TL;DR

AI has raised the floor for everyone. Competent marketing is no longer a differentiator — it’s the baseline. What fills the gap when there’s no governing standard isn’t brilliance. It’s average. I call this the sameness tax, and it has real costs. This piece names those costs — and what it takes to stop paying them.

I recently went on a road trip with a few not-to-be-named travel companions (well, I’ll name one, my dog Zoey). We were using Grok to find a Starbucks along our route — nothing fancy, just a quick voice search to locate caffeine before we started losing our minds — when the whole thing went sideways. Everyone started talking at once, Grok got confused, and one of my fellow roadies went into a full-on rant about artificial intelligence. Not the navigation fail. AI. All of it. The existential threat, the jobs, the future of humanity.

Let me be clear. I love this person. They are smart, philosophical, and fun to hang out with. I also like to get their POV on tough issues because they think seriously about things most people wave off. But, at 8 AM, on a highway to nowhere, the last thing I wanted to do was debate the perils of AI (despite the dystopian scene outside our windshield). In fact, as far as I was concerned, Grok was exactly the right tool for the time and place, and I was thrilled to have access to it.

I let it go. Everyone else did too. Coffee was indeed our top priority.

The conversation, however, stuck with me — not because this person was wrong to think critically about AI, but because I believe the love it / hate it binary is entirely the wrong conversation to be having. Both positions require taking a stand on what AI could be without asking the more useful question: what actually is AI right now and what are the frameworks in which we are comfortable using it?

My understanding is that the chat interfaces we all have access to — Claude, ChatGPT, Grok, Gemini — don’t think. What they actually do is much simpler. They are prediction models. Sophisticated ones, yes, but prediction models nonetheless — systems trained to generate the most statistically likely response based on patterns in everything they’ve ever been fed.

Andrej Karpathy, one of the original architects of modern AI, describes it plainly: LLMs are engines of “next token prediction” at massive scale. They don’t reason, they don’t understand, they don’t decide.¹

This means the quality of what comes out is almost entirely determined by what you put in. Not just your prompt, but your thinking, your phrasing, your clarity (or lack thereof), and your governing standard.

And the confidence these chatbots exude is exactly what makes them dangerous. Without a clear POV, defined brand voice, and a filter for what you will and won’t do, AI doesn’t fill the gap with brilliance. It fills it with average. Assumptions based on the most common denominator. Ew.

Which brings us to what that’s actually costing you.

I call it the sameness tax. And it’s more expensive than most people realize.

Here’s what’s happening: AI has made competent marketing accessible to everyone. The floor has risen. But the ceiling — the work that actually gets someone to pay attention and engage, that sounds like a specific human with a specific POV — has gotten harder to reach, not easier.

And that gap has a cost. Several, actually:

• Time. Without setting a governing standard, every AI session becomes a negotiation. Every piece of content starts from scratch. You’re not creating — you’re arbitrating between what the tool thinks and what your gut knows isn’t right. Research backs this up: In 2026, the number one reason marketing organizations are not scaling AI is… (drum roll please) governance.²

• Credibility. Every time you let AI fill a gap you haven’t defined, you’re outsourcing your POV to a probability engine. Your audience feels the disconnect even when they can’t name it. Messaging that could have come from anyone tells the reader zero about you or your business.

• Voice. Your voice is the thing that makes you recognizable and worth engaging with. It’s also the first thing that erodes — one compromised output at a time — when you operate without a standard, and eventually the thread of what you stand for is lost.

• Opportunity. This is the cost that’s hardest to see because it’s invisible by definition. The right client who never engaged because nothing distinguished you. The referral that didn’t happen because nobody could quite articulate what makes you different. You don’t see this tax on a spreadsheet. You feel it in the pipeline.

The data makes the stakes impossible to ignore: Over 70% of marketers have already encountered an AI-related incident — inaccurate, irrelevant, off-brand, or generally non-compliant messaging that missed the mark entirely.³

That’s the sameness tax in action. It results in the kind of slop that makes people avoid using AI. And the frustrating part is it’s entirely self-imposed.

If you're new here: I drop a Purpose Play into most of my posts. You should think of it as a brief pause where I ask you to take the idea off the page and hold it up against your own work. Regular readers, you know the drill.

Purpose Play

Take a look at the last three pieces of content you published — a webpage, an email, a post, a caption, whatever form your marketing takes.

For each one, ask yourself: did I know exactly why I was creating it, who it was for, and what I wanted it to communicate? And, did I review the final output, before I hit publish, to make sure it fit the brief or just accept what I was given.

