About this session
AI is now built into many of the tools people already use at work, but the language surrounding it can make the subject feel more complicated than it needs to be.
Generative AI, copilots, assistants, predictive systems, automation and agents are often discussed together even though they do different things and require different levels of human involvement.
This session gives participants a practical mental model. Rather than starting with technical architecture, it begins with work.
Participants learn the kinds of contribution AI can currently make: generating a first draft, summarizing material, extracting information, reorganizing content, comparing options, identifying patterns, transforming formats and helping people think through possibilities.
They also examine where AI is weaker: establishing truth, understanding hidden organizational context, exercising accountable judgment and knowing whether an output is appropriate to use.
Participants then explore how AI fits into a task.
A useful pattern is not simply 'give the work to AI.' It is to decide what outcome is needed, provide appropriate context, let AI contribute where it is useful and retain human review where judgment, accuracy, confidentiality or consequences require it.
Participants use this structure to evaluate realistic workplace activities rather than relying on abstract examples.
Finally, participants choose a practical starting point. They identify a low-risk task worth experimenting with, define the human role and establish what should be reviewed before the result is used.
The aim is to leave participants neither dazzled nor intimidated by AI, but equipped with a clear understanding of what it is good for, what it is not and where deeper AI skills can take them next.
What your people take away
- Understand the main forms of AI employees are likely to encounter at work without needing technical expertise
- Recognize common tasks where generative AI can make a useful contribution
- Identify important limitations including factual reliability, missing context and lack of accountable human judgment
- Break a workplace task into what the human provides, what AI contributes and what the human must review
- Recognize essential information-sensitivity and responsible-use boundaries before experimenting
- Choose a practical, low-risk AI use case and define what successful experimentation should look like
Shared with you
See the full session
Create your free Workbliss profile to see the rest of this outline and book it. It takes a minute, with your work email.
- What each length covers, 30 minutes to full day
- Everything that’s covered, part by part
- Book online, and browse 1,500+ more sessions for your teams
Already a member? Sign in
What each length covers
30 minutes
30 Minutes — Key Points: Understand What AI at Work Actually MeansA focused 30-minute session on three key points from Understand What AI at Work Actually Means: AI is a category — not one thing, understand generative AI and AI assistant does not mean human colleague.
- AI is a category — not one thing
- Understand generative AI
- AI assistant does not mean human colleague
Covers 3 of 4 points in Understand What AI at Work Actually Means.
60 minutes
AI at Work Without the JargonA focused introduction to workplace AI. Participants learn what generative AI can and cannot do, examine common work patterns and choose one practical, low-risk use case for responsible experimentation.
- What AI at work means
- Generative AI
- AI assistants
- Common AI capabilities
- Common AI limitations
- Generating and transforming
- Extracting and organizing
- Human judgment
- Information sensitivity
- Choosing a first use case
- AI at Work Starter Map
- Live Q&A
Covers 1 of 4 parts: Understand What AI at Work Actually Means.
90 minutes
From AI Curiosity to Practical Workplace UseThe extended session connects AI fundamentals with real workplace tasks. Participants explore capabilities, limitations, task selection, human review, information boundaries and how to run a useful first AI experiment.
- Workplace AI landscape
- Generative AI
- AI assistants
- AI-generated content
- Summarization
- Extraction
- Transformation
- Comparison
- Brainstorming
- AI limitations
- Human judgment
- Information sensitivity
- Task decomposition
- AI contribution
- Human review
- Safe experimentation
- Next-step learning
- Live Q&A
Covers 2 of 4 parts: Understand What AI at Work Actually Means and Know What AI Is Good At — and Where It Struggles.
3 hours
Covers 3 of 4 parts: Understand What AI at Work Actually Means, Know What AI Is Good At — and Where It Struggles and Put AI Into the Task Without Giving Away the Work.
Full day
AI at Work Foundations LabA hands-on full-day workshop covering all four modules. Participants explore realistic workplace tasks, identify what AI can contribute, examine limitations and information boundaries and design a practical first AI-assisted workflow.
- Module 1 — Understand What AI at Work Actually Means
- Module 2 — Know What AI Is Good At — and Where It Struggles
- Module 3 — Put AI Into the Task Without Giving Away the Work
- Module 4 — Start Small, Learn Fast & Build Capability
- AI Capability Sort
- AI Myth vs. Reality Review
- Generate / Transform Exercise
- Extract / Organize Exercise
- Human Judgment Scenario
- AI Limitation Spotting
- Task Outcome Mapping
- AI Contribution Mapping
- Human Review Design
- Information Sensitivity Check
- First Use-Case Selection
- AI Experiment Planner
- AI Learning Path Map
- Live Q&A
Covers all 4 parts.
Also available as a 4-week or 8-week program, for change that lasts. Ask us about it.
