Introduction and context

• What generative AI is, where we are now and what it is good at
• The confidence problem in AI writing – why it sounds right even when it is wrong
• Key terms and acronyms explained in plain English
• Ethics, confidentiality and responsible use in a workplace setting

How AI writing tools work (and why they go wrong)

• How AI writing tools generate text in practice (in plain English)
• Why hallucinations happen and when they are most likely
• Where errors show up most often: facts, citations, product details and claims
• When to use AI and when to avoid it

Hallucinations and accuracy control

• Practical tactics to reduce hallucinations in the first draft
• Prompt techniques that force clarity: assumptions, unknowns and source boundaries
• Verification habits that don’t kill speed
• Turning verification into a simple publish-ready checklist

Prompting for better writing outcomes (hands-on)

• How to brief AI clearly using plain English and simple constraints
• Prompt patterns for common writing tasks: outlining, drafting, rewriting, shortening and simplifying
• Iteration techniques that improve quality without endless back-and-forth
• Hands-on exercises based on realistic workplace writing scenarios

Planning and ideation

• Turning vague stakeholder input into a clear brief
• Using AI to generate angles, outlines and content options
• Stress-testing structure, logic and clarity before you draft
• Writing for different audiences and objectives without reinventing the wheel

Drafting and editing with AI

• Producing stronger first drafts and more useful variations
• Editing for clarity, concision and tone
• Adapting a single piece of writing for different formats and channels (web, email, social and LinkedIn)
• Avoiding “AI beige” while keeping readability high
• Working faster while keeping standards

Brand voice and consistency

• Keeping tone of voice consistent across AI-assisted writing
• Using brand principles, examples and do’s and don’ts to guide outputs
• Common causes of tone drift and how to prevent them
• Lightweight processes for review and sign-off

Reusable writing assistants and automation (Custom GPTs, Gemini Gems & Copilot Agents)

• When automation helps: repetitive writing tasks, quality checks and consistency
• Building a reusable assistant for tone of voice, structure and editing rules
• Creating standard prompts and templates for common content types
• Guardrails: what these assistants should never do, data considerations and approval flows

Applying the workflow and next steps

• A repeatable end-to-end workflow from brief to final draft
• What to automate and what should remain human-led
• Key takeaways, pitfalls and recommended next steps