In any modern factory, robots are everywhere. They are assembling cars, sewing jeans, wrapping candy. Now, with advances in artificial intelligence (AI) and machine learning, bots are showing up to work in offices. Billy Bot, for example, can help people with administrative tasks in law firms. The “robot junior clerk” works for Clerksroom, a provider of advocacy, advice and mediation services throughout England and Wales. But are these bots productive? And can they be trusted to run critical processes such as paying your bills?
Bots can automate everything from moving files to making calculations. They are easily taught, task-agnostic and don’t care what work is assigned. They are dream employees, so to speak. Bots can cost 60 to 80 percent less than a full-time employee and nearly 70 percent less than a full-time offshore worker. Bots can also cut processing times by 60 percent or more, streamlining business processes and improving customer satisfaction.
It’s important to point out that the value of automation through bots is not just about cutting labor costs. It’s also about speed, quality and agility. And when partnered with AI, the bots assimilate more complex processes requiring judgment. That cognitive computing elevates robotic process automation (RPA) to intelligent process automation (IPA) and provides even greater opportunities for innovation.
DXC Technology’s white paper, “Enlightened Automation: Time to Leap,” suggests that today’s market makers can now reimagine what industrialized robotic platforms will do to the business, from line departments to the bottom line. Think of it as what the industrial revolution did to the manufacturing line: streamlined processes using new technology.
Of course, putting bots to work is not without risk. For starters, the implementation has to be well planned and executed; otherwise, enterprises aren’t likely to realize benefits to their operations. But there are also larger issues to consider. Security and privacy are paramount and need to be considered early on during the evaluation and implementation of bots and IPA. Ongoing management and governance are also key. For example, bots are bits of software that will need regular updates and software patches; consistency will be vital to ensure that those updates and patches are done as needed — to avoid gaps that might lead to malfunctions or even worse, breaches.
Enterprises also need to revisit privacy policies whenever bots are used to collect and work with customer or partner information. Privacy policies should be a central part of any company’s data strategy, of course, and they will need to be updated to factor in the use of AI, machine learning, bots and IPA.
A great example is the use of AI in chatbots that automatically communicate with customers. Suppose the customer calls in to check on the status of an invoice, and the chatbot uses AI to query the customer about purchasing additional products or services based on previous orders. That upsell might be a value-add for the company, but the customer may not appreciate it. The general rule, when it comes to privacy, is to put users in control of the data, and they should be made aware of how it’s used and shared. Opt-in should be the norm.
Learn more about innovating your traditional labor model in the DXC paper, “Enlightened Automation: Time to Leap.”