Overview

Lecture URL: https://skill.re/learn/manager/presentation-and-narrative-building.php

AI FOR MANAGERS CERTIFICATION

Independent AI Application (Level 3) | Independent Communication Workflows

LECTURE: Presentation and Narrative Building

Lesson 1.3 | Estimated Duration: ~27 minutes

Welcome to the AI for Managers certification program. I am your instructor, and today we are covering one of the essential lessons in the Independent Communication Workflows module: Presentation and Narrative Building.

This is Lesson 1.3 in Level 3, the Independent AI Application track. Whether you are joining us as a new manager finding your footing, a seasoned director refining your approach, or a VP setting strategic direction for your organization, the material in this session is designed to meet you where you are and give you something immediately actionable.

In our previous lesson, we covered Difficult Conversations Preparation. Today we build directly on that foundation. If any of those concepts feel uncertain, I would encourage you to revisit that material before we go further.

Before we begin, let me set expectations. This is not a passive lecture. I will ask you to think, to challenge assumptions, and to connect what we discuss to your own work. The managers who get the most out of this program are those who pause, reflect, and apply. So I encourage you to have a notepad ready, whether physical or digital, and to jot down ideas as they come to you.

Let us get started.

Lesson 1.3: Presentation and Narrative Building

Title & Purpose

Presentation and Narrative Building teaches you to use AI to develop compelling presentations, executive

summaries, and narratives from complex inputs--strategy, data, research, disparate perspectives. AI helps you

synthesize information, identify storylines, and surface different ways to frame complex material. You exercise

judgment about what story to tell, what emphasis serves your audience, and how to structure your thinking.

By the end, you'll independently move from raw inputs to a cohesive narrative with confidence.

Why This Matters for Managers

Managers constantly translate complexity into clarity:

• Quarterly business reviews that make sense of six months of data
  - Strategic updates that frame organizational direction
  - Presentations that help executives understand a problem and your recommendation
  - Team updates that create shared understanding across diverse knowledge
  - Client briefings that position your work in their context

The challenge: You're drowning in inputs--data, emails, perspectives, research, feedback. The narrative

doesn't emerge naturally. You need a way to organize it.

The AI opportunity: AI excels at:

• Synthesis (finding threads across disparate inputs)
  - Pattern recognition (what themes emerge? What's the story?)
  - Narrative structures (chronological, problem-solution, comparative, etc.)
  - Emphasis (what's essential? What's supporting?)
  - Translation (how to explain this to a different audience)

What AI can't do: Decide what story should be told. That's judgment. AI shows you options; you

choose what's authentic and true.

The manager value-add: You know your audience, your organization, what's politically safe, what's

bold. You know what's a half-truth vs. a full truth. You decide whether to play it safe or challenge.

Core Concepts

1. Narrative Architecture

Strong narratives have structure:

• Opening: What question are we answering? What problem are we solving? Why does it matter?
  - Middle: Here's what we found / learned / know. (Evidence, data, research, experience)
  - Turning point: This is what changes or matters. This is the insight.
  - Implication: So what? What does this mean for us?
  - Call to action or resolution: Here's what we do next. Here's what we recommend.

Different narrative types use these components differently.

1. Story Selection

With complex inputs, multiple stories are possible:

• The "everything is broken" story (lots of problems to fix)
  - The "things are working better" story (progress is real)
  - The "here's the hard choice" story (tradeoffs are real)
  - The "we're pivoting" story (direction is changing)
  - The "we're doubling down" story (we know what we're doing and it's working)

None of these is automatically true or false. All might be partially true. Your job is deciding

which story illuminates what your audience needs to understand.

1. Evidence Hierarchy

Different audiences need different evidence:

• Executives: High-level metrics, competitive context, financial impact, risk assessment
  - Team members: What changed, what it means for their work, what they should do
  - Customers: Value proposition, trust signals, why this matters for them
  - Board members: Governance, fiduciary risk, long-term positioning

Same narrative, different evidence emphasis.

1. Visual Thinking

Presentations are often more visual than written. Key ideas:

• Reduce cognitive load: One idea per slide, not ten
  - Emphasize over explain: Visuals should support your spoken words, not duplicate them
  - Hierarchy: Make important things visually prominent
  - Consistency: Similar ideas look similar; different ideas look different

AI can help you plan visual hierarchy; you decide what deserves prominence.

