AI tools are useful only when people know what job they are giving them. This course shows employees how to choose the right tool, start with ChatGPT, Claude, or Copilot, and apply AI to writing, research, data analysis, meetings, scheduling, customer messages, and daily workflows. The focus stays practical: use AI to reduce busywork, then review the result before it reaches a colleague, customer, or decision maker.
What you'll learn:
- Match AI tools to the task instead of using one tool for everything
- Use AI for writing, research, data analysis, meetings, and customer communication
- Review AI output for accuracy, tone, privacy, and missing context
- Build a repeatable workflow that keeps humans responsible for the final result
Using AI Tools Effectively at Work
A plain-English guide to how to choose an AI tool based on the job, with workplace examples and a warning about using the most familiar tool even when it is a poor fit.
How how to start using ChatGPT, Claude, or Copilot at work shows up in real work, including the checks that prevent pasting sensitive company information into an unapproved tool.
How using AI for drafting, editing, and rewriting shows up in real work, including the checks that prevent publishing polished text that is vague, inaccurate, or off brand.
How to use asking for summaries, comparison tables, source checks, open questions, and next-step research prompts while keeping an eye on accepting unsupported claims because the summary sounds confident.
How to use asking questions about trends, outliers, segments, assumptions, and possible explanations while keeping an eye on mistaking a plausible pattern for a proven conclusion.
A plain-English guide to using AI for meeting notes and summaries, with workplace examples and a warning about sharing summaries that include private comments or incorrect actions.
A plain-English guide to using AI for scheduling and task management, with workplace examples and a warning about letting automation move work without confirming people, timing, or priorities.
How to use setting tone, facts, policy boundaries, empathy level, and escalation triggers before generating a response while keeping an eye on sending a message that sounds helpful but promises something the company cannot do.
A plain-English guide to how to review and validate AI output, with workplace examples and a warning about treating review as optional because the output looks polished.
A practical look at how to build an AI-assisted workflow: where it helps, what to check, and how to avoid adding AI to every step until the process becomes harder to manage.
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.
