I think RPA, or other process understanding or improvement methods should always be considered when you are planning AI. We at least sketched a flow of what we were working on, and there is so much more you can do today. You need to understand what you are doing, considering, risking. Some good thoughts here.
RPA In The Real World: Driving Marketing, Analytics, Productivity and Security
As we continue to move forward in digital transformation, an increasing number of companies are discovering the promise of robotic process automation (RPA). In a nutshell, RPA allows companies to gain efficiencies and (hopefully) save money by automating routine tasks. RPA is what I’d call the low-hanging fruit of artificial intelligence. It’s governed by structured input. Its processes are mundane and rule-based. It doesn’t require the deep, complex system or infrastructure integration that other more substantial AI requires. Best yet, it frees up your employees to work on higher-value projects, rather than repetitive day-to-day tasks. And for that reason, it’s become a hot commodity. Forrester says RPA will be a $1.5 billion business by 2020. This spending is a boon for vendors like UiPath, Automation Anywhere and Blue Prism that are at the forefront of this product offering.
But rather than more "philosophical" use cases for RPA, let's look at how businesses are using RPA in the real-world right now—and how your organization may benefit as well. .... "
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