In the past several decades alone, innovations in machine learning and artificial intelligence have drastically altered the world as we know it. Advances in the way that computers “think” have powered everything from self-driving cars to personal assistants like Siri and Alexa.
Beyond these consumer applications, machine learning and AI are also crucial elements of “digital transformation”: using digital technology to make your business processes more efficient and deliver better value to your customers.
Machine learning and AI are integral to robotic process automation (RPA): the use of “robotic” software agents to automate many lower-level business processes. RPA agents seek to imitate the actions of human employees while interacting with a computer system: typing emails, surfing the web and operating different applications.
Not only does RPA make your business processes more predictable, it also cuts down on the problems created by human error, and can massively speed up your workflow from start to finish.
Of course, if RPA agents are meant to fully replace your human employees, it’s not enough for them just to follow a few prescribed set of rules. RPA software also needs to be reactive, responding intelligently to unknown and unforeseen situations.
For example, customer service is one of the greatest opportunities for RPA. By identifying users’ issues and assessing whether they need to speak to a human representative, RPA agents can save you money and cut down on help desk wait times resulting in a greater customer experience.
AI and natural language processing technology can parse customers’ responses to determine what their problem is and how they are currently feeling. Meanwhile, machine learning can help RPA agents better classify support tickets and send them to the appropriate help desk. By giving it thousands or millions of previous tickets and the categories they belong to, the agent can “learn” the features that are most relevant for classifying the ticket.
While RPA can be a game changer for many businesses, it becomes exponentially more powerful when you combine it with machine learning and AI technologies. With the right experience and expertise, companies can build intelligent automation solutions leading to higher returns on investment and happier customers.