Around a decade ago, paperless offices were all anyone could talk about, but have you noticed how those conversations have quietened in the last year or two? To some extent, of course, the relevance of this topic has faded as more businesses have already digitised. But it’s naive to assume that there aren’t still paper documents flying around in the vast majority of offices. Could it be, then, that we’ve simply grown complacent? After all, AI data handling capabilities have made many companies feel like they’re invincible. Interestingly, though, continued efforts towards efficient paper document scanning might actually put your AI in better stead. We consider the 3 reasons why document scanning might actually be the unexpected first step to AI success company-wide.
By Team Savant
Image: Zach M
1. Bringing Data into a Digital Realm
It’s easy to assume that modern offices simply don’t need paper scanning, but roughly 80% of enterprise data is still unstructured, and a lot of that is ‘trapped knowledge’ that remains limited to paper files and resources. What’s more, this information tends to be company-specific, meaning that there’s no other way to access it than via those direct files.
This is why the use of technologies like A3 scanners continues to matter – this is the only way to make sure to understand the depths of your company’s inner workings. Without this process, your AI efforts will stay stuck on potentially irrelevant public information. By bringing your data into a digital realm through this simple process, you can ensure far more informed and thus more efficient AI switchovers in general.
2. Extracting Document Essentials With Ease
AI works best when it understands things like your company’s bottom line, key data sources, and priority information. But remember that AI is only as effective as its training. If you’re training your new AI systems on limited stores of digital data, then it will inevitably be less effective at the levels of analysis you would like. Expand those data sets with physical scanning processes, and you should soon have an AI powerhouse on your hands.
This is especially true if you implement dedicated AI-powered scanning methods, which will automatically enhance their knowledge stores by scanning those documents using technologies like machine learning and optical character recognition in the first place. Both of which ensure faster, more knowledgeable AI extractions and categorisations at all times.
3. A Stronger AI Foundation
We all know that AI solutions are prone to a fair few technical issues. AI hallucinations, or outright false information, have gained particularly unwanted attention of late, and you know why they happen? Because those systems utilise outdated information. If your AI systems are trained on a paper trail that you digitised ten years ago, then you could end up with a completely irrelevant understanding of everything from performance to client communications. Updating your data is, therefore, key to building the strongest foundations possible for AI systems that never let you down, even when they’re interacting with clients directly.