After the initial implementation of RPA and after insurers have addressed the ‘low-lying-fruit” for process automation, many ask “what’s next?”, and the answer is: plenty! RPA platform and service providers have been heavily focused on extending RPA capabilities by integrating it with artificial intelligence (AI), low code and developing RPA-as-a-Service (RPAaaS) capabilities in the cloud.
As many insurers who have implemented RPA already know, RPA bots excel at completing repetitive and simple tasks. Now with the addition of AI, the universe of opportunity for RPA applications expands exponentially. AI will reshape the future of the insurance industry and advancements in RPA using AI will mean the tools can identify and improve processes with limited-to-no human intervention. Leveraging AI will enable far more flexible processes and decision making based on better understanding and continued integration with new data sources. The integration with AI will extend the value of the RPA investments made by insurers over the last several years. AI enabled bots utilizing machine learning (ML), natural language processing (NLP) and optical character recognition (OCR) can now address a much more complex tasks in a process. Intelligent bots can read and analyze text and images from an endless variety of data sources.
NLP has made significant strides in programming machines that can understand and have a general understanding of human language, think Siri. But the next step is to not only understand what you say but also what you mean. A lot of future focus will be on natural language semantics. Continued investment in handwriting analysis will lead to incremental improvements in the accuracy of reading characters in documents of all types. This will also lead to directly improving the conversion of unstructured data to structured data enabling insurers to identify new trends, emerging risks, future forecasting and develop new products in response. The evolution of open-source OCR platforms like Google’s Tesseract 4 will continue to advance OCR LSTM based engines. They focus online recognition as well as character patterns. ML and deep learning algorithms will self-improve over time without programming, providing even more accurate and complex insights. ML will continue to decrease costs and increase its impact on areas such as lead generation, claims and fraud.
AI will have a profound impact in intelligent process automation over the next decade. It is forecasted that the global growth in investment in AI will jump from an estimated $65-85 billion in 2022 to well north of $900 billion by 2030. The landscape for RPA is changing and based on our previously published insurer views on RPA, we expect it will continue to gain a strong utilization from across the insurance industry for at least the next few years. From a global industry perspective, the adoption of RPA also continues to accelerate, and that would indicate vendors will continue to invest heavily in the ongoing integration of cognitive technologies.
To learn more about the future of RPA please follow this link to my latest report - Extending The Value Chain of RPA Through AI, Cloud and API's