In an industry growing and changing as fast as business process automation, how do you know what technology developments are important, and how can you tell how those developments will impact your business? We tackle this topic periodically in our State of Intelligent Automation webinar series. In our Fall 2018 edition, WorkFusion Chief Evangelist Adam Devine made clear what the single most important capability is in process automation right now: software robots that learn from and adapt to real-time data.
You can freely watch that webinar on-demand to hear about learning bots, the importance of a single platform, predictive analytics and what capabilities it takes to achieve digital operations.
What follows is both Adam’s recap of the key points within the webinar and his answers to the most popular questions asked by our live audience.
- Cutting through RPA froth
Are we in an RPA bubble? Maybe. The recent Wall Street Journal articlesuggests we are. Forrester analyst Craig Le Clair doesn’t believe the valuations of the top three “RPA 1.0” companies are justified, and Hacket Group VP of Research Erik Dorr observes in the article that there’s “no real software magic” behind RPA 1.0 products.
What does this mean?
It means that the first generation of RPA product use rules-based software to automate predictable functions that involve structured, static data through application user interfaces. Given that, according to Gartner, 80% of data within a typical enterprise is unstructured, this limits the application of RPA 1.0 within typical customer environments. McKinsey further reports that one third of automation use cases change monthly, and one quarter change daily. RPA software that lacks the ability to dynamically learn from and adapt to changing processes and inputs will require constant training, and any reduction in manual work will be lost in people retraining bots.
First generation RPA vendors overpromised and over-marketed their products with the “scent of AI.” UI Path CEO Daniel Dines went so far in the WSJ article to say that, “AI makes it sexier for companies to think about automation.” It’s time for the market to understand what’s real and what’s froth.
2. The mandate for AI-driven automation
AI-driven automation delivers what RPA 1.0 companies have promised. As Craig Le Clair explains in the WSJ article, “higher-order artificial intelligence software can learn when presented with new data and make decisions without human input, such as monitoring credit card charges for fraud, or determining whether to underwrite an insurance policy.” Software robots that learn through AI are able to adapt to the frequent change in both processes and inputs, maintain optimal levels of automation, and deliver sustainable reductions in manual effort for customers.
One of the most important concepts in the webinar is the evolution from “Software 1.0” to “Software 2.0.”
Software 1.0, which has been the programming paradigm since computers were invented, requires programmers to decompose a problem into steps, write rules for each step of the problem, compose each rule into a system and then measure performance. When performance suffers as a result of change, programmers edit the code. This is precisely how RPA works: people train bots, data and rules change, people retrain bots. Rinse and repeat.
AI-driven automation flips the paradigm by using dynamic data within a process to automatically train machine learning (ML) algorithms, which people validate through simple user interfaces. Once the ML achieves an optimal level of completeness and accuracy, people are engaged only to handle exceptions, which make the learning bots incrementally smarter. This constant learning means that customers achieve higher levels of automation over time without the need for data scientists or programmers. It means that AI becomes a truly self-service capability for business people.