"I'm not sure AI is really relevant for our industry."

This sentence sends shivers down my spine. I hear it at least once a week from executives who genuinely believe their industry is somehow immune to the AI transformation sweeping through every sector of the economy.

Often these people when asked will acknowledge AI is about to change everything. For everyone. Just not, you know, their specific situation. Ha!

We all think we are special, unique and not like anyone else. Yeah…about that….

There isn't a single industry that won't be fundamentally changed by AI in the next 5-10 years. Not one.

Sure, some physical roles have some leeway. But when robotics starts to catch up and has its ChatGPT moment? We’re going to see the same impact.

The question isn't if AI will impact your industry—it's how quickly, how deeply, and whether you'll be leading that change or scrambling to catch up.

That’s the realisation we need the executives to come to.

Remember in Part 2, we established our three-act structure for executive briefings:

• Act 1: Why AI Matters to This Specific Business

• Act 2: One Concrete Example With Real-World Impact

• Act 3: Clear, Actionable Next Steps

In this Part we're focusing entirely on Act 1—crafting a compelling business case that makes executives sit up and take notice.

This is where you establish the foundation for everything that follows. Get this wrong, and it doesn't matter how brilliant your example is or how clear your next steps are—the executive has already mentally checked out and are thinking about what to have for lunch.

Let's get started:

The Carrot and Stick: Opportunities and Threats

The most effective business case for AI combines both opportunities (the carrot) and threats (the stick). It's human nature to respond to both gain and loss motivations, but in different ways.

Most executives are actually more motivated by preventing losses than by achieving equivalent gains—a psychological principle known as loss aversion.

Why is this? Well…they are at the top already. They now need to protect what they’ve earned.

If they were young and hungry then opportunity (even with risk) is attractive. But when you are within spitting distance of retirement your only goal is to guide the boat in without sinking it.

Here's how to structure this part of your briefing:

Start with the Opportunity (The Carrot)

Begin with the positive vision because it creates openness and enthusiasm. We don’t want to go in with doom and gloom because it’s a grim way to start a talk! Focus on specific, tangible benefits for their business.

Get some actual data here (use a research model to find case studies and articles) to show what others are doing and some of their successes. These don’t have to be from your industry specifically but if they are you can pivot into the threat very neatly.

Then Introduce the Threat (The Stick)

After establishing the opportunity, introduce the competitive threat:

• Disruption risk: "Traditional industry leaders who delay AI adoption are being leapfrogged by more agile competitors"

• Cost disadvantage: "Companies without AI automation are facing a growing cost structure disadvantage—averaging 30% higher operational costs"

• Talent exodus: "Organisations seen as technology laggards are losing their best talent to more innovative competitors"

• Existential risk: "In similar industries, companies that delayed AI implementation for just 2-3 years found themselves unable to catch up"

Again, you want to find real facts and figures here. You need ONE good data point to start. Don’t worry about providing a sheet of references - we want one focused, powerful point.

The balance between opportunity and threat should be calibrated to the executive's personality and corporate culture. Some respond better to opportunity, others to threat. Read the room and adjust accordingly.

You’ll also need to adjust your language so it doesn’t sound like you are directly criticising their leadership. This’ll end the meeting pretty quickly! Instead talk about other companies who aren’t investing in AI - maybe even in other (related) industries. Use these parallel examples so as not to offend but also making it clear this could happen in their company.

Finding Industry-Specific Evidence

Generic AI statistics are a dime a dozen. What executives need is evidence specific to their industry, company size, and situation. Here's how to find it:

Industry Research Reports

Analyst firms like Gartner, Forrester, McKinsey, and Deloitte regularly publish industry-specific AI impact reports. These carry credibility with executives. Stick to big names and you can immediately borrow authority.

Example: "According to McKinsey's 2025 Industry Digitisation Report, insurance companies implementing AI-powered claims processing are reducing cycle times by 70% while improving accuracy by 30%."

Right there you are hijacking McKinsey’s authority. You didn’t do the study. You don’t need to. But you’re hopping onto McKinsey’s names and using it to immediately secure credibility.

How to find these reports? Use an AI research model.

Competitive Intelligence

Sneaky one but this works amazingly well.

Nothing motivates executives like learning what their competitors are doing. Research competitors' AI initiatives through:

• Press releases and annual reports

• LinkedIn posts from their employees

• Industry conference presentations

• Tech vendor case studies

Example: "Your competitor XYZ launched an AI customer service platform last quarter and is publicly claiming a 40% reduction in resolution times."

The simplest way to start finding this is Googling the competitor’s name + AI and see what turns up.

Case Studies from Analogous Industries

If direct examples in their industry are limited, look for parallels in adjacent sectors:

Example: "While AI adoption in commercial real estate is just beginning, the residential sector has seen property management companies reduce maintenance costs by 35% using AI-powered predictive maintenance. There’s an opportunity here to be the first in commercial real estate gaining these savings."

