AI Literacy for Employees

AI Literacy for Employees

Course Overview

Artificial intelligence is already part of everyday work, from drafting emails and summarising reports to scheduling, translation, and data analysis. This course gives employees a practical, non-technical understanding of what AI is, how generative AI tools work, and how to use them safely, responsibly, and productively on the job. Participants learn to write effective prompts, check AI output for accuracy, protect confidential company and personal data, and recognise the limits and risks of AI, including bias, fabricated information, and over-reliance. By the end of the course, employees will be able to use approved AI tools with confidence and good judgement, in line with company policy.

Learning Outcomes

By the end of this course, participants will be able to:

1. Explain in plain language what AI, machine learning, and generative AI are, and how they differ from traditional software.
2. Identify common workplace uses of AI and tasks where AI is and is not appropriate.
3. Write clear, structured prompts that produce useful, relevant results.
4. Evaluate AI-generated output for accuracy, completeness, bias, and fabricated content before using it.
5. Apply data privacy and confidentiality rules when using AI tools, including what information must never be entered.
6. Describe key ethical, legal, and reputational risks of AI use, including intellectual property and transparency concerns.
7. Follow the organisation’s AI acceptable-use policy and know when to escalate questions or concerns.

Course Outline

Module 1: What Is AI?
Defining artificial intelligence, machine learning, and generative AI; how large language models produce text; a short history and why AI has accelerated recently; common myths and misconceptions; AI tools employees may already be using without realising.

Module 2: AI in the Workplace
Practical use cases by function: writing and communication, research and summarisation, data and reporting, translation, scheduling, and planning; tasks AI handles well versus tasks requiring human judgement; the “human in the loop” principle; examples of AI improving productivity and examples of it going wrong.

Module 3: Working Effectively with AI Tools
Anatomy of a good prompt (role, task, context, format, constraints); iterating and refining responses; providing examples; asking for alternatives and critiques; hands-on prompt practice with before-and-after examples; building simple reusable prompt templates for routine tasks.

Module 4: Checking AI Output
Why AI makes mistakes; hallucinations and invented sources; recognising outdated or incomplete information; detecting bias and one-sided answers; a simple verification checklist; accountability: the employee, not the tool, is responsible for the final work.

Module 5: Data, Privacy, and Security
What happens to data entered into AI tools; public versus company-approved tools; categories of information that must never be shared (personal data, client information, financial data, trade secrets, credentials); recognising AI-enabled phishing, deepfakes, and social engineering; reporting suspected incidents.

Module 6: Responsible and Ethical AI Use
Fairness and bias in AI decisions; transparency and disclosing AI assistance; copyright and intellectual property considerations; regulatory landscape overview (e.g. EU AI Act, data protection laws); the organisation’s AI acceptable-use policy; scenario-based decision exercises.