AI for Leadership Communication
I was intrigued to read that the Professional Speechwriters Association is promoting a workshop titled ‘AI for Leadership Communication‘ taught by speechwriter Brent Kerrigan. The course promises:
…[a] course with one goal in mind: to help leadership communication professionals gain a hands-on, practical, shirtsleeve understanding of AI’s role in our work and how to use it ethically, effectively and strategically.
We’ll tailor it to your organization’s needs—the technology you use, the skillsets your team possesses and the communication problems you’re trying to solve, for the leaders you work for every day.
Together, you and your team will come away AI-aligned, with a toolbox of prompts and approaches that you can apply immediately to strengthen your research, enhance your messaging, drill down on fact-checking and refine your communication strategies. You will learn how to use generative AI, make the leap into agentic AI, and understand the (important) difference. Just as important, you’ll see how AI can help boost your value as individuals and as a team—by making you faster, more adaptive and more confident in the services you provide.
You’ll all return to your work less ambivalent about AI and more enthusiastic—clearer-minded about how it can help and how it can’t, and confident in your own ability to make AI work: for organization and its leaders, and the communicators they rely on.
Brent offers four 90-minute webinars tailored for beginners, priced at a flat $15K, plus an additional $1K for every participant over 15. This might work in the corporate world and certainly represents fair value for organizations that want a seasoned pro to guide them in what, for some, is the overwhelming and rapidly changing world of generative AI. And it is especially valuable since Brent promises to tailor it for each group.
Generating Coursework
I took Brent’s description of the first session in the series and fed it into Claude:
PROMPT: Act as a instructional designer. Create an outline of a course for corporate communications professionals titled ‘Generative AI in Speechwriting and Other Leadership Communications (Research, Structure and Composition)’ Include a non-technical explanation of what AI is—and isn’t—as far as communicators are concerned. Then focus on using AI to support the early and middle stages of the writing process. Begin with foundational generative AI techniques and strategic prompt development, give the essential skills to build better workflows, conduct fast and thorough speech research, and turn briefing notes into clear building blocks for speech drafts.
The result was a much more elaborate curriculum than would fit into a 90-minute webinar. Nevertheless, it is a useful framework for those not flush enough to pay Brent’s fees, showing how speechwriters willing to do some self-paced learning can engage with AI.
Claude’s response
Start of Claude generated content >>>>
Course Outline
Generative AI in Speechwriting and Other Leadership Communications
Research, Structure and Composition
Audience: Corporate communications professionals, speechwriters, executive communications teams Format: Instructor-led or self-directed modular learning Estimated Duration: 6 modules / ~9–11 hours of instruction + exercises
Course Philosophy
This course treats generative AI as a thinking partner and process accelerator, not a ghostwriter. The skills taught here are designed to make communicators faster, more thorough, and better prepared — while keeping human judgment, voice, and craft firmly in charge. The focus is on the early and middle stages of the writing process: research, discovery, framing, structure, and drafting building blocks.
Module 1 | What AI Actually Is — A Communicator’s Orientation
Duration: ~90 minutes Purpose: Build an accurate, non-technical mental model of generative AI so communicators can use it with confidence and appropriate skepticism.
1.1 Stripping Away the Hype
- Why the public narrative about AI confuses more than it clarifies
- What “generative” actually means: pattern, prediction, and language
- The difference between AI generating text and AI knowing something
- Why AI has no intentions, no experience, and no memory of your last session
1.2 What Generative AI Is, for a Communicator
- A fast, tireless language processor with vast pattern exposure
- A useful first-draft engine, brainstorming partner, and structural scaffold
- A tool that reflects what you give it — quality in, quality out
- An accelerant for the parts of writing that are slow, repetitive, or paralyzing
1.3 What Generative AI Is Not
- Not a researcher: it does not retrieve live, verified facts
- Not a strategist: it cannot assess organizational politics or stakeholder nuance
- Not a voice: it defaults to generic unless you teach it otherwise
- Not infallible: hallucination, overconfidence, and flatness are real risks
1.4 The Communicator’s Compact with AI
- You are the editor, not the typist
- AI raises a first floor; your craft builds the rest
- Accountability for accuracy, voice, and appropriateness remains entirely yours
- Introducing the concept of the human-in-the-loop workflow
1.5 A Quick Look at the Tools Landscape
- Overview of major platforms (ChatGPT, Claude, Gemini, Copilot) without technical deep-dives
- Key differences relevant to communicators: context windows, memory, file handling
- Security and confidentiality basics: what not to put in a prompt
- Practical guidance on tool selection for your organization
Module 2 | Prompt Development as a Professional Skill
Duration: ~2 hours Purpose: Establish strategic prompting as a core, learnable competency — the communicator’s primary interface with AI.
