When viewed as a foundational automation technology, there is no doubt RPA can deliver significant short term benefits. However, RPA on its own is not disruptive and not the panacea for all operational challenges. It will be the combinatorial effect of other AI technologies that will pave the way to true operational transformation.

RPA is not a disruptive technology – Artificial intelligence (AI) is the future of automation.

While RPA can deliver significant benefits, we believe that Artificial Intelligence will be the truly disruptive technology of the future. RPA is a foundational technology that companies should consider as a first step in their AI journey.

AI can be transformative when it is part of a combination of a wider suite of technologies working together to allow companies to reap the biggest return from automation. According to Accenture Research “The combinatorial effect of AI, cloud, sophisticated analytics and other technologies is already starting to change how work is done by humans and computers, and how organizations interact with consumers in startling ways.” Our research demonstrates that, as AI matures, it can foster economic growth and enhance productivity.

An example of just how transformative Artificial Intelligence is becoming can be seen in a Proof of Concept Google DeepMind is conducting at the National Health Service (NHS). DeepMind has started to use machine learning — a type of AI — in the early detection of common eye conditions such as age related macular degeneration through teaching the technology how to read complex scans. According to Dr. Dolores Conroy, Director of Research at Fight for Sight (Google DeepMind: https://deepmind.com/applied/), “the potential of machine learning to analyze the thousands of retinal scans taken each week in the NHS allow eye health professionals to make faster, more accurate diagnoses and more timely treatments thus preventing sight loss.”

While RPA can deliver significant benefits, we believe it will be the combinatorial effect of AI, cloud, sophisticated analytics and other technologies that will be the truly disruptive technology of the future.

In asset management, natural language generation (advanced NLG, another type of AI), has started to create enterprise reporting that goes beyond the basic reporting produced by RPA. It has started to create reports that are complex, perfectly written, meaningful and have narratives intended for any audience (Source: Narrative Science)

In support functions, such as procurement, cognitive systems will support procurement professionals to increase compliance and quality, leading to an estimated 98% contract/policy compliance by 2020. The use of advanced analytics together with the industrial internet of things leading to meaningful insights for 100% of the spend.[1] 

A company seeking to realize the full potential of AI and reap its disruptive benefits can start by:

  • Getting the basics right. Making AI work in a business context requires domain knowledge, sufficient data and an understanding of the task and scale at hand. It may also require an overhaul or redesign of broken or old processes. RPA can help lay the groundwork for AI by providing automated digital execution of processes, which can then be extended with AI.
  • Preparing the next generation. By starting to integrate human intelligence with machine intelligence using RPA we demonstrate how man and machine can co-exist and complement one another. A new mind-set, shifting the focus from ‘competition for jobs’ to closer collaboration to enhance uniquely human skills, will be needed for this transition.
  • Embracing open innovation. An artificial intelligence solution must be technology rich. It should be a constellation of technologies that, when integrated, can create a highly adaptable, nimble business capability.    

RPA on its own is not disruptive and is certainly not the panacea to all operational challenges. Rather, RPA should be viewed as an additional lever in a whole suite of tools that can be used to mitigate the resourcing and cost pressure challenges facing many organizations today. It is an enabler that will allow a company to optimize and automate processes, reduce costs and human errors and act as a foundation to pave the way to the future of artificial intelligence. 

[1] Source: Accenture Operations Trends 2016

 

 

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