Firms who take the time to understand and implement AI and machine learning will reap the rewards
Elly Yates-Roberts |
This article was originally published in the Summer 2019 issue of The Record. Subscribe for FREE here to get the next issue delivered directly to your inbox.
Technology buzzwords are everywhere – from scholarly articles to Twitter. As technology continues to advance, we see more umbrella terms that encompass various definitions. Think words like digital transformation, machine learning, artificial intelligence (AI), robotic process automation (RPA) and business process automation.
Two of the biggest buzzwords are AI and machine learning, but people are still unsure about what makes these two technologies different, let alone how they work together or relate to RPA.
AI performs tasks using human intelligence and cognition. It can recognise patterns and understand natural language, allowing it to learn and to solve problems. One of the biggest differentiators of AI is that it can learn without being programmed, which sets it apart from some forms of automation that are coded to perform specific repetitive tasks in the same way every time. Occasionally, AI uses machine learning to kick-start its decision-making abilities.
Machine learning is both a form of AI, and a way of achieving AI. Rather than being hardcoded with specific directions, machine learning technology uses an algorithm to train itself how to perform tasks. It continuously learns from the data it receives, which means it can change the way it handles processes. The technology also uses statistical analysis to make better-informed decisions.
Where does RPA fit in? Machine learning and AI engage in ‘thinking,’ while RPA does the ‘doing.’ In other words, AI and machine learning can make changes to a process in a similar way to a human, whereas RPA follows the process that was put into place during the implementation stage and doesn’t deviate from that task – unless AI or machine learning technology is integrated into the solution. In this case, the RPA solution will learn certain procedures, engage in trial-and-error, adjust based on the results, and make cognitive decisions and predictions like a human would. Often, RPA solutions incorporate applications used by AI, like optical character recognition, to pull information and make decisions. When this happens, RPA is no longer solely responsible for handling tedious, repetitive tasks, but instead makes intelligent decisions based on predetermined business rules.
By mimicking human behaviour, RPA with AI and machine learning empowers organisations to improve processes as they take in information. When companies understand the buzzwords and how to implement these technologies together, they can streamline systems, make operations more efficient and improve decision making to gain a competitive edge.
Alyssa Putzer is the marketing communications specialist for Metafile Information Systems