2.1 Why Prompting Is Not Just Asking Questions
- The prompt as a creative brief: specificity determines output quality
- How AI interprets vague instructions — and why the results feel generic
- The prompting mindset: directing, not requesting
2.2 Anatomy of an Effective Prompt
- Role: Assigning context and perspective (“You are an experienced speechwriter working for a Fortune 500 CFO…”)
- Task: Stating what you need with precision
- Constraints: Length, tone, audience, format, what to avoid
- Output format: Bullet points, prose, structured outline, table — specify it
- Examples: Using sample language to anchor the style you want
2.3 Core Prompting Techniques for Communicators
- Zero-shot, few-shot, and example-anchored prompting
- Chain-of-thought prompting: asking AI to reason step-by-step before producing output
- Persona prompting: establishing audience perspective to pressure-test content
- Iterative refinement: treating the first response as a draft, not a deliverable
- Constraint prompting: using restrictions to sharpen focus (“Do not include statistics. Avoid jargon. Write at an 8th-grade reading level.”)
2.4 Prompts for the Writing Process Specifically
- Prompts for generating questions you haven’t thought to ask
- Prompts for identifying gaps in an argument
- Prompts for exploring alternative framings of a message
- Prompts for tone calibration and register adjustment
2.5 Building a Personal Prompt Library
- Why saving and iterating on prompts is a professional asset
- Organizing prompts by task type: research, structure, drafting, editing
- Prompt templates for recurring communications tasks (earnings remarks, town halls, external keynotes)
- Workshop: Participants build their first five reusable prompt templates
Module 3 | Establishing AI-Assisted Workflows
Duration: ~90 minutes Purpose: Map the writing process clearly and identify where AI creates the most leverage — and where human judgment is non-negotiable.
3.1 Mapping the Communications Writing Process
- A clear stage-by-stage model: Discovery → Research → Framing → Structure → Drafting → Refinement → Delivery Prep
- Where most communicators lose time and why
- Introducing the concept of AI handoff points: where you bring AI in and where you take back control
3.2 Designing Your Workflow Before You Start Writing
- Why beginning without a plan produces mediocre AI output
- The pre-prompt checklist: what you need to know before you type a prompt
- Aligning your workflow to the type of communication (internal vs. external, scripted vs. extemporaneous, technical vs. inspirational)
3.3 Collaboration and Oversight in AI-Assisted Work
- Working within team environments: version control, transparency, attribution norms
- Communicating AI involvement to stakeholders (when and how to disclose)
- Establishing your organization’s guardrails for AI use in sensitive communications
3.4 Common Workflow Failures — and How to Avoid Them
- Accepting first-draft AI output without critical review
- Feeding AI too little context and expecting nuanced results
- Over-relying on AI for voice — and why executive communications is especially vulnerable
- Workflow exercise: Participants diagram a current project and identify three AI integration points
Module 4 | AI-Powered Research for Speeches and Leadership Communications
Duration: ~2 hours Purpose: Teach communicators to use AI to accelerate, organize, and deepen the research phase — while understanding its factual limitations.
4.1 The Research Challenge in Executive Communications
- Why speech research is different from academic or journalistic research
- The communicator’s research goals: context, credibility, narrative material, and audience insight
- Time pressure and the risk of under-researched speeches
4.2 Using AI to Generate Research Frameworks
- Prompting AI to produce a research agenda for a given topic and audience
- Using AI to surface angles, sub-topics, and lines of inquiry you might not have considered
- Asking AI to identify likely audience knowledge gaps, objections, or skepticism points
- Generating a “what do I need to know before I write this” checklist
4.3 Background Research and Context-Building
- Using AI to synthesize background on an industry, company, policy area, or issue
- Building a fast-briefing document from AI-generated summaries (with verification steps)
- Prompting for historical context, relevant precedents, and analogy material
- The verification imperative: every AI-generated fact must be confirmed with a primary source
4.4 Audience Research and Stakeholder Analysis
- Prompting AI to help profile an audience: likely concerns, priorities, cultural context
- Using AI to stress-test a message from the perspective of a skeptical audience member
- Building empathy maps and listener profiles using AI as a thinking partner
- Identifying language that resonates vs. language that alienates for a given group
4.5 Researching the Speaker
- Using AI to help synthesize information from speaker bios, prior speeches, and interviews
- Prompting for voice and style patterns from provided text samples
- Building a speaker profile document that informs drafting and maintains consistency
- Research lab: Participants use AI to produce a structured research brief for a sample speech assignment
Module 5 | From Briefing Notes to Building Blocks: Structuring the Draft
Duration: ~2 hours Purpose: Teach communicators to use AI to transform raw input — briefing notes, bullet points, background materials — into organized structural foundations for a speech or communication.
5.1 What a Briefing Note Is and What It Needs to Become
- The typical content of a briefing note: facts, context, objectives, key messages, tone direction
- The gap between a briefing note and a speech: narrative, flow, voice, emotional architecture
- The structural translation problem — and how AI helps bridge it
5.2 Feeding AI Your Source Material Effectively
- How to prepare and format briefing notes for AI input
- Providing context AI cannot infer: organizational culture, speaker personality, audience relationship
- Using the briefing note as a constraint document, not just a content source
- What to withhold from AI input for security and confidentiality reasons
5.3 AI-Assisted Message Architecture
- Prompting AI to extract and prioritize key messages from a briefing
- Using AI to identify the single most important idea in a body of content
- Generating a message hierarchy: primary message, supporting points, proof points
- Stress-testing message clarity: prompting AI to summarize in one sentence, then evaluating alignment
5.4 Building Speech Structures with AI
- Classic structural frameworks and when to use them (Problem–Solution, Past–Present–Future, Challenge–Response–Vision, The Narrative Arc)
- Prompting AI to propose multiple structural options for the same content
- Using AI to generate section headings and signpost language
- Mapping content from the briefing to structural slots — AI as an organizational sorter
5.5 Turning Structure into Draft Building Blocks
- The concept of the modular draft: discrete, replaceable units of content
- Prompting AI to develop individual sections — openings, transitions, proof points, closes — as separable building blocks
- Using AI to generate multiple versions of the same section for comparison
- The communicator’s role at this stage: curator and architect, not transcriptionist
5.6 Evaluating AI-Generated Structure
- What good structure feels like vs. what AI tends to produce (competent but flat)
- Identifying where AI has imposed a generic logic that doesn’t fit your speaker or audience
- Annotating and revising AI structure before moving to full drafting
- Practical exercise: Participants receive a sample briefing note and use AI to produce a fully annotated structural draft
Module 6 | Putting It Together — Applied Practice and Professional Judgment
Duration: ~90 minutes Purpose: Consolidate skills through an end-to-end applied exercise and establish a framework for ongoing, responsible AI use.
6.1 End-to-End Workflow Simulation
- Participants work through a realistic scenario: a 10-minute town hall address for a fictional executive
- Using AI at each stage: research brief → audience profile → message architecture → structural outline → draft building blocks
- Individual or team debrief: where did AI accelerate the work? Where did it fall short?
6.2 Recognizing and Fixing Common AI Output Failures
- The five most common problems in AI-generated communications content: vagueness, over-explanation, tonal flatness, unearned emotion, and structural conventionality
- Editing strategies for each failure type
- When to regenerate vs. when to edit
6.3 Developing Your AI Judgment as a Professional
- How to know when AI is helping vs. when it’s anchoring you to mediocrity
- Building critical distance from AI output — the 30-minute rule
- Continuing to develop your craft alongside your AI fluency
6.4 Looking Ahead: What’s Next in AI for Communicators
- Emerging capabilities relevant to communications professionals (multimodal input, real-time research integration, longer context windows)
- What is unlikely to change: the need for human voice, judgment, and relational intelligence
- Staying current without chasing every new tool
6.5 Course Wrap-Up and Personal Action Planning
- Each participant articulates three workflow changes they will implement immediately
- Building a 30-day AI integration plan
- Recommended resources for continued learning
Course Appendices
Appendix A — Master Prompt Library (30 starter prompts organized by workflow stage)
Appendix B — The Communicator’s AI Verification Checklist (fact-checking protocol for AI-assisted research)
Appendix C — Sample Briefing Note → Structural Draft exercise set (3 scenarios at varying complexity)
Appendix D — AI Tool Comparison Reference Card for Communications Professionals
Appendix E — Organizational AI Policy Template for Communications Teams
This course addresses Modules covering research, structure, and composition. A companion course — covering voice development, full drafting, revision, and delivery preparation — is recommended as a follow-on for teams seeking end-to-end AI integration in the speechwriting process.
<<< < End of Claude generated content
A Deeper Dive
Having reviewed this framework, speechwriters wishing to dive deeper might consider asking Claude to elaborate. Any of the bullet points listed in the course outline could be expanded on. For example:
PROMPT: Explain what you meant by the core prompting technique ‘Chain-of-thought prompting: asking AI to reason step-by-step before producing output’.
PROMPT: Suggest ways to overcome the five most common problems in AI-generated communications content: vagueness, over-explanation, tonal flatness, unearned emotion, and structural conventionality.
and so on.
I decided to go big and ask Claude to provide the contents of the first Appendix it listed.
PROMPT: Please generate Appendix A with 30 starter prompts organized by workflow stage that a speechwriter in the food and beverage industry could use.
The response (customizable for your own industry of course) supplies plenty of grist for the speechwriters mill.
30 Speechwriting Prompts
Start of Claude generated content >>>>
Here is your complete Appendix A — all 30 starter prompts, filterable by the six workflow stages from the course.
Discovery Stage
[1] You are an experienced communications strategist supporting the CCO of a major food and beverage company. I need to deliver a [keynote / town hall / investor remarks] on [topic]. Before I start researching or drafting, generate 10 questions I should answer about the speaker, the audience, and the occasion to ensure this speech achieves its goal. (Use before any briefing call.)
[2] I am writing remarks for our [CEO / CMO / VP of Supply Chain] at [event name/type]. The communication objective is [brief statement]. Generate a pre-prompt checklist — all the information I need to gather before I begin drafting or prompting an AI for this assignment. (Pre-work checklist.)
[3] Act as a veteran speechwriter. I have a briefing for a speech at a [food industry trade conference / retailer summit / investor day]. The speaker’s stated goal is [goal]. Identify three potential tensions or contradictions in that objective that I should resolve before writing begins. (Spot strategic contradictions early.)
[4] I am developing communications for a food and beverage leader speaking about [topic — e.g., sustainability / pricing pressures / portfolio innovation]. Generate five different angles this speech could take. For each, describe the strategic emphasis, the likely audience response, and the potential risk. (Explore angles before committing.)
[5] Our [CEO] is speaking at [internal town hall / external industry event] in [timeframe]. Here are my raw background notes: [paste notes]. Identify the most important missing information I need before I can write effectively, and explain why each gap matters. (Gap-spot raw briefing notes.)
Research Stage
[6] Build me a research agenda for a speech on [topic — e.g., sustainable packaging / GLP-1 drug impact on CPG consumption / supply chain resilience]. The audience is [e.g., senior retail buyers at a category leadership summit]. List the 8–10 most important research areas and explain why each matters to this audience.. (Build a full research agenda.)
[7] I am preparing remarks for our [CFO] at an investor day. The topic is [e.g., our margin recovery story]. Generate a list of the five most likely tough questions analysts will have on this topic, and for each, suggest the supporting data or proof points our speaker should be prepared to reference. (Anticipate analyst pressure.)
[8] Act as a research assistant for a speechwriter at a large CPG company. I need background context on [topic — e.g., the history of regenerative agriculture in food supply chains / recent trends in private label vs. branded grocery]. Provide a structured synthesis I can use as background. Flag any claims I must independently verify. (Generate synthesized background context.)
[9] I’m writing a speech that will reference our company’s sustainability commitments. Generate a framework for contextualizing our claims against industry norms — including benchmarks, certifications, and third-party reports I should research to give our claims credibility with a skeptical audience. (Frame sustainability claims credibly.)
[10] Our speaker must address [a difficult topic — e.g., price increases / a product recall / market share loss]. Provide a research framework: what facts I need, what the audience likely already knows and feels, what our position should rest on, and what I should avoid asserting without solid evidence. (Research sensitive or negative topics.)
Audience Stage
[11] I am writing remarks for our [CEO] at [event]. The audience is [description — e.g., 500 foodservice operators who have seen significant cost pressure]. Create a detailed audience profile: their primary concerns, likely attitude toward our company, what they need from this speech, and what language will resonate vs. alienate. (Build a full audience profile.)
[12] Act as a skeptical audience member. The speaker is [role] at [company type] addressing [topic]. From the perspective of a [specific persona — e.g., a retail category manager who has heard three vendor pitches this week], write 8 reactions, doubts, or unasked questions you would have during this speech. (Stress-test from a skeptic’s chair.)
[13] I need to write remarks for a leadership [town hall / all-hands] following [a difficult announcement — e.g., restructuring / plant closure / product recall]. The internal audience includes [employee groups]. Build an empathy map: what are they thinking, feeling, hearing, and fearing right now? What do they need from leadership? (Empathy mapping for difficult news.)
[14] Our [CMO] is keynoting at a trade event for retail grocery buyers, category managers, and private label heads. Generate a language guide: 10 phrases or framings that will signal credibility and partnership to this audience, and 5 phrases or approaches that will undermine trust or feel tone-deaf. (Language guide for trade audiences.)
[15] I’m drafting remarks for a speech being delivered to Wall Street analysts and media on the same day. Help me understand where messaging needs for these two audiences overlap and where they diverge. What are the key tensions I must manage, and how should I sequence and weight content? (Manage dual audiences.)
Messaging Stage
[16] I have the following briefing notes for a speech on [topic]: [paste notes]. Extract the three most important messages the speaker must communicate. For each, state it as a single clear sentence, identify its supporting evidence, and explain why it matters to this audience. (Extract the real messages from briefing notes.)
[17] Our [CEO] needs to deliver a message about [e.g., our transformation strategy / response to private label pressure / commitment to reducing food waste]. Suggest five framings for this central message — ranging from aspirational to pragmatic — and evaluate the strengths and risks of each for a [specify audience]. (Test multiple framings before committing.)
[18] I am writing remarks for [speaker] and need a message hierarchy. The primary message is: [state it]. Generate three supporting messages and two to three proof points for each. Make proof points specific enough that I know exactly what information I need to find and verify. (Build a message hierarchy with proof points.)
[19] Act as a brand strategist. Review these key messages I’ve drafted for a speech: [paste messages]. Assess each for clarity, distinctiveness, credibility, and memorability. Identify which message is doing the most work, which is the weakest, and what is missing entirely. (Audit your own key messages.)
[20] Translate the following corporate strategy language from our briefing document into plain messaging a [general employee audience / trade customer audience] can connect with: [paste language]. Rewrite each point in accessible language without losing the strategic intent. Flag any terms that sound hollow or evasive. (Translate corporate jargon into human language.)
Structure Stage
[21] I have the following content elements for a [12-minute keynote] on [topic]: [list points, themes, stories, data]. Propose three structural frameworks that could organize this content. For each, name it, describe the logic, explain when it works best, and map my content elements to the corresponding sections. (Get structural options before you commit.)
[22] Our [CEO] is delivering opening remarks at our annual customer summit — approximately [8 minutes]. I have the following content: [paste]. Using a Past–Present–Future structure, organize this content into a clear section-by-section outline with notes on the tone and purpose of each section. (Past–Present–Future for customer summits.)
[23] Our [VP of Sustainability] will announce [a new initiative — e.g., a net zero commitment / a regenerative sourcing program]. Develop a Problem–Solution–Call to Action structure. Include recommended section lengths, transition language between sections, and one specific opening hook option. (Structure a sustainability announcement.)
[24] Review the following speech outline: [paste outline]. Identify structural problems: sections that are too long or too short, transitions that will feel abrupt, points that are out of logical order, and content likely to lose the audience. Suggest specific revisions with brief explanations. (Diagnose a weak outline.)
[25] I am writing a [3-minute] executive introduction for [speaker name/role] at [event]. Draft a structural template for this format: what it must accomplish, in what order, with approximate word counts per section, one suggested opening line, and one note on what to avoid. (Template for executive introductions.)
Drafting Stage
[26] Write three alternative opening paragraphs for a speech by our [CEO] on [topic] to [audience]. The first opens with a direct challenge or provocation. The second opens with a brief relevant observation or story. The third opens with a striking fact (note: I will verify all data before use). Each opening: 60–90 words. (Generate three opening options.)
[27] Draft two versions of a transition passage moving a speech from [section A — e.g., our recent challenges] to [section B — e.g., the strategic response]. Version one: direct and confident. Version two: reflective and empathetic. Each transition should be 30–50 words and be written to be spoken aloud. (Bridge difficult section transitions.)
[28] I need a closing for a [town hall / keynote / customer remarks] on [topic]. The speaker’s final message is: [state it]. Write three closing options: one that ends on inspiration, one that ends on a clear call to action, and one that ends on a human, personal note. Each: 60–80 words. (Three closes for three occasions.)
[29] Draft a proof point passage supporting the claim: ‘[state claim — e.g., our investment in regenerative agriculture is delivering measurable results].’ Use [PLACEHOLDER] where specific statistics or examples should go — I will fill in verified data. The passage should be 80–100 words and feel concrete, not corporate. (Draft a proof point passage with placeholders.)
[30] I have raw bullet points from a briefing document representing our speaker’s key message on [topic]: [paste bullets]. Transform these into a cohesive 150-word passage of speech prose — written to be spoken aloud, not read. Use short sentences. Avoid jargon. Maintain a tone that is [direct / warm / confident / urgent — choose one]. (Transform bullets into spoken prose.)
A few notes on how to use this library:
The bracketed fields are intentional. Every [placeholder] in italic is a required input — the specificity you add there is what separates a useful, tailored output from generic AI prose. Resist the urge to skip them.
These are starting points, not finished prompts. Each prompt is designed to be enriched with context from your actual briefing notes, speaker bio, and organizational background before you submit it. The more context you layer in, the better the output.
The “hint” in parens after each prompt signals the specific workflow moment it’s built for — use it to judge whether you’re reaching for the right tool at the right time.
Prompts 1–5 (Discovery) are the most underused category in practice. Most communicators skip straight to research or drafting and pay for it later. Starting with a discovery prompt — even for a familiar assignment — consistently surfaces assumptions and gaps worth resolving early.
The prompts are also designed to be modified and saved as reusable templates once you’ve shaped them to your organization’s voice, your speaker’s typical events, and your team’s most recurring assignment types.
<<<< End of Claude generated content.
In Conclusion
It’s refreshing that the Professional Speechwriters Association is supporting the training of speechwriters and communications professionals in the use of generative AI. I’ve noted before that AI is a hot topic that has divided writers. I began experimenting with ways speechwriters can use AI in 2023, and have been impressed with the assistance it provides as a development editor.
Anything that enables speechwriters to productively engage with this technology is welcome.
I wish Brent every success in the delivery of his webinar series.


























