Chat GPT, what do you THINK?

I have always been fascinated by AI and having written about the adoption of AI in my dissertation, I have used Chat GPT since it became publicly available. I mainly use it to trigger my creative process, providing alternatives to the status quo or shortcuts for labor-intensive tasks. As a leader of many transformational activities, the value proposition for Gen AI can similarly accelerate innovation, improve productivity, or reduce workload for the executive and project manager alike. The ability to leverage an expansive data bank in large language models makes AI an invaluable tool for accelerating innovation and enhancing productivity.

AI as a Brainstorming Partner

By retaining the context of prior inputs, generative AI effectively simulates statefulness, making it incredibly helpful for creating an iterative brainstorming experience similar to working with a trusted colleague or mentor. Through one of these sessions, I even found myself typing, "What do you think the highest risks would be?" … Woah… the phrase "What do you THINK…" This moment made me pause—while ChatGPT mimics understanding, it reminded me that true thinking is still a human domain, and generative AI’s strength lies in augmenting, not replacing, human insight.

Generative AI: A Tool, Not a Thinker

We have come a long way in the last five years since I did my AI research. However, we need to remember that Gen AI is not yet "thinking"—it processes patterns from large amounts of data and predicts what comes next. I’m always a little surprised at the level of confidence Gen AI can declare something which is completely false. So, with the disclaimer that you always need to double-check everything output by a Gen AI model, here is a list of activities you may find helpful. I’ve personally used many of these and added some other ideas I’ll be trying in the future.

NOTE: always consider the type of data you are uploading to any public Gen AI model and de-identify/anonymize where appropriate to avoid sharing any confidential data.

Practical Use Cases for Generative AI

1. Writing Business Cases and Use Cases - I have used this feature to give me business cases to inform capability modeling, and a starter set of use cases for a health plan go-live and to predict the most likely failure points.
2. Creating Timelines and Project Plans - Entering an excel project plan, I was able to query Chat GPT to get a high-level summary of critical milestones.?
3. Generating Tables - Begin your prompt with "Give me a table I can cut and paste into Excel…"—it’s a huge time saver!
4. Risk and Dependency Predictions - After uploading a timeline, ask what risks and dependencies exist. Chat GPT also gave me some mitigation ideas.
5. Agendas & Note-Taking from Live Meetings - I used AI in MS Teams to create a transcript from a meeting, summarize what was discussed, and even generate a list of next steps and owners. The only flaw? A couple of times it didn’t work (just gave one of those dreaded "Oops" messages an hour after the meeting had finished), and I was left without any notes. Recordings are a useful backup.
6. Creating VB Macros for Excel - I automated the process of taking 14 different exports from Monday.com boards into a single spreadsheet to perform some analysis that Monday.com was unable to do. While it took some time to tweak it to perfection requiring some coding experience, performing this task weekly went from an hour to 5 minutes—with far fewer opportunities for human error.
7. Summarizing Documents - A life-changing feature for academics when the introduction and executive summary don’t quite cut it.
8. Generating Creative Content - Try DALL-E! It’s highly creative and powerful, though one time I had to ask it multiple times to remove a piggy bank from a financial image, and it never managed it, so I had to start again.
9. Creating Reports and Graphics - Create all kinds of different Project Management artifacts such as Gantt charts, task bar progress reports, resource allocation charts, and dependency diagrams.
10. Knowledge Base Creation - With careful consideration for company confidentiality, an option is to select a pre-trained language model, deploy privately and integrate with company knowledge repositories such as SharePoint. Deploying a chatbot interface can provide employees with a user-friendly way to query company policies, technical documentation and other proprietary information.

What’s Next?

How are you using generative AI to transform your work? Let’s share ideas and insights to shape the future of innovation.