The Future of AI in Robotic Process Automation

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    Within the Robotic Process Automation industry, we imagine RPA as a set of tools that work together to help automate tasks within an office setting. As new tools are added, or as existing tools are improved, the full solution is enhanced.

    The latest toolset upgrade that has been buzzing around the RPA world is related to Artificial Intelligence (AI) and Machine Learning (ML). With an AI that can find patterns and learn new behaviors, we suddenly have a whole new array of possibilities in our RPA functionality.

    What is RPA, AI, and ML?

    Before talking about the future of AI in RPA, we’ve got to understand what the terms mean.

    Robotic Process Automation – As technology advances in the workplace, RPA refers to intelligent programs and systems performing the tasks and labor of office workers. Some tasks that can be automated include receiving and filing documents, performing data entry, syncing data between systems, and sending alerts and notifications.

    artificial intelligence

    Artificial Intelligence – This term refers to intelligence that is exhibited by a machine, allowing it to understand elements within its environment and perform certain tasks.

    Machine Learning – Taking technology a step beyond AI, ML refers to the algorithms used by machines that allow them to learn and improve their performance. This can involve growth of their knowledge base, which in turn helps improve the accuracy of their pattern matching.

    How does it all work together?

    As explained in “Artificial Intelligence, Machine Learning and Robotic Process Automation – Preparing your Career for the Rise of the Machines,” when these three ideas combine, we are able to teach our software to perform routine business tasks, while also allowing that software to capture new information and learn through experience.

    Within the DocuPhase Enterprise Automation Platform, this is applied to functions like our automated GL Coding bot. This bit of our software codes accounting transactions within the General Ledger, and it’s actually able to learn new codes and recognize patterns, improving its functionality over time.

    Early adopters

    IT firms themselves have been among the first to adopt the new technology, using it internally. In fact, in 2016-17, Infosys and Wipro both reported that automation tools gained them 12,000 full-time-equivalent hours of work. These results can translate outside of the IT world. For example, since deploying the DocuPhase Enterprise Automation Platform, Alimera Sciences has reduced their invoice processing time by 93%. Likewise, RPA tools have brought Lockheed Martin a 96% increase in overall productivity.

    Do these tools have a future?

    By nature, technology isn’t stagnant. It is ever-changing. It’s not often that breakthroughs have any real staying power. Generally, they are replaced fairly quickly by the next thing and then the next thing after that. So what sets RPA, AI, and ML apart from other technologies that come and go?

    We believe that the very nature of these technologies is what gives them staying power. If the nature of AI is to learn and improve, it will be able to adapt and meet your organization’s needs, now and in the future. As explains, AI will be able to accelerate its own adoption, even as it is working to build a better version of itself.

    Want to see how RPA can be adapted to your workplace? Request a demo today!


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