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How AutoML Can Change the Lives of Your Knowledge Workers

Document processing has come a long way in a short time. It was less than 40 years ago when software developers started looking at how to blend traditional paper documents with digital platforms. Today, the goals are the same — but the challenges are different. 

Never have companies been faced with the proliferation of data (and documents) that they are today. Because of the sheer volume, many companies have yet to adjust document processing processes to keep up. Every company has outdated ways of processing documents – whether it be invoices, insurance claims, medical forms, or mortgage documents – that are begging to be simplified. These processes are terrible for your business: your workers struggle with the monotony of the tasks and paying them to manage tactical processes is taking away from more important work and, in many instances, their professional growth. 

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Automated Machine Learning (AutoML) is a nascent artificial intelligence (AI) technology that exposes the power of machine learning (ML) to a much broader audience than data scientists and technologists. Instead of preparing for every possible scenario like pre-trained AI does, AutoML learns based on your documents. In doing so, you get all the benefits of an AI-driven approach over any set of documents you want to work with. When executed well, AutoML provides a  user experience that is perfect in its simplicity. You don’t need a computer engineering or data science degree — AutoML platforms can be operated by business users; in fact, it puts an emphasis on subject matter experts who have an innate understanding of the process being automated and are capable of teaching the system. 

An AutoML-based approach provides the benefits of Optical Character Recognition (OCR), ICR (Intelligent Character Recognition), and ML, learning the nuances of your documents continuously. And unlike pure Robotic Processing Automation (RPA), AutoML can go “off script” and learn on the fly with your users. AutoML can be used on its own or in tandem with an RPA solution to fully automate complex processes.

Here are some ways AutoML can help you re-imagine your business processes: 

Increased Speed.

If workers don’t need to spend all their time entering data that requires painstaking accuracy, it serves to reason that they can move quicker through the document processing phase and spend their time on more deliberate activities that help move the business forward. We’ve all faced the monotony of filling out health or mortgage forms — now imagine the primary focus of your job being entering all that data into a system (or systems) that need to access that data. It’s exhausting just imagining it! 

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Better Utilize Your Existing Human Capital.  

Many think advanced automation technologies are people replacements, but that overstated narrative applies to very tactical activities and roles. It’s more accurate to think that AutoML frees up your workers to spend their time on more strategic initiatives. There’s also a big role for them in human-in-the-loop processes, where their domain expertise is invaluable in making AutoML work for your business. 

Free to Get Back to Your Real Work.

By counting on technology to handle the processes, you free your knowledge workers to focus on what you pay them to do. We must arm them with the ability to find the most important information as quickly as possible. On the podcast, one of the speakers spoke about millennials and research that has shown that they equate the quality of information with how hard it is to find. The harder it is to find, the less significant it can be. I’m sure we can all relate to that when we’re on page 17 of a Google Search, slogging through with our eyes glazed over. 

Get Answers More Quickly.

Your knowledge workers are teed up to deliver information to the business but can’t do that if they are focused on manual data entry or forced to use other antiquated technology to process complex documents like PDFs, videos, and other structured and unstructured data formats.

Through AutoML, we can empower them by enabling them to train intelligent systems to work for them. Take an application we all know like Excel. It takes very complex ideas and boils them down so anyone inside the business can do amazing things with it. For AI to see the growth that’s anticipated, we need to take what’s perceived as a nebulous and expensive technology and simplify it so that information workers can apply it to the unique problems they face every day. 

AI projects can be cumbersome and often fail for a number of reasons: too impractical, no clear outcomes, no human in the loop. But AutoML promises a new future for enterprises that embrace it and put it in the hands of the people who can make it work: knowledge workers. 

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