The evolution of automation was accelerated with the introduction of ML and natural language processing (NLP) in the 1960s, which enabled computers to understand human language. Therefore, characteristics of both ML and NLP can be seen within the RPA technology today. Although RPA emerged in the 90s, significant developments to this technology were done in the early 2000s. However, RPA remained unknown until around 2015, where it started to become the hot topic in digital transformation. The potential savings from RPA for companies by 2025 is estimated at USD 5 to 7 trillion. So, it’s evident that RPA is in it for the long haul and will continue to improve its capabilities with the advancement of related technologies.

We know of many global companies that have eventually died because their business models didn’t adapt to changing environments and evolving technology – Kodak, Nokia, Yahoo, Motorola, Sony, and National Geographic are a few examples. Who would have thought small startups would supersede these corporate giants. This is not to say that all companies should adopt RPA for survival, but they should keep a close eye on emerging technologies in order to adapt faster. If an organization has traditional, time-consuming operational processes, it is unlikely that it will create customer-centric products with cutting-edge technology. Most likely, the same characteristics within the organization will be reflected across their customers as well. Therefore, streamlining processes is a stepping stone for providing better customer service and products.

We are living in an era of digital and social revolution where people are expected to fulfil more than just the survival requirements and basic standard at a job – but they seek quality of job and opportunities to learn. This is a driving factor in encouraging companies to adopt new technologies such as RPA; organizations need to keep their most valuable resource satisfied; their employees.