The Uncertainty Cost is Real

Steve Jobs famously wore the same black turtleneck, jeans, and sneakers every day for one simple reason: to save time. The small daily decision of choosing an outfit becomes significant when multiplied across thousands of workdays.

Now consider how much time your organization loses when hundreds of employees spend their days searching through folders across multiple applications. The “closet” is overflowing with duplicates, partial versions, and endless drafts, all obscuring the truth and slowing everyone down. This uncertainty cost is both significant and very real.

And the impact doesn’t stop with people-hours. It extends directly into the most transformative technology of our time: AI and large language models (LLMs). The cost of using AI is proportional to the quantity and quality of the data you feed it. More duplicates and unnecessary versions mean more tokens used, higher processing costs, and slower results.

There’s also a quality cost. If you want accurate, high-value output, the engine must be trained and prompted with verified, final, consistently tagged documents, not drafts and clutter. Cleaner input means smarter, more reliable AI output.

The message is clear:

Organize your documents. Establish the record copy. Feed AI only what’s verified.

You’ll spend fewer tokens, get better results, and achieve a meaningful ROI.