Last year, Gartner estimated that by 2030, Robotic Process Automation (RPA) will create $20 billion in value. That is nearly 10 times what it generates today.
But in that future, what would process mining and RPA look like? Let’s find out.
The next breakthroughs in RPA services
The objective of RPA, ultimately, is to emulate human actions.
Today, the range is impressive but far from complete. And that is what is expected from RPA in the future — the expansion of its range.
1. More high-value automation
Sure, RPA eliminates paperwork, but can it go a step further and collect information via voice recognition?
Sure, RPA can automate scheduling, but can it go a step further and automate email replies as well?
Of course, job portal RPAs can extract information from a résumé, but can they go a step further and identify the ideal candidate as well?
And can we have chatbots that are more natural, more human?
With great leaps in processing speeds and data analytics tools, technologies like audio-visual signal processing, machine learning modeling, forecasting, will transform, becoming more advanced and capable than ever.
When these technologies become more advanced, so does RPA. And therefore, its capabilities expand, enabling it to emulate a larger range of human actions.
In other words, in the future, RPA will continue to automate, but it will automate a wider, more complex range of tasks. It will still be far from reaching its true potential, but it will be closer than ever.
2. The democratization of automation
Gartner also estimates that by 2030, RPA will be adopted by 90% of the world’s largest businesses. The challenge, however, is to be adopted by 90% of all businesses.
Yes, RPA will make businesses more productive, better at risk management, more cost-effective, and scalable, among other things, but its distribution is uneven, and so will be the resulting competitive advantage.
Early adopters of RPA, by capital or knowledge, already have an edge, which allows them to invest in more expensive and more high-value-high-return advancements in the technology, making them even stronger.
Hopefully, in the future, RPA too will trace the trajectory of all semiconductor technologies — first, expensive and exclusive, then, gradually, cheap and universal.
Yes, the biggest businesses will have access to cutting-edge business intelligence tools, but, like computers, most businesses will get their hands on tools that should, at least, get the job done.
In other words, a virtual assistant, not for a select, privileged few, but everyone.
RPA consulting? Make sure you do this first
RPA solutions can have a profound positive impact on the people who rely on them.
Hospitals, for example, will automate registration, insurance claims, and billing so that health professionals can do what they do best: taking care of their patients. In banking and finance, data collection, management, and visualization will unfold on their own, liberating the workforce from manual, repetitive work.
But RPA can also have a profound, negative impact on people if they don’t know how to use it.
Without data governance, RPA will not make much difference to business productivity, efficiency, or cost-effectiveness.
What is data governance?
Data governance is a set of practices that ensure that the data managed by a business is of the highest quality.
Therefore, the most successful businesses invest in data governance solutions before they invest in business intelligence. Because RPA brings the execution, the solution, while governance brings the guidance, the plan.