1. Rhetorical Choices

How you frame something shapes how it's received:

• Positive frame: "We've made 40% progress" vs. Negative frame: "60% still to go"
  - Urgency frame: "We need to move fast" vs. Steady frame: "We're building for long-term"
  - Opportunity frame: "This opens possibilities" vs. Risk frame: "This protects us from..."
  - Us frame: "We're all in this together" vs. Role frame: "Here's what different teams do"

Same underlying facts; different emphasis. Your job is choosing which framing is most honest

and most serves your purpose.

Practical Managerial Use Cases

1. Quarterly business review (synthesizing three months of data, metrics, learnings into a coherent

narrative for leadership or the company)

1. Strategic presentation (here's where we're going, why, and what it means--translated for different

audiences)

1. Problem diagnosis (we observed X problem; here's what we learned about why; here's what we recommend)
2. Progress report (here's what we said we'd do, here's what we actually did, here's what we learned)
3. Team update (here's what's happening in the company/department; here's what it means for our team)
4. Client briefing (here's your current situation, here's what we've done, here's the impact)
5. Resource request (we need more budget/headcount/time; here's the business case)
6. Executive summary (you have a complex situation; here's the essential framing in 2 pages)

Examples

Example 1: From Data Overload to Quarterly Business Review

Scenario: You've got six months of data--customer metrics, team metrics, revenue, churn, product releases,

hiring, market context. You need to create a 30-minute presentation for your CEO that tells the story of

your business this quarter.

The Input Chaos:

• 47 pages of raw metrics (CAC, LTV, churn, engagement, feature adoption)
  - 12 email threads about what customers are saying
  - 3 competitive analysis documents
  - 4 product releases with varying success
  - Hiring data (pipeline, offers, starts, retention)
  - Financial actuals vs. plan
  - Your own notes and thoughts

With AI--Smart Approach:

Prompt:

`

Help me synthesize a quarter of data into a coherent 30-minute executive presentation for our CEO.

Here's what happened this quarter (raw inputs):

I need help:

1. Identifying the 3-4 core story threads (not everything)
2. Suggesting what evidence matters most for each thread
3. Thinking about narrative structure (how do these threads relate?)
4. Suggesting different angles--what if we emphasize growth? Efficiency? Resilience?
5. Drafting an outline that would take 30 minutes to present

Questions I need answered:

• Are we on track overall, or is there meaningful deviation?
  - What's the biggest opportunity or risk emerging?
  - What should the CEO care most about?
  - What decision or direction shift might the CEO need to make?

`

AI produces:

`

Story threads identified:

1. Revenue growth slower than expected (but customer satisfaction up)
2. Product-market fit improving in segment B, unclear in segment A
3. Hiring pipeline strong, but retention at 90% (down from 95%)
4. Market volatility creating both opportunity and risk

Suggested narrative structure:

• Opening: "We're at an inflection point. Growth is solid, product-market fit is improving

in some areas, but we need to make a choice about where we double down."

• Thread 1: Growth isn't dramatically different from plan, but composition is. We're

retaining existing customers better; new customer acquisition is slower.

• Thread 2: Product investment is paying off in segment B. Segment A still searching.
  - Thread 3: Retention dip is concerning--market competition is real.
  - Implication: We're stronger in execution, but need to clarify strategy (go deep in B or

balance A and B?).

• Call to action: Decision on resource allocation for next quarter.

Evidence to include:

• CEO cares about: Strategic clarity, market position, unit economics
  - Key metrics: Revenue (with composition breakdown), churn (with segment analysis),

new vs. expand, CAC/LTV by segment, retention (with cohort analysis)

• One competitive insight (where are we vs. competition?)
  - Hiring/retention as capability story

Different angles:

1. Execution angle: "We've built the operating leverage to drive growth efficiently"
2. Strategic angle: "Product-market fit is clearer; time to choose our bet"
3. Risk angle: "Retention dip signals competitive pressure; we need to respond"

`

Now you craft your presentation:

Your outline (30 minutes):

Opening (2 min): "This quarter, we've clarified where we are and what we need to decide. Growth is

solid. Product-market fit is improving. But we're seeing early signals we need to respond to. Here's what

happened and what we're recommending."