There’s no wrong answer. But the gap between intentional and good enough is exactly where the sameness tax lives.

I’ll be honest: I’ve sat in the middle of this issue myself. Not just philosophically, but practically: wondering whether AI is making my work better or worse. Whether it’s a threat or a shortcut. Whether I should lean in or hold back.

My POV however is that this debate, just like the one about Grok, kept me stuck circling the wrong questions.

Once I got clear on that, the next steps were easy. I defined my POV, set real voice standards, and built a decision filter — a set of constraints that tells me, and every tool I use, what belongs and what doesn’t. In other words, I stopped treating AI like an omnipotent god and started treating it like a paid employee.

That’s the shift. Not searching for a better tool. Not creating a smarter prompt. Just finding a clear answer to the question technology can’t answer for you: what does your brand actually stand for, and what does that sound like?

When you define that first, everything else follows. AI becomes useful instead of argumentative. Your content starts to compound instead of evaporate. The sameness tax stops being something that quietly accumulates in your pipeline.

Sources

¹ Andrej Karpathy, “Deep Dive into LLMs like ChatGPT,” YouTube, February 2025.

² Jasper. (2026). The State of AI in Marketing 2026. “Core Challenge: Governance is the main bottleneck to scale.”

³ Koch, J. & Pellatt, C. (August 2025). AI Adoption Is Surging in Advertising, but is the Industry Prepared for Responsible AI?, IAB / Aymara

About the Work

I’m Amy Zwagerman—brand strategist, fractional CMO, and founder of The Launch Box. I work with founders and marketing leaders to translate durable marketing principles into strategies and systems that fit their specific context, stage, and goals.

Marketing Jam sits alongside my client work as a place to explore ideas more openly. If the thinking here resonates and you’re curious about working together, you can learn more about my services or get in touch here.

AI-supported, human-led. All ideas and insights are my own. Curious how I use AI and where I draw the line? See my AI Disclosure Policy →

Integrity Pledge 🙋🏻‍♀️: The books, newsletters, shows, podcasts, and client work shared here are 100% reflective of my world. I will always disclose if and when I have a relationship with a brand I mention in a post or am sharing an affiliate link.

TL;DR

AI defaults to the statistical average of everything it's seen. Without brand strategy as a constraint, it will optimize for what's probable — not what's distinctive. The fix isn't a better prompt or tool. It's moving your brand controls upstream, before AI ever touches the work.

The Problem Everyone’s Talking About

You’re using AI to write marketing copy—emails, social posts, landing pages, campaign messaging. It’s fast. It’s grammatically correct. But when you read it back, something’s off. It feels… flat. Generic. Like it could’ve come from any of your competitors.

You tweak the prompt. You add more detail. You try a different model. Same problem. The output is fine. It’s just not you.

Most people assume the issue is the tool. “ChatGPT isn’t good at brand voice.” “I need better prompts.” “Maybe I should try Claude instead.” But AI isn’t the issue. The issue is treating AI like it replaces the process instead of what it actually is: a new creative partner in an old architecture.

The inputs haven’t changed. The architecture has. And if you’re skipping the first step—defining what makes your brand distinct—AI will default to what makes you average.

Why AI Defaults to Generic

AI was built to be helpful, responsive, and resourceful. Its job is simple: predict the next most likely word (or “token”) based on everything it’s seen before.

Ethan Mollick, a Wharton professor and one of the clearest thinkers on how AI actually works, puts it bluntly:

This isn’t a flaw. It’s how the system works.

AI models are trained on massive datasets scraped from the public internet—articles, blog posts, marketing materials, social media, forums, everything. This gives AI access to patterns in human language at enormous scale.

The good news: AI has learned the structure of human thought and communication. It can mimic tone, style, format, and context remarkably well.

The catch: It’s also learned the structure of marketing copy, and it optimizes for what’s most probable, not what’s most distinctive.

AI is designed to be agreeable. It wants to give you an answer even if it doesn’t have the full context. So when you ask it to “write a blog post about X,” it’s pulling from thousands of similar blog posts. The result? You get the statistical average of all of them. Safe language. Industry buzzwords. Vague value props (“we help you succeed,” “innovative solutions,” “best-in-class”).

AI also doesn’t know your brand unless you teach it. If you haven’t defined what makes you different—your positioning, your voice, your non-negotiables—it will default to what makes you the same.

What "Good" AI Output Requires

The marketing teams getting sharp, on-brand AI outputs aren’t using better tools. They’re using better inputs.

