What is AI, Really? (And what it means for your job)

A fun, no-jargon introduction for people who are brand new to AI, and a solid refresher for everyone else. Starts from things the audience already uses every day (spam filters, autocorrect, movie recommendations) to show they have been working with AI for years, then builds the plain-language family tree: rules, classic machine learning, and generative AI, with a live demo and some myth-busting along the way. No math, no acronym soup. Then the question on everyone's mind: what does this mean for my job? Real published examples show the consistent pattern of people being repurposed rather than replaced, and why the process knowledge in this room becomes more valuable, not less. Closes with a plain-language first look at automation risks and guardrails: where AI gets things wrong, why over-trusting it is the real hazard, and the simple safeguards (a human in the loop, clear rules for what goes into public tools) that the rest of the series builds on. Governance thread. Automation risks and guardrails, introduced in plain language, plus acceptable use: simple ground rules for what should and should not go into public AI tools. Vocabulary. AI vs. machine learning vs. generative AI · large language model (LLM) · prompt · hallucination · model · training vs. inference · copilot / assistant · agent · automation vs. augmentation · human-in-the-loop · guardrails Takeaways. A cheat-sheet card on the final slide: the AI family tree at a glance (rules vs. machine learning vs. generative AI, and what each is good for). Presenter Bio: Dr. Jeanne McClure is an applied AI researcher, builder, and the founder of Ars Innovate Technologies & Consulting in Raleigh, North Carolina, where she ships B2B AI products and workflows for manufacturing, healthcare, and education, from answering and booking platforms to systems that run entirely on-site, keeping proprietary data in the building. She has worked in classical and modern AI since 2018 and been programming since the early 2000s. Her focus is AI people can trust: human-in-the-loop design, observability, evaluation frameworks, and returns you can measure. Earlier in her career, at packaging company Stephen Gould, she managed end-to-end programs for Revlon, Liggett, and Pergo, from package and label through floor packaging and on-time shipment. Over the last two years she has delivered more than 15 workshops to over 2,000 professionals at all levels on working with data science and AI. She co-authored a 2026 paper, built on her Orchestration Maturity Framework, on why AI readiness is an organizational learning problem, not a technology purchase, and holds a PhD from NC State University.