Section 1 - Growth Story (8 min):

• Slide: Revenue vs. plan (we're close, slight miss)
  - Slide: Composition (breakdown by segment; tell the story: segment B is accelerating, segment A is

steady, new CAC is flat while expansion is strong)

• Insight: "We're better at keeping existing customers; harder on new acquisition"
  - Implication: Either we're becoming a land-and-expand business (good), or we need to rethink

new customer go-to-market (decision point)

Section 2 - Product/Market Fit (6 min):

• Slide: Product adoption by segment (B is 60%, A is 35%)
  - Slide: Churn by segment (B down, A up)
  - Insight: "Our product changes are working for segment B. Segment A wants something different."
  - Implication: We have a bet to make. Can't optimize for both.

Section 3 - People/Capability (5 min):

• Slide: Hiring pipeline and starts
  - Slide: Retention (90%, down from 95%)
  - Insight: "We're growing the team, but losing more experienced people to competition"
  - Implication: Compensation review? Clarity of direction? Both?

Section 4 - Market Context (4 min):

• Slide: Competitive positioning (one key insight about where you stand)
  - Insight: "Market is fractioning. Players are specializing. That helps us."

Closing (5 min):

• Call to action: "We need to decide: Do we commit to segment B as our primary market, or do we

split effort between A and B? This decision cascades to product, sales, and hiring. My recommendation:

Why this works:

• Reduces six months of complexity to three threads that matter
  - Evidence is selective, not exhaustive
  - Clear implication for each section
  - CEO gets what they need to decide
  - You made the editorial choice about story and recommendation

What you specifically did (that AI couldn't):

• Decided that segment differentiation was the story, not growth rate
  - Chose to frame the retention dip as a decision-point (competitive pressure) rather than a problem
  - Recommended a decision (commit to B) rather than safer middle-ground framing
  - Used your market knowledge to explain why the separation makes sense (market fractioning)

Example 2: Executive Summary From Complex Project Analysis

Scenario: Your team spent six weeks analyzing whether to acquire a smaller company. You have market

research, financials, tech assessment, cultural fit analysis, integration plans. The executive team needs

a 2-page summary to decide.

With AI:

Prompt:

`

I need a 2-page executive summary on an acquisition opportunity. The team has done extensive analysis.

Here's the situation (key findings from each area):

For the executive summary, I need:

1. Crystal clear recommendation (yes, no, or conditional)
2. The 3 strongest reasons to do it
3. The 2 biggest risks
4. The one key question the execs should ask before deciding
5. A timeline/process for next steps

Help me structure this so it's persuasive but honest about tradeoffs.

`

AI structures:

`

Recommendation: Acquire, contingent on [specific condition--price, integration plan clarity, talent

retention].

Top 3 reasons:

1. Market position (fills a gap in our offering, gives us entry to segment X)
2. Technical assets (their IP reduces our development timeline by 12 months)
3. Team (8 of their 12 engineers are A-players we want to retain)

Biggest risks:

1. Integration complexity (their tech stack is different; integration is not trivial, ~6 months, ~$500K)
2. Cultural mismatch (they're bootstrapped startup; we're scaled company; could lose good people)

Key question: Can we retain their engineering team post-acquisition? If yes, ROI case is strong. If

we lose them, economics don't work.

Next steps:

1. Counter-offer + retention agreements with their key people (1 week)
2. Integration planning + detailed timeline (2 weeks)
3. Final decision point (end of month)

`

You write the 2-page summary:

Page 1:

• The Opportunity: Brief description of what they do, why it matters
  - Our Recommendation: Acquire, pending successful retention discussions with their engineering team
  - The Business Case: Markets impact (segment entry), technical benefit (12-month timeline reduction),

team capability

• Financial Summary: Purchase price, integration cost, expected payback (X years, Y% ROI)

Page 2:

• Critical Success Factors: What has to be true for this to work (team retention, successful integration)
  - Risks & Mitigation: Integration complexity (plan underway), culture (retention focus), market

(contingent on market assumptions)

• Timeline: Retention discussions (1 week), integration planning (2 weeks), decision (end of month)
  - For Discussion: What questions do we need answered before committing?

What AI couldn't do:

• Decide whether the "cultural mismatch" is a blocker or manageable (you know your culture better)
  - Determine if the market timing is actually right (you understand your strategy)
  - Weigh whether 12-month timeline savings is worth the integration cost (judgment call)
  - Know whether the retention conversation is realistic or just hope

Example 3: Translating Complex Data Into a Team Update

Scenario: Your company just announced a major strategic shift (moving from product X into new market Y).

Your team needs to understand what this means. The announcement is clear to execs (market opportunity is

big, existing product is declining). Your team is worried (will my role change? Are we hiring or cutting?).