Governance is now the #1 barrier to scaling AI—not capability, not access, but the lack of clear constraints. But here’s what’s interesting: high-performing teams don’t see governance as a bottleneck. They see it as the unlock. ²

What high-performing teams are doing differently:

• They anchor AI to brand voice guidelines (pre-approved tone, language, positioning)

• They use claims libraries (messaging that’s already been vetted and reflects their POV)

• They treat brand strategy as the governance layer—the filter that tells AI what’s on-brand and what’s off-limits

The bottom line: Brand strategy isn’t decoration. It’s the thing that keeps AI from defaulting to the marketplace average.

How to Use Brand Strategy as AI Governance

When I started integrating AI into my writing workflow, I didn’t just start prompting and hope for the best (well, maybe I did, but I’ve come a long way since then). I treated it like architecture and built a system that would compound over time.

Here’s my process:

• Step 1: Defined Writing Style: I used AI to analyze samples of my writing and identify patterns—sentence structure, rhythm, vocabulary, tone. This wasn’t about having AI “write like me.” It was about establishing a baseline so I could teach AI to recognize what my voice actually sounds like.

• Step 2: Created a Copywriting Partner: I built a custom GPT governed by my brand strategy and writing style. This GPT serves as my creative writing partner. It acts as a collaborative copywriter that frames my ideas within the constraints I’ve defined. I refine this GPT regularly as my voice evolves.

• Step 3: Added a Review Layer: I created a second editorial GPT. This one has different parameters than the copywriting partner: optimize for length targets, manage cognitive load, and maintain tonal consistency. It pressure-tests drafts to make sure they’re sharp (I’ll admit it—I tend to write long and need the help).

• Step 4: Mapped the Workflow: I took a giant step back and outlined the actual writing process that evolved from this work—ideation, outlining, drafting, refining, editing, and posting—and identified where AI does and doesn’t add value. Then I updated the entire system based on what I learned.

Psst → My Step 4 should actually be your Step 1. Like I noted earlier, I’ve come a long way since AI first came on the scene.

In the end, AI doesn’t write for me. It works with me. And because I built the architecture first—defining the brand strategy, the voice, the constraints—the output is distinctly mine, not generic.

My Writing Workflow: Before and After AI

The architecture of my writing process hasn't changed. I am still the person responsible for creating a post (even when I give myself different job titles). I have however made AI a creative partner that helps me execute the work — faster, iteratively, and within my constraints.

What This Means for How you Build

If you’re serious about using AI in your marketing workflows, brand strategy can’t be an afterthought. It has to come first.

The most advanced marketing teams have moved beyond experimentation into what Jasper calls an “operational era”—the point where guardrails, controls, and policies live inside the system itself. When brand strategy is embedded as governance, trust becomes the default. Teams don’t have to slow down to ask, “Is this OK?” They can move fast because the filter is built in. ²

Everyone has access to the same AI tools. The differentiator isn’t who uses AI. It’s who uses it with intention—because they know what they’re protecting.

I like to include what I call Purpose Plays in my posts. You should think of them as brief breaks in the story for you to reflect on how the themes being presented align (or not) with what you're actually building.

Purpose Play

Think about the last time you used AI to create brand copy. How many rounds did it take you to get something usable? What were you correcting for—clarity, or fit? Do you think you could have avoided the issue by providing your brand constraints up front?

If your outputs feel generic, don’t blame the tool. Ask yourself: have I actually defined what makes my brand different? Or am I hoping AI will figure it out for me?

Build the filter first. Then let AI work within it.

Sources

¹ Mollick, E. (2024). Co-Intelligence: Living and Working with AI. Portfolio.

² Jasper (2026). The State of AI in Marketing 2026.

About the Work

I’m Amy Zwagerman—brand strategist, fractional CMO, and founder of The Launch Box. I work with founders and marketing leaders to translate durable marketing principles into strategies and systems that fit their specific context, stage, and goals.

Marketing Jam sits alongside my client work as a place to explore ideas more openly. If the thinking here resonates and you’re curious about working together, you can learn more about my services or get in touch here.

AI-supported, human-led. All ideas and insights are my own. Curious how I use AI and where I draw the line? See my AI Disclosure Policy →

Integrity Pledge 🙋🏻‍♀️: The books, newsletters, shows, podcasts, and client work shared here are 100% reflective of my world. I will always disclose if and when I have a relationship with a brand I mention in a post or am sharing an affiliate link.

