Made emerging AI understandable and started the organizational conversation
I began helping coworkers understand generative AI early in its enterprise adoption, when the technology was still unfamiliar and easy to dismiss. Rather than explain it abstractly, I built demonstrations around work employees already recognized: writing emails, creating documents and lab reports, sourcing products, building formulas, generating images, and structuring conversations so the output stayed focused and useful.
I created two internal learning decks, From DeLoreans to Deep Learning: A Time Traveler’s Guide to AI and AI Comparison and Examples. The material compared tools including Duet AI, Midjourney, ChatGPT, and DALL-E, while teaching people to define the objective, constrain the prompt, summarize context, follow up, and improve an answer iteratively. I also addressed why early accuracy limitations should lead to better testing and judgment, not automatic dismissal of the technology.
Generative AI was arriving faster than most employees could make sense of it.
I translated the tools into familiar work examples and started advocating for coordinated awareness.
Coworkers and the head of IS.
AI became something people could explore practically instead of dismissing abstractly.
- I spoke directly with the head of IS about the emerging tools I was seeing and how I believed they could support employees’ work in the future.
- I encouraged forming an AI radar team to maintain a shared view of new capabilities, how people were adopting them, and which developments might matter to the organization.
- I emphasized that knowledge sharing would become increasingly important as the tools evolved, because useful adoption would depend on employees learning from one another rather than experimenting in isolation.