other areas, allowing the computer to concentrate on the repetitive processes. The increasing cognitive abilities of the most up-to-date RPA technology means that processes can be automated from end-to-end with no need for any human involvement at all, moving towards an advanced workplace where bots and humans can work together in cooperation and to the advantage of the business. Pre-built bots are now able to turbocharge business process automation. Some examples of this include the Skype bot which can automatically message contacts and the Twilio bot which can send text messages through the Twilio API.

What is cognitive intelligence?

Cognitive Intelligence technology utilizes the latest advances to analyze unstructured data whilst improving its performance and skills. In short, it can learn from the way in which humans behave. One example of this technology comes in the form of IQ Bot – a cognitive bot which also boasts vision skills to add structure to companies’ unstructured data and to learn by watching workers to increase the organization’s digital footprint.

Today’s businesses produce vast amounts of data, but around 80% of this is hard to access, being unextractable and undigitized when using more traditional RPA solutions. Cognitive intelligence is the next step forward. There can only ever be limited Robotic Process Automation due to variations in the format of documents and communications’ unstructured nature.

This means that human workers need to be used to extract all the relevant data to feed into an RPA process. IQ Bot can change all this, automating business processes which rely on unstructured or semi-structured data within images, electronic documents and emails. By harnessing a number of different AI techniques which intelligently extract and digitize data, IQ Bot makes RPA technology more effective and continues to learn from the corrections made by human workers, helping it to become more accurate and more intelligent over time.

Cognitive Intelligence reduces errors in data processing thanks to the automation of ERP system data entry, accelerates turnaround times and exponentially improves the customer experience.

What about machine learning?

Even people who know very little about artificial intelligence have heard of machine learning. It is one of the best known forms of AI today, distinguishing itself from other kinds of AI by its ability to improve its understanding and then take action with no need for any human intervention. Other types of AI require programmers to give it the information about what it should do in specific circumstances. However, machine learning programs are capable of making decisions themselves and to learn without any need for human instruction.

In its most basic form, you can see machine learning every time you log into your Amazon or Netflix account. You receive recommendations that are personalized to your preferences thanks to the integrated algorithms which study what you like, compare that information with what others who have similar tastes prefer and then develops an idea of what would appeal to you most.

Machine learning holds amazing potential for businesses today. By harnessing its capabilities to review and interpret data then act on that information with no need for human input, it’s possible to transform the way in which business is carried out. The human effort required will be minimized while the outcomes can become more accurate. Already, machine learning is being utilized to detect fraud within the financial services sector and to improve marketing campaigns.

Artificial intelligence – How can it help businesses?

Almost everyone has heard about AI, and it is already transforming the technology sector. While most people think AI is all about machines capable of thinking for themselves, there is more to it. Machine learning is just one element of AI. In fact, most people are already engaging with artificial intelligence on a regular basis. Siri and other voice search engines use this technology, as do chatbots and automatic image recognition tools.

Although many people tend to imagine that AI is all about fully-functioning robots or virtual assistants, this isn’t the goal for businesses today. Rather, the focus of AI within the business sector is on daily applications.

Companies can use AI to transform the way in which they function, for example by tracking market scenarios and business conditions to help in product development, marketing and sales. Within the healthcare industry, AI can track patient behavior patterns and review data from medical trials to pinpoint effective treatments and alert healthcare providers to possible issues. Patients can also benefit from wellbeing and health plans which are personalized to their unique needs simply by harnessing AI technology to gather data from sensors and wearables.

It’s clear that AI is a major need in today’s business world and demand for it will only increase as time goes on. With the volume of data worldwide set to reach as high as 163 zettabytes within the next 5 years, primarily generated by the Internet of Things, AI will be absolutely essential to cope with it.

As the boundaries of AI are pushed still further, we are starting to see the beginnings of intelligent robots, such as Sophia the Saudi Arabian learning robot, but for businesses, it isn’t too surprising that there’s a lot of confusion about the purpose of the intelligent automation continuum and how its technologies can benefit organizations.

Integrating AI, machine learning and RPA into today’s businesses

Although many organizations today are blindly focused on the race to deploy AI within their business, injecting intelligence into the processes which are relevant to their company is a more beneficial goal. Companies must grow and adapt into AI as their organization’s RPA maturity increases.

For most businesses, putting this technology to the best use is really all about making RPA slicker and more effective for their organization. Putting a bot workforce in place isn’t always easy, and making changes can end up causing a chain of ongoing problems if a comprehensive overview cannot be obtained. Machine learning is the optimal solution for limiting downtime and allowing for convenient troubleshooting in such situations. By comparing automated processes’ outcomes, spotting errors, predicting problems and managing changes processes, machine learning allows automation to stay relevant and to function at the highest possible level.

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