TL;DR

We’ve all been on the receiving end of it — the sales pitch that comes too fast… from someone we don’t know… asking for a level of trust they haven’t earned. It doesn’t feel like pressure. It feels like a violation.

Scarcity, deadlines, and fear-forward framing are popular sales strategies for a reason: they work. But, here’s the catch, they don’t work without credibility. They’re a reward you earn by establishing your reputation and credibility first.

Unconscious Thoughts

I’ve been thinking about trust lately — specifically about how fast we assess it, and how little we’re aware that we’re doing it.

In particular, there are all these little micro-moments that happen before we make a decision. They live in the split second before the brain processes whatever we are reading, watching, or listening to. They are beats in time when something quiet, but immensely powerful, happens: we decide if we trust whatever information we are taking in. This internal process is fast, automatic, and largely invisible — until, well, it isn’t.

I was reminded of this internal assessment last week when two emails landed in my inbox within minutes of each other. They both shared the same broad topic, Claude Code, and the same implied promise — leverage, edge, future-readiness. One made me lean in. The other made me recoil. And the gap between those two reactions is what I’ve been considering ever since.

How do these messages make you feel?

Immediately, No

It would be easy to chalk my reaction up to not liking pushy sales tactics. And sure, that’s part of it, but it’s not the whole story.

I invest in courses, hire advisors, pay for subscriptions, and buy all kinds of things. I respond to urgency all the time. The key however is that it has to come from someone I trust.

So, what was it that bothered me about the second email? It honestly wasn’t the offer. It was the posture. The framing was future-focused and fear-based: What happens if you don’t take action today? From someone I’d never met. Someone who had never meaningfully been in my inbox. Someone who had not yet established any credibility or relational equity with me whatsoever.

My reaction wasn’t this is interesting. It was something closer to:

That sentence is about sequence. Not sensitivity.

The Real Reason

Consumer psychology tells us that before taking action, people perform a perceived risk assessment — financial, functional, social, psychological. But in digital environments there’s another layer to consider: relational uncertainty.

Relational uncertainty is the degree to which a person lacks confidence in the nature, intentions, or trustworthiness of another party in an interaction. In face-to-face contexts, we resolve it through body language, reputation, shared social context. But online, those signals are stripped away, and in their place we get design, tone, social proof, and increasingly, AI-generated polish. When those proxies are all we have, the pressure to assess correctly increases. So we scan harder — for familiarity, demonstrated expertise, consistency over time, and tone that matches the actual depth of the relationship.

This is where urgency tactics run into trouble. They serve as decision amplifiers, and amplifying a decision before building trust surfaces risk. Put another way, fear-based urgency from someone with no relational standing doesn’t feel motivating. It feels like pressure from a stranger. And when perceived risk rises, people withdraw.

Yes, It’s A Pattern

This reaction isn’t new to me.

Years ago I signed up for a free trial at a gym with some friends (a rite of passage I suspect many readers have also experienced), and I had to sit down with a very enthusiastic salesperson at the end of the week. His entire job was to convert me.

The good news: he did exactly what he was trained to do: limited-time rate, today-only pricing, gentle but persistent pressure about what committing to my health would mean six months from now. It wasn’t aggressive. It wasn’t even rude. But I remember thinking, get me the #$@! out of here.

My discomfort was apparently written all over my face, because my friends turned it a running joke that they still laugh at whenever I’m in the hot seat.

I didn’t fully understand my own reaction at the time. But I do now. My gut was screaming:

The bad news (at least for the sales person): I didn’t join. Not because the gym was bad. Not because the price was wrong. Because the urgency of the pitch had outpaced the relationship — and when persuasion tries to move faster than trust, the gap gets filled with risk. And I walk away from unnecessary risk every time.

If you've been reading Marketing Jam for a while, you know I like to build what I call Purpose Plays into my posts. A Purpose Play is a brief pause for you to step out of the ideas and into your own experience. If you're new here, welcome to the tradition.

Purpose Play

Think about the last time you walked away from something you were interested in. Not because the offer was bad — but because something felt off. What was the signal you were reacting to? Was it the tone, the timing, the assumption of intimacy? What would it have taken for that same ask to land differently?

Why This Matters Today

My gym story was personal. But the dynamic it captures isn’t.

We’ve spent the last two decades living in the digital attention economy — a system where capturing attention was the primary strategic goal. In that environment, urgency worked. Scarcity cut through. Fear grabbed clicks. The metrics rewarded the tactics and the playbook spread accordingly.

