Three Personal Use Cases for ChatGPT and Grok

Over the last couple years, I’ve been working on incorporating AI tools into my personal workflow. One of the fun questions I enjoy asking other entrepreneurs is how they’ve integrated AI into their own lives and businesses. This has provided me with a variety of ideas and use cases to experiment with and explore. Today, I want to share the three most recent ways I’ve used AI.

1. Preparing for a Board Meeting

Last week, I attended a board meeting with 30 other board members. Prior to the meeting, we received a PDF containing the board agenda, a list of attendees, and governance items. I uploaded this PDF to ChatGPT and Grok, asking each tool to extract all the names and companies listed, then search the web for two to three news items or recent events about each person or company. Within a couple of minutes, they generated a bullet-point list of all the attendees, their companies, and relevant recent news. As a result, I entered the board meeting much better prepared, with a variety of topics to discuss during our dinner session.

2. Analyzing a Potential Geographic Expansion

One of our companies is researching the next city to expand into, based on our demographic profile and the most common types of users. I fed the details into ChatGPT and Grok, explaining the situation: “We’re considering City X. Our typical users are these types of people, in these types of industries, with these characteristics. Analyze the most prominent firms in those industries in that city, identify the neighborhoods where they’re based, and rank the top 10 neighborhoods based on these parameters.” A few minutes later, I received detailed reports with citations and a strong recommendation for the best geographic location.

3. Understanding Neighborhood Dynamics in South Downtown Atlanta 

We wanted to analyze the neighborhood dynamics around residential units and retail use in South Downtown Atlanta. I explained the context to the AI—our neighborhood redevelopment goals, our desire to create a large, innovation-focused district for entrepreneurs and startups, and how residential units might influence the area. I asked: “How would residential units for people living in the neighborhood impact demand for restaurants and retailers?” The AI instantly returned a retail demand equation, calculated based on the number of proposed residential units. It included a range of retail square footage demand and an estimated annual spend per resident at local establishments. In moments, I had a framework and example data to work with.

These three recent examples really highlight the power of having a thoughtful, personal assistant that can perform deep dives almost instantly. The possibilities for use cases seem endless. I’m committed to further incorporating AI into my daily life and actively seeking out more applications. For me, these examples underscore the value of having instant research and analysis always on demand.