Small Data, Big Impact: Making The Most Of AI With Less

Headlines have reiterated that investments in big data have continued to increase, and the big data story they’re selling us on just keeps getting bigger. But it’s time to burst that bubble.

For the last decade, the big data story has been plastered across headlines and weaved into organizations’ IT models as the end-all-be-all solution. We’ve been sold on the idea that AI and big data will together be what drives modern businesses down the path to success, helping these companies thrive in today’s digital-first, consumer-driven environment. Across almost every industry, from financial services to healthcare to real estate and beyond, this story told us that all problems must be solved by more computing power and more data analysis — AI and big data.

And that’s a good thing since companies have been, for years, aggregating massive data sets to fuel algorithms to create positive experiences and outcomes. Unfortunately, the problem many businesses run into is that gathering massive amounts of data doesn’t really amount to much when 80-90% of enterprise data is unstructured and turns out to be effectively useless. In practice, big data isn’t as applicable for all businesses as it initially seemed; it really only applies to the tech giants with resources like a massive budget and a digital-first business model that enable them to make the most of this approach. For everyone else, big data has the opposite effect. Instead of powering AI, it actually compromises and thins out the transformative potential for AI to impact society in a meaningful way.

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