AI can feel technical from the outside, but most business use starts with a practical question: what can this tool help us do better, and where should we be careful? This course gives employees a plain-English foundation in artificial intelligence, machine learning, generative AI, large language models, business use cases, myths, governance, and ongoing learning. It helps teams talk about AI clearly before they make bigger decisions with it.
What you'll learn:
- Explain core AI terms without getting lost in technical jargon
- Understand what AI tools can do well and where they still need human judgment
- Spot common business use cases, myths, risks, and governance needs
- Build a realistic habit for keeping up with AI as tools and rules change
AI Literacy for Business Professionals
How what artificial intelligence means in ordinary business language shows up in real work, including the checks that prevent treating every smart feature as the same kind of AI.
A plain-English guide to the difference between machine learning, deep learning, and generative AI, with workplace examples and a warning about using technical labels without knowing what kind of problem each method solves.
How how large language models predict and generate text shows up in real work, including the checks that prevent assuming fluent answers are always accurate answers.
A practical look at where AI is strong and where it still struggles: where it helps, what to check, and how to avoid using AI for decisions that require facts, consent, or expert review.
What employees need to know about common AI use cases across business teams, why it matters, and how to avoid starting with a tool instead of a real business problem.
How the gap between AI hype and day-to-day reality shows up in real work, including the checks that prevent believing AI is either magic or useless.
What employees need to know about the main tool categories and vendors in the AI market, why it matters, and how to avoid choosing tools by brand recognition rather than fit, security, or policy.
What employees need to know about how AI may change work in different industries, why it matters, and how to avoid copying another industry's AI use case without checking local rules or workflows.
How the role of AI governance and oversight shows up in real work, including the checks that prevent letting AI use spread through informal habits with no accountability.
A plain-English guide to how employees can keep up as AI changes, with workplace examples and a warning about chasing every new feature or ignoring AI until a change is forced.
About the teacher
Vikram Chalana
Vikram Chalana is the co-founder and CEO of Pictory. He is an engineer and entrepreneur who previously co-founded Winshuttle, an enterprise software company that grew to 300 employees globally.
At Pictory, Vikram works on making video creation easier for trainers, educators, marketers and business teams who want to turn existing content into clear, useful videos with AI.