What’s covered
Understand What AI at Work Actually Means
Every length- AI is a category — not one thingParticipants distinguish broad workplace AI from a single chatbot or product.
- Understand generative AIParticipants develop a practical understanding of generative AI as technology that produces new outputs such as text, images, audio, code or structured content in response to instructions and context.
- AI assistant does not mean human colleagueAI interfaces can feel conversational, but participants learn not to confuse conversational fluency with human understanding, intention, memory, accountability or judgment.
- Look beyond the hypeParticipants distinguish demonstrated capability from predictions about what AI might eventually do.
Know What AI Is Good At — and Where It Struggles
90 minutes and longer- Generate & transformAI can help produce drafts, variations, outlines, examples, summaries, translations and reformatted content.
- Extract, organize & compareAI can help pull information from appropriate material, organize themes, compare supplied content or convert unstructured information into a more usable format.
- Support thinking without replacing itAI can generate questions, alternative viewpoints, options and counterarguments that help a person think more broadly.
- Recognize the limitsAI may generate incorrect facts, miss hidden organizational context, misunderstand ambiguous instructions or produce confident answers without adequate evidence.
Put AI Into the Task Without Giving Away the Work
3 hours and longer- Start with the outcomeParticipants begin with what the task needs to accomplish rather than asking what they can make AI do.
- Decide what AI should contributeParticipants break tasks into parts and identify where AI may contribute usefully.
- Keep human judgment visibleParticipants define what the person still needs to understand, choose, validate, adapt or approve before an AI-assisted output becomes usable work.
- Notice the information you are providingBefore entering content into an AI tool, participants pause to consider whether the information is public, internal, confidential, personal, sensitive or otherwise restricted under organizational policy.
Start Small, Learn Fast & Build Capability
Full day only- Choose a good first use caseParticipants identify repetitive, time-consuming or cognitively demanding work where AI could provide a useful contribution without creating unnecessary risk.
- Define what better would look likeAI use should have a reason.
- Review what actually happenedParticipants compare the AI-assisted approach with the previous way of working.
- Know what to learn nextParticipants map their next capability according to the work they want to do.
Tools and materials
- Workplace AI Landscape Map
- AI Terminology Guide
- AI Capability Guide
- AI Limitation Review
- AI Task Opportunity Map
- Task Suitability Check
- Human + AI Task Map
- Human Review Planner
- AI Output Review Guide
- Information Sensitivity Check
- Approved Tool Decision Guide
- First AI Experiment Planner
- AI Experiment Review
- AI Learning Path Map
- AI at Work Starter Playbook
Who it’s for
- Employees who are new to workplace AI and want a practical, jargon-free starting point
- Teams beginning to use generative AI assistants in everyday work
- Managers who need enough AI understanding to support employees without becoming technical specialists
- Organizations introducing approved AI tools and wanting a common foundation across functions
- Employees who have experimented informally with AI but want a clearer understanding of where it is genuinely useful
- Mixed-function cohorts that need a shared language before moving into more advanced AI-at-Work learning
How booking works
- Book online. Create a free Workbliss profile, then pay with session credits, by card or by invoice.
- Pick a date. Choose a date at least 14 days ahead, or book now and set the date later.
- Choose your expert. Within 3 working days, we send you profiles of the experts available for your date.
- We deliver it. Your expert is briefed on your people and goals, then runs the session live online or at your site.
Questions about AI at Work, Explained: What It Can Do & Where to Start
How long is AI at Work, Explained: What It Can Do & Where to Start?
AI at Work, Explained: What It Can Do & Where to Start runs as 30 minutes, 60 minutes, 90 minutes, 3 hours or full day. You choose the length when you book. A 30-minute session covers three key points from Understand What AI at Work Actually Means: AI is a category — not one thing, understand generative AI and AI assistant does not mean human colleague. A 60-minute session covers Understand What AI at Work Actually Means in full, with a live Q&A. A 90-minute session adds Know What AI Is Good At — and Where It Struggles. A 3-hour session adds Put AI Into the Task Without Giving Away the Work. A full-day session adds Start Small, Learn Fast & Build Capability. It is also available as a 4-week or 8-week program.
Can AI at Work, Explained: What It Can Do & Where to Start be delivered online or in person?
Yes, both. It runs live online, so every office can join at the same time, or in person at your site, in any country.
How do we book AI at Work, Explained: What It Can Do & Where to Start?
Create a free Workbliss profile with your work email, then open AI at Work, Explained: What It Can Do & Where to Start to see the price for each length and book it. You can pay with session credits, by card or by invoice, and choose a date at least 14 days ahead, or set it later.
Who leads the session?
A vetted Workbliss expert, briefed on your people, culture and goals before the session. After you book, we send you profiles of the experts available for your date within 3 working days, so you can choose who leads it.
Can it be tailored to our company?
Yes. Every session is shaped around your goals, your people and the benefits you already offer, and delivered by experts in your people’s languages.