Personalize AI to Capture Proprietary Data and Gain Competitive Advantage

Key Quotes

"The default approach to AI in business today is to use it like a shortcut. Everybody is so laser-focused on efficiency, using it to produce more in less time with the least amount of effort, to churn more things out. I do think it is a bit of a short-sighted approach."

Taylor Radey argues that businesses often misuse AI by solely focusing on efficiency and speed, treating it as a shortcut. This approach, Radey explains, is short-sighted because it overlooks the potential for AI to produce more strategic and higher-quality outcomes.

"My concern is that this race to do less is going to lead a lot of companies straight into the trap of looking and sounding like everybody else. The reality is that good enough is no longer good enough. Good enough has become so accessible and so attainable that marketing professionals, sales people, brands, businesses, we actually have to be better in order to stand out."

Radey expresses concern that an overemphasis on efficiency with AI will cause businesses to become indistinguishable from their competitors. She emphasizes that in an era where "good enough" is easily achievable with AI, true differentiation requires a commitment to producing superior work.

"Second, you're going to produce work that is actually original and authentic to your business, and so that is going to be unique. It's going to, like I said, stand out, especially in a world that is going to be becoming increasingly cluttered with generic AI content."

Taylor Radey highlights that personalizing AI enables businesses to generate content that is uniquely their own. This originality is crucial for standing out in a market increasingly saturated with generic AI-generated material.

"So D.A.T.A. D is Domain Expertise. That is the deep insight you have after spending years in a given field. Some things to think about here are: what do experts in your field know that beginners or novices maybe don't? What do outsiders tend to get wrong about your space? How can you tell if a piece of content has been written by a true expert versus an outsider?"

Radey defines "Domain Expertise" as a key component of personalizing AI, emphasizing the unique knowledge held by experts. She suggests probing questions to help identify this specialized insight, distinguishing it from general knowledge that AI models might already possess.

"The first place that I encourage people to start is to capture and collect all that stuff. So you need to collect all the files and the documents that you already have in your business that might be technical support documents, product descriptions, existing marketing content, sales pitch decks, proposals, strategy documents, whatever it is."

Taylor Radey advises that the initial step in personalizing AI is to gather existing business documentation. She lists various types of internal documents, such as support materials and marketing content, as valuable resources for this collection process.

"The real value is it grounds all of its answers in the sources you provide. So similar to that kind of knowledge management that I talked about earlier, but instead of pulling across all of these systems, you're assigning specific sources to a notebook, and the answers are going to be grounded in those specific files that you've designated."

Radey explains the core functionality of NotebookLM, stating that its primary value lies in grounding AI-generated answers in user-provided sources. She contrasts this with other knowledge management systems by highlighting that NotebookLM focuses on specific designated files rather than broad system integration.