Even after the machine-based computers came online, humans were still very much part of the equation, utilizing their skills to define the right theories and strategies. Depending on your business, there are two types of automation/AI that a finance organization can start employing: machine learning and RPA (Robotic Process Automation). First, let's get one thing straight--robots are not stealing our jobs. When NASA's Apollo program hired human computers to help decipher the math for the moon landing--so compellingly presented in the film "Hidden Figures"--today's machines were not readily available. In fact, the math for the computational questions they needed to answer hadn't even been invented.

The "virtuous circle" comprising RPA, machine learning and analytics was the central theme of this month's BotVisions webinar series. Joining me were Kelly Coupe, Principal Product Manager, and Abhijit Kakhandiki, VP of Products, to share their insights into how business users are integrating the execution capabilities of RPA with the cognitive capabilities of machine learning to take the business benefits of automation to the next level. While extremely good at executing specifically defined tasks, RPA tools are limited in the sense that they cannot adjust to new conditions or learn from experience. Machine learning, meanwhile, applies Artificial Intelligence (AI) capabilities to lend business context to the tasks executed by RPA systems, enabling the latter to make better decisions and be more productive. For example, RPA systems can effectively perform many tasks associated with loan origination or account management.