Let’s accept the fact that everyone is fascinated with the word AI or Artificial Intelligence today. Some way or the other we want to make it a part of our digital transformation journey.
Being one of the leading RPA Implementers, we always get this question from our new partners about identifying and using some form of AI/ML for process automation. Although this sounds very cool for presenting to senior leadership in your organization, finding such processes in the initial phases of RPA is difficult and automating those are more complex.
One needs to understand that AI is no magic which you set-up once and it will run forever on its own. Artificial Intelligence is a concept and one need to build a platform using combination of tools like Google Vision, IBM Watson, open source libraries like Tesseract, etc. in order to fulfill one’s needs. Also, it doesn’t just stop here. Such tools require continuous training to improve their intelligence. All this takes time and even a bit of impatience leads to a catastrophic failure. And this finally leads to a stage where organizations claim that RPA is not for them.
Give RPA a time to stabilize in your organization. Begin with processes that are simple but resource intensive. Processes with fixed set of steps and which deals with structured data. Success rate of such processes is higher and thus automating processes like these will help establish trust in RPA and win confidence of people. This will also give you enough time to understand the type of processes are executed in various verticals/departments and create a pattern out of it.
Once the initial hurdle is over and you have more data about the processes, you can think of moving to the next stage which is automating the processes involving unstructured data. This is where AI and ML will come into play. Some initial candidates involving AI and ML are invoice processing, check scanning, PO processing, etc. You can either use out of the box solutions available in the market or write your own platform to suite your custom needs.
To sum up, don’t rush into adding AI to your RPA kitty however tempting it may sound. Create a strong foundation first so that these cutting-edge technologies can stand firmly on it.
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