Information Is Still the Cornerstone

Why Information Still Matters More Than the Technology

I've been in this industry since 1978, and I've watched the terminology change more times than I can count. Document management became content management. Content management became information governance. Now everybody's talking about AI. But underneath all of it, there's one word that hasn't moved: information.

Whether you like it or not, this world runs on it. Business decisions get better when you have more information. Medical decisions get better when the doctor has more information. It doesn't matter what industry you're in or what you call the technology, information sits at the core of it.

Does the Old Data vs. Content Distinction Still Matter?

That's actually the answer to a question I get a lot these days, which is whether the old distinction between "our kind of data" (the messy, unstructured stuff our members deal with) and the clean, structured data a data analyst works with still matters. My answer is no, and I don't think it should. Data is data. Information is information. The real question is whether it's in a format today's technology can actually use.

Why Scanning and Capture Are the Fuel Behind AI

Think about scanning for a minute. I know, it doesn't sound exciting. But scanning today is the input for AI systems. AI can't do anything with information that's sitting in a filing cabinet or buried in a format a machine can't read. If you get that capture step wrong, if the information going in is incomplete or poorly structured, it's going to mess up everything downstream. That's not a small technical detail. That's the whole ballgame.

So when I hear people say the old skills, capture, scanning, records management, don't matter anymore because AI is here, I'd push back on that. Those skills matter more than ever, because they're what feeds the machine. Democratizing information, gathering it all together in a usable way, that's exactly how AI and whatever comes after AI is going to work. The more information you have in a form that can actually be used, the better.

Is AI Dangerous? A Different Way to Think About the Risk

Now, I understand the skepticism out there about AI. All it takes is one glitch and people say, see, I told you this was dangerous. I get it. But I like to put it this way: if you have a medical issue, your doctor gives you an opinion, and it might be right or it might be wrong. But what if you could get the combined opinion of a million doctors, with millions of years of experience between them, pointing you toward the best outcome? When you frame it that way, people usually come around, even if they're still a little nervous. And honestly, a little hesitancy isn't a bad thing. There's something healthy about acknowledging the opportunity in AI while keeping your eyes open to the risk. Our industry, and frankly our government, could use more of that kind of clear-eyed thinking around the rules of the road for this technology.

The Role AIIM Can Play in Responsible AI

I think there's a role here for AIIM and organizations like it: helping companies show what they're actually doing to keep information secure and used responsibly, so the conversation isn't just fear on one side and hype on the other.

Fifty years in, and I still believe the same thing I believed when I started: get the information right, get it into a form that can be used, and everything else, automation, AI, whatever comes next, gets a whole lot easier.

This blog post is based on an original AIIM OnAir podcast. When recording podcasts, AIIM uses AI-enabled transcription in Zoom. We then use that transcription as part of a prompt with Claude Pro, Anthropic’s AI assistant. AIIM staff (aka humans) then edit the output from Claude for accuracy, completeness, and tone. In this way, we use AI to increase the accessibility of our podcast and extend the value of great content.