But that model is showing its age. Media analyst Evan Shapiro describes the market we are in today as the “affinity economy”: a user-centric era where community, engagement, and genuine passion drive value. The distinction matters:

And that shift changes how persuasion functions. When audiences have real control — when they can unsubscribe, mute, cancel, or scroll past a post in seconds — urgency without relational equity doesn’t work. It comes off as pushy, and, quite frankly, a little insulting.

Now, put that in context with today’s affinity-driven environment, and the sequence is non-negotiable: credibility first, then urgency. Trust first, then acceleration.

My Point

Urgency is not dead. Scarcity is not dead. Future framing is not dead. They will always work — but they need to be used at the right moment in the right relationship.

When a brand deploys one of these tactics too early, it can look like the audience is pulling back. This reaction gets misread as indifference. But it’s not indifference. It’s withdrawal due to a lack of relational equity. And the difference matters enormously.

Indifference means the audience was never interested. Withdrawal means you had them — and lost them by moving too fast. In an attention economy, you could recover from that. Reach and frequency could get you back in front of someone. In an affinity environment, trust compounds slowly over time and erodes quickly. It doesn’t however reset on demand.

The bottom line: You can earn the right to urgency, but you can’t assume it.

Purpose Play

Think about the last time you deployed urgency in your own marketing: a deadline, a limited offer, a fear-framed email. Where were you in the relationship with that audience? Had you established enough credibility and consistency for that ask to feel earned?

What It All Comes Down To

The right to urgency isn’t granted by confidence or good copy. It’s built slowly, through consistency, through demonstrated expertise, and through showing up in a way that earns the next interaction before you ask for it.

When brands skip that work and lead with pressure, the audience goes into assessment mode. They instinctively search for credibility markers and disengage when the ask feels bigger than the relationship. Not out of disinterest. Out of self-preservation.

The psychology isn’t complicated — but waiting to build trust and affinity before attempting to accelerate conversion apparently is.

About the Work

I’m Amy Zwagerman—brand strategist, fractional CMO, and founder of The Launch Box. I work with founders and marketing leaders to translate durable marketing principles into strategies and systems that fit their specific context, stage, and goals.

Marketing Jam sits alongside my client work as a place to explore ideas more openly. If the thinking here resonates and you’re curious about working together, you can learn more about my services or get in touch here.

AI-supported, human-led. All ideas and insights are my own. Curious how I use AI and where I draw the line? See my AI Disclosure Policy →

Integrity Pledge 🙋🏻‍♀️: The books, newsletters, shows, podcasts, and client work shared here are 100% reflective of my world. I will always disclose if and when I have a relationship with a brand I mention in a post or am sharing an affiliate link.

TL;DR

91% of marketing teams are using AI.¹

That sounds terrifying—until you realize most are stuck in “random acts of prompting.” This post breaks down the real story behind the statistic: how marketers are actually using AI today, what it takes to move forward, and what this shift likely means for your career.

The Sky is Falling… or Is It?

The AI conversation has shifted a lot over the past few years. We’ve all seen the headlines: AI is going to change (or destroy) the world. It is somehow going to simultaneously kill jobs, create jobs, destroy trust, save time, democratize creativity, harm the environment, make us all superhuman, and reshape the economy.

A lot of this information is just noise. Posturing to support a narrative. The reality however is that none of us have a crystal ball, and how AI ultimately affects society is a story only future historians can tell.

That said, underneath all the hype and fear, something real is happening—and it’s worth paying attention to. Not the headlines. The data. Because the data tells us what is going on at the ground level, where most of us are at today, and it’s often quite different from what we’re seeing on our news feed.

If you’re familiar with the Gartner Hype Cycle, I think we’re somewhere between the Peak of Inflated Expectations and the Trough of Disillusionment—but it honestly depends on what AI innovation you are talking about.

This post is my attempt at unfurling all the of headlines and all of the data that I’m seeing in real time. The goal is simple: understand how the market is shifting, my place in it, and how I should be thinking about AI as I look to the future.

The Maturity Curve: Where Teams Actually Are

According to Jasper’s 2026 State of AI in Marketing Report, 91% of teams are using AI in some capacity.¹

I recently heard that stat on a webinar and did a serious double take. I mean, as a marketer, that is a really scary statistic, like Scooby Doo ruh-roh kind of scary. My brain literally went on tilt.

Don’t freak out. The second, and I would argue, more important statistic they revealed highlights that the majority of these users are simply experimenting with prompts. That’s it.

Digging even deeper, the broader story is that there are three distinct AI user groups within the 91%:

1. Experimenters (60-70% of the market): