Have We Hit the Ceiling of Automation?

As the likes of Google, Microsoft, and Meta continue to battle it out for the top spot in AI development, it seems like the right time to take a look back at the roots of AI in business. Specifically – task and process automation. 

Task and process automation is arguably a cornerstone of staying competitive in the long term for any modern enterprise. It improves productivity to perform repetitive tasks, freeing people to work on those that are high value. 

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Traditional robotic process automation (RPA) is one of the early forms of automation. It’s a type of automation where a user can program instructions to enable a bot to perform a task in place of a human. 

While RPA still plays a part in businesses today, recent developments in AI are, understandably, causing businesses to assess their current processes to see where the gaps are.

But where does traditional RPA stand in this assessment? Have we hit the ceiling of robotic process automation?   

Strengths of Traditional RPA

Despite huge leaps being made with digital transformation, many organizations continue to operate with siloed IT systems. Time-consuming repetitive processes still have to be inputted manually, which results in significant time delays and major operational overheads. 

This is where traditional RPA can shine. RPA gives organizations the ability to automate repetitive tasks that are necessary but time-consuming. The obvious benefit here is increased efficiency as by automating these more menial tasks, processes can be completed quickly and accurately. 

And, by siphoning off these manual time-consuming tasks, employees are freed to work on other areas of the business. Not only does this allow them to work on higher-value tasks it is also likely to increase employee satisfaction – as their work can be more engaging and challenging. 

Another benefit of RPA is eliminating human error when it comes to manual, repetitive tasks. Humans can make mistakes when they’re tired or busy, it’s just human nature. Automation, however, isn’t affected by these extenuating circumstances – they are consistent. By investing in traditional RPA, accuracy, and reliability levels immediately increase, and there is less chance of mistakes. 

Overall, there are a lot of strengths of traditional RPA, especially for businesses looking to automate just a handful of time-consuming tasks. Despite these strengths, however, some organizations are looking to move away from the technology.

Traditional RPA Has Hit a Ceiling?

Recently, the conversation around task automation has shifted from the roots of RPA towards intelligent automation, and one thing is clear — traditional RPA has hit a ceiling. 

Traditional RPA has at its core, always been about automating individual tasks. While this is important and definitely has its benefits, it is also limited. 

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One of these limitations is that eventually, RPA can result in diminishing returns. Because traditional RPA is designed for automating individual tasks, businesses have to build and deploy another RPA bot for each task they want to automate. 

Not only is this time-consuming in itself, but it’s difficult to maintain a large portfolio of bots that are constantly aging. Over time, the cost of maintaining all of the individual bots actually offsets the savings from automation in the first place. 

Why is this a problem?

As AI is progressing even further, automation is no longer about simply automating a few tasks to save costs and time, now it is about driving tangible business results. 

The Shift Toward Intelligent Automation

This shift that we’re beginning to see in terms of automation isn’t the end of RPA, but more of an evolution into intelligent automation. 

In layman’s terms, rather than automating individual tasks as seen with RPA, intelligent automation combines multiple technologies and as such, is simple to develop and maintain.

By combining business process management, robotic process, low code, AI, and machine learning (ML), intelligent automation is able to create natural language processing, optical character recognition (OCR), conversational AI, and more. 

A key aspect of intelligent automation that pushes it beyond RPA is the fact that it operates on low code. Low code allows the application to be developed in one-tenth of the time in comparison to more traditional development methods. This also means that businesses are also able to layer on AI with intelligent automation — making it more viable for future development than traditional RPA. 

What Does This Mean for Future Business Processes?

While it’s clear there are huge benefits to be gained from this technology, there’s still work to be done for those businesses looking to make the most of intelligent automation. 

It’s necessary to address complicated, siloed IT systems and data sources as automation can only do so much, especially if all of your data is stored in different places. 

To fully make an impact with intelligent automation, businesses need to adopt a digital engineering mindset – namely moving away from a configuration mindset, where needs are adapted to match the available solutions, and moving to an engineering mindset where you combine technologies to create the solution you need to meet your needs specifically.

Investing in a long-term roadmap is also key to successfully implementing RPA and intelligent automation technology into operations.

If you don’t know where you’re going, how can you be sure your technology is fit for the journey?

So, have we really hit the ceiling of automation?

The short answer is no.

While we are recognizing the limits of more traditional RPA, the way has already been paved for intelligent automation to take its place. It’s going to be exciting to see how businesses take this to the next level.