If there aren’t many case studies in the specific industry this is actually a good hook for you to use. You can posit this as an opportunity for the executives you are talking to to spearhead AI adoption in the industry. Think of the plaudits, the industry paper write ups, the awards, the fancy galas? That’s the image you want to embed.

For all of these we can use a research AI to help us gather up information. This prompt will help you gather industry-specific evidence:

You are an AI research assistant helping me prepare for an executive briefing on AI adoption. Please help me find industry-specific evidence about AI impacts in the following sector:

Industry: [Specify industry]
Company size/segment: [SMB, Mid-market, Enterprise]
Geographic focus: [Optional - specify region]

Please provide:
1. 3-5 specific data points about how AI is creating competitive advantage in this industry (with sources if available)
2. 2-3 examples of leading companies in this space implementing AI (what they're doing and results)
3. 2-3 examples of companies that delayed AI adoption and faced negative consequences
4. Key industry-specific metrics that executives in this field typically care about and how AI impacts them

Focus on concrete business outcomes rather than technical implementations.

With research AIs in particular make sure you go back and check the sources. We need them to be watertight. You don’t need many - but you do need them to be good. So take the extra time to confirm everything the model digs up.

Addressing the Emotional Barriers

Beyond rational concerns, executives have emotional barriers that often go unspoken but significantly influence decisions. Now, they won’t necessarily express these (in so many words) so you need to be on the lookout for language that gives away what they are feeling.

Fear of Personal Obsolescence : "If AI can do strategic thinking, what's my role as an executive?"

Solution: "AI processes data but lacks judgment and leadership. The best executives will use AI to focus on truly strategic decisions that require human wisdom. If anything your jobs are the safest right now."

Fear of Looking Foolish: "What if I champion AI and it fails?”

Solution: "Start with small, contained wins before broader rollout. This protects your credibility while positioning you as forward-thinking. Position the projects as experiments from the start."

Impostor Syndrome Around Technology : "Everyone seems to understand this AI stuff. I don't want to reveal how little I know."

Solution: "Many executives feel this way. And the good thing is it doesn’t really matter. Do you know the ins-and-outs of how the internet works? Probably not - and we don’t need to. Implementation doesn't require technical expertise—it requires business judgment about where to apply AI. That’s what you bring."

Fear of Cultural Resistance: "If I push this and the team resists, I'll be blamed for the disruption."

Solution: "Involve employees in identifying opportunities. In fact I recommend as a next step a staff-led workshop for exactly this reason. When people see AI as making their work more valuable rather than threatening their jobs, resistance transforms into enthusiasm."

Remember, executives rarely make purely rational decisions. As Johnathan Haidt writes they instead make human decisions influenced by emotions, then justify them with data. Address both for the most compelling case.

Putting It All Together: Your Act 1 Framework

Here's a framework for structuring the "Why AI Matters" portion of your briefing:

1. Industry Context

• Current state of AI adoption in their industry

• Key competitive dynamics being shaped by AI

• Specific challenges AI is uniquely positioned to address

2. Opportunity Overview

• 3 key areas where AI creates value in their specific business

• Concrete metrics and outcomes from industry examples

• Timeline for realising these benefits

3. Risk of Inaction

• Competitive consequences of delayed adoption

• Cost and efficiency disadvantages

• Potential strategic limitations

4. Addressing Key Concerns

• Proactively tackle the specific objections you anticipate

• Demonstrate empathy and understanding of legitimate concerns

• Pivot to how these challenges can be mitigated

5. Transition to Concrete Example

• Bridge to your Act 2 by saying something like: "Let me show you exactly what this looks like in practice with a specific example relevant to your business..."

Adapt this to different time constraints. In a 5-minute pitch, you might compress Act 1 to just 1-2 minutes. In a 30-minute presentation, you could expand it to 7-8 minutes with more detailed examples. But the basic thrust remains the same.

Generate Your Act 1

Use this prompt to generate a first draft for Act 1”

You are an AI consultant preparing the "Why AI Matters" section of an executive briefing. Create a compelling business case for AI adoption in the following context:

Industry: [Specify industry]
Company size: [SMB, Mid-market, Enterprise]
Current AI maturity: [Early, Mid, Advanced]
Key executive concerns: [List any specific concerns/priorities]

Please provide:
1. An industry context overview (2-3 paragraphs)
2. Three specific opportunity areas with concrete metrics and examples
3. Two key risks of delayed adoption with supporting evidence
4. Preemptive responses to the most common objections in this industry
5. A smooth transition to introducing a specific example

Format this as a script I could potentially deliver in about 5 minutes. Use persuasive but factual language appropriate for senior executives. Include 2-3 compelling statistics or data points with sources if available.

What's Next?

In Part 4, we'll dive into Act 2 of your executive briefing: creating a killer example.

You'll learn how to select, develop, and present a compelling use case that makes the abstract more real and convinces executives that AI implementation is actually doable.