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Automated Records Management: Can We Handle AI ERM?

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Organizations aren’t always prepared for the particular technological developments of automated records management.

During the relatively brief time it’s been around, electronic records management (ERM) has evolved drastically and will continue to do so in the future. But with advancements often come difficulties. Some of these difficulties arise when organizations aren’t quite prepared for the particular technological developments of automated records management. Using artificial intelligence (AI) in records management, for example, has thrown some organizations for a loop.

With AI developing at a rapid pace, discussion is crucial between policy and technology leaders regarding the legal, ethical and logistical issues of transferring everyday tasks from humans to machines. The focus needs to be on how to handle current and future risks associated with AI.

Despite its advancements, AI can still produce inaccurate results — even when the coding is considered trustworthy. Does this undermine the dependability of AI when it comes to handling records, including financial, health and personal information? For some, perhaps.

That’s not to say that AI can’t be a useful tool in modern-day automated records management. But first, AI needs to be able to regulate itself. This requires the development of testing and experimental procedures regarding the creation of AI algorithms, enhanced cybersecurity systems and input authorization criteria. These solutions would need to be customized to fit each organization and industry by AI professionals with comprehensive knowledge of the technology, regulatory setting and particular industry or application of each product. Additionally, it would be just as crucial for regulatory applications to be designed so as to not hinder development and innovation.

Another issue with AI ERM is scalability. Some organizations handle thousands of records simultaneously. Others handle many more — possibly millions or billions. If such an organization were to attempt to leverage AI records management without a sound strategy, it could fall behind while processing the records and potentially need years to catch up. That is why the need to scale rapidly is crucial.

AI provides a wide range of solutions that can broaden the capabilities of records management software. It does have its risks, but they can be managed under the right leadership. After all, AI is meant to work with humans, not against them.

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