With AI--Smart Approach:

Prompt:

`

Our company just announced a strategic shift from product X to market Y. The exec announcement focused

on market opportunity and business case. My team is confused about what this means for them. Help me

think through:

1. What are the layers of understanding they need?

• What's actually changing (scope, timeline, investment)
  - What's staying the same (their current work for X more weeks/months)
  - What's uncertain (will roles change? Timeline? Headcount?)

1. What are they likely worried about?

• Job security
  - Whether their skills are still relevant
  - Timeline (when does this actually affect them?)
  - Clarity (is this definitely happening or still being discussed?)

1. How do I frame this so they understand the business case but don't panic?
2. What specific commitments can I make to them about how they'll be supported?

`

AI surfaces:

`

Layers of understanding:

• Immediate (next 30 days): Business continues, we finish what we started on product X
  - Near-term (next quarter): We start hiring/allocating to new market Y work
  - Medium-term (next 6 months): Product X gets less investment; Y gets more
  - Longer-term: Product X may sunset

Likely concerns:

in Y, so we need skills for Y. We'll help you build those if you want to move, or we'll help you

find something if you don't."

• "When does this affect me?" -> Timeline clarity: "No immediate change. Current work continues.

Starting next quarter, we're building capacity in Y."

• "Is my role changing?" -> "Not immediately. Eventually, probably. We'll talk about what

makes sense for your growth."

Framing:

• Lead with honesty: "This is a big shift."
  - Explain why: "Market Y is 10x bigger than where X is going. This is where we can build something significant."
  - Name what's real: "This will change how we invest time and resources. It will create new opportunities."
  - Address the concern directly: "I get that this feels uncertain. Here's what I'm certain about:

I want to keep you, I want to help you succeed in whatever this looks like, and I'll be straight

with you about what's happening as I know it."

Commitments:

• Timeline clarity (when does it affect their work, when is a decision point)
  - Support (training, coaching, honest conversation about whether Y role appeals to them)
  - No surprises (you'll know what's happening when I know)

`

You plan your team meeting:

Opening: "The company announced a pretty significant strategic shift this week. I want to walk you

through what it means, and more importantly, what it means for you."

The Business Case (brief): "Here's why: Market Y is 10x bigger than where product X is heading. There's

a real opportunity here. We're making a bet that we can build something significant there."

What's Changing:

• Investment allocation: Starting next quarter, we're hiring for Y, reducing X investment
  - Timeline: It's not immediate. Your current work continues. But over the next 6 months, the split changes.
  - Long-term: X probably winds down; Y is where the company goes

What's Stable:

• Your job through this quarter and next: Your current work continues, no interruption
  - Your role through Q2: Not changing
  - Your value: The skills you have, the things you're good at, those matter more than ever

What's Uncertain (and honest about it):

• Longer-term role fit: I can't promise your exact role exists in a Y-focused company. But that doesn't

mean there's no role for you.

• Timeline: This isn't overnight. We have time to figure this out.

What You Can Expect From Me:

• Transparency: You'll know what's happening as I know it. No surprises.
  - Support: If you want to build skills for Y work, I'll support that. If you decide this isn't for you,

I'll help you find something that is.

• Honesty: If I see a role that's a natural fit for you, I'll advocate for it. If I see it being tough,

I'll tell you that too.

What I'm Asking:

• Stay engaged. This is a real opportunity.
  - Ask questions. Be honest about what you're worried about.
  - Over next month, we'll talk individually about what this means for you specifically.

Closing: "I know this creates some uncertainty, and I want to acknowledge that. I'm confident we're

making the right bet. And I'm committed to making sure you're set up to succeed in whatever that looks like."

Why this works:

• Honest about the shift
  - Clear about what's changing, stable, uncertain
  - Addresses fears directly (job security, timeline, support)
  - Makes realistic commitments (you'll be straight, you'll support their growth, no surprises)
  - Invites conversation (not a one-way pronouncement)

Anti-Patterns & Misuse Risks

1. Letting AI Choose Your Narrative

Risk: AI suggests a compelling story, and you run with it without asking if it's the true story.

Example: AI structures "We've overcome adversity and emerged stronger" when the real story is "We

made mistakes but learned." The first sounds better; the second is more honest.

Mitigation: Ask yourself: Is this the story I actually believe? Or is this a more persuasive fiction?

1. Over-Simplifying for Clarity

Risk: You reduce complexity so much that you lose important nuance.

Example: "We're pivoting to Y" makes it sound simpler than it is. The truth is more like "We're

investing heavily in Y while sustaining X; they'll diverge over time."

Mitigation: Clarity is good. Oversimplification is bad. Find the level of nuance that's honest.

1. Leading With Your Recommendation Instead of Evidence

Risk: You structure the narrative to convince people to your conclusion, rather than to help them

understand and decide.

Example: You present evidence only for the acquisition, not against it.

Mitigation: Present the case fairly. Then make your recommendation. Let people see your reasoning.

1. Ignoring Dissenting Views

Risk: Your narrative omits perspectives or data that complicate the story.

Example: You present strong quarter growth but never mention the retention dip.

Mitigation: Strong narratives include tradeoffs and complexity, not false clarity.

1. Confusing Emphasis With Dishonesty

Risk: You frame things so positively that they obscure reality.

Example: "We've reduced headcount by 15%" sounds very different from "We laid off 15% of the company,"

even though it's the same thing.

Mitigation: Positive framing is fine. Dishonesty isn't. Ask yourself: Would someone with a different

perspective see this as misleading?

1. AI's Emphasis Doesn't Match Your Judgment

Risk: AI emphasizes something that feels important to your synthesis but not to your organization.

Example: AI structures the narrative around "we're building team resilience," but your organization

cares about "we're shipping faster." Same story, wrong emphasis.

Mitigation: Adapt AI suggestions to match what actually matters to your audience.

Human Judgment Checkpoints

Critical moments where you override or adapt:

1. Story selection: Multiple stories are possible. Is the one AI suggests the most important one?

Or is there a bigger story?

1. Narrative honesty: Does the structure tell the full truth? What's being left out or de-emphasized?

Should it be?

1. Evidence hierarchy: Is the supporting evidence what your audience actually cares about? Or does

AI's suggestion miss your organization's actual priorities?

1. Tone and confidence: Should this narrative be optimistic, cautious, or urgent? Does AI's

framing match what the moment actually calls for?

1. Action clarity: Will your audience know what they're supposed to do with this information?

Or does the narrative leave that hanging?

1. Audience fit: Does this presentation actually work for this audience? Or is it generic?
2. Authenticity check: Does this feel like your thinking? Or does it sound like a presentation

consultant wrote it?

Responsible AI Considerations

1. Honesty in Narrative Selection

The risk: You choose a narrative that serves your agenda rather than illuminates truth.

Your practice:

• Multiple narratives can be true. Choose the one that's most important for understanding.
  - Be honest about what story you're telling and what you're de-emphasizing.
  - If your boss asks "Is there another way to look at this?" you should be able to give them the

tradeoff answer.

1. Protecting Against Narrative Bias

The risk: AI learns from existing presentations, which may reflect organizational biases or outdated

ways of thinking.

Your practice:

• Challenge AI's suggestions if they feel status-quo or conventional.
  - Ask: "What if we told this story differently?" Generate multiple narratives.
  - Notice if the narrative advantages one group or perspective. Is that accurate?

1. Respecting Complexity

The risk: You oversimplify for narrative cohesion, losing important nuance.

Your practice:

• Clarity is good. Oversimplification is bad.
  - The narrative doesn't have to be one thread. It can be "here's the good, here's the bad, here's

what we're deciding."

• Don't let the need for a clean story prevent you from acknowledging real complexity.

1. Transparency About What's Not Included

The risk: Your narrative is complete and coherent, but it omits things that matter.

Your practice:

• If you're not including dissenting views, acknowledge that choice.
  - If there's uncertainty you're not surfacing, that's a risky omission.
  - Strong presentations often start with "Here's what I'm focusing on, and here's what's outside the scope."

Practice & Reflection Prompts

1. Pick a complex situation in your organization (a quarter, a project, a strategic question).

Gather the raw inputs. Use AI to help you identify possible narratives. Then: which story is most

important? Why?

1. Presentation stress test: Take a presentation you've given recently. Read it for what it emphasizes

vs. what it omits. What story is it telling? Is there a different, more honest story?

1. Multiple narratives exercise: For a decision or situation, generate 3-4 different narratives

using AI. Which one is most true? Which one would your skeptics tell? How do you reconcile them?

1. Audience translation: Take a complex idea. Explain it to an executive (2 minutes, focus on

business impact). Explain it to your team (5 minutes, focus on what it means for them). Explain it

to a customer (3 minutes, focus on value). Notice how the narrative shifts.

1. Authenticity check: Record yourself giving a presentation or watch yourself via video. Does it

sound like you? Or does it sound like a presentation? Adjust.

Key Takeaways

• Multiple narratives are possible. Your job is choosing the one that's most true and most important,

not the most persuasive.

• Simplicity serves clarity, not truth. Don't oversimplify. The narrative should be clear and honest.
  - Evidence matters more than rhetoric. Strong presentations are built on evidence that your audience

understands the situation, not on eloquence.

• Different audiences need different evidence. Same narrative, different emphasis. Serve what each

group needs to understand.

• Your voice matters. If the presentation doesn't sound like you, rewrite it. Authenticity is

more persuasive than polish.

• Transparency about limits. Strong presentations often acknowledge uncertainty, tradeoffs, or

dissenting views. That builds trust.

• The call to action should be clear. By the end, your audience should know what you're asking

them to do (decide, approve, understand, support, etc.).

Terms & Glossary Items

• Narrative structure: The logical flow of a presentation--opening, problem, evidence, insight,

implication, action.

• Story selection: Choosing which threads are essential from complex inputs; editing ruthlessly

for clarity and impact.

• Evidence hierarchy: Organizing supporting information so that the most important evidence is

prominent and clear.

• Rhetorical framing: How you choose to present facts (positive vs. negative, urgent vs. steady,

opportunity vs. risk) to shape understanding.

• Narrative thread: A consistent theme that runs through the presentation, connecting different

pieces of evidence.

• Turning point: The moment in a presentation where the listener's understanding shifts (usually

the insight or implication).

• Call to action: The clear ask at the end--what you need your audience to do with this understanding.

Related Lessons

• Lesson 1.1: Complex Stakeholder Communications -- Narrative is communication; these skills pair
  - Lesson 1.4: Written Communication Excellence -- Similar principles apply to written synthesis
  - Lesson 2.1: Structuring Complex Decisions -- Decision frameworks share structure with presentations
  - Lesson 2.3: Evidence Gathering and Synthesis -- Where presentations start (gathering and synthesizing

evidence)

[SYNTHESIS AND APPLICATION]

Let us step back and look at the bigger picture of what we have covered in this session on Presentation and Narrative Building.

The concepts here are not abstract frameworks meant to sit in a binder on your shelf. They are practical tools for the decisions you make every day as a manager. Whether you are leading a small team or a large department, whether you work in technology, finance, healthcare, education, or any other sector, the principles we discussed apply to your work right now.

Here is what I want you to take away from this session:

First, the conceptual understanding. You now have a clearer mental model of presentation and narrative building and how it fits into the broader landscape of AI-augmented management. This mental model is what allows you to make good decisions rather than reactive ones.

Second, the practical application. We walked through specific scenarios, examples, and frameworks that you can apply in your work this week. Not next quarter. This week. I want you to identify one specific situation in your current work where you can apply what we discussed today.

Third, the judgment dimension. Perhaps most importantly, we discussed when and how to exercise human judgment. AI is a powerful tool, but it requires an informed, thoughtful manager at the helm. That is you. Your judgment, your context awareness, your understanding of your team and your organization, those are irreplaceable.

[REFLECTION EXERCISE]

Before we close, I would like you to spend two minutes, just two minutes, on this reflection:

Think about your work this past week. Identify one task, one decision, one communication where the concepts from today's lesson would have changed your approach. What would you have done differently? What would the outcome have been?

Write that down. That connection between concept and practice is where real learning happens.

[CLOSING REMARKS]

In our next lesson, we will explore Written Communication Excellence, which builds directly on what we have covered today. I would encourage you to complete the reflection exercises before moving on, as they will prepare you for the next set of concepts.

This has been Lesson 1.3: Presentation and Narrative Building, part of the Independent Communication Workflows module in Level 3: Independent AI Application of the AI for Managers certification.

Remember: the goal is not to know more about AI. The goal is to be a better manager because of how you use AI. Those are very different things, and this program is designed for the latter.

Thank you for your time, your attention, and your commitment to growing as a leader in an AI-transformed workplace. I look forward to our next session together.

END OF TRANSCRIPT

AI for Managers Certification Program

Level 3: Independent AI Application | Independent Communication Workflows | Lesson 1.3

A SkillsClinic initiative by No Worker Left Behind and The Work Company.

Duration: ~27 minutes | Word Count: ~4194