In the AI Era, More Data Isn’t Better; ‘Business-Savvy’ Data Is More Valuable!

Someone recently asked, in the AI era, how should companies handle their data? Is it just about collecting data and throwing it all into a model to train a useful one? Dream on! If your data is that kind of unprocessed, “messy data,” like a garbage dump where you just throw any textual stuff into the database, then that data is essentially meaningless because it lacks your business logic. Simply put, it’s a bunch of “zombie data” – it looks busy but is not very useful, and it wastes computing power and resources. Not to mention those “cheap, purchased data” sets. Unless you’re doing pre-training for models, this kind of data might even be worse than open-source data. Why? Because such data is often generic and lacks specificity, let alone helping you optimize your business.

In the AI Era, What’s Truly Valuable?

It’s the data with embedded business logic! In the world of AI, the relationship between business, data, and models is like a pyramid:

• At the bottom is the model algorithm, which is the foundation of AI.
• Above the model is data, which is the fuel for AI.
• Above data is business, which is the goal of AI. Only when your data incorporates clear business logic can you train truly valuable models and enable AI to genuinely empower your business. I’ve always believed that when undertaking AI projects, investment in data should never be skimped on. If you’re lazy with data, AI will show its “colors” in your business results. You might even need to spend a significant amount to get your data right.

Your Data Determines How Far Your AI Can Go

It’s like this: if you feed your AI “delicacies,” it will naturally prepare a grand feast for you; but if you feed it “leftovers,” it can only produce some “dark cuisine.”

High-Quality Data is AI’s “Nutrient”

For AI to truly understand your business and solve your problems, you need to provide it with high-quality, targeted data. This data must be carefully cleaned, organized, and labeled, and it must fully reflect your business logic.

The “Business Logic” in Data is Its Soul

More data isn’t necessarily better; what’s better is data that is “business-savvy.” Only data that contains your business understanding and industry knowledge can truly enable AI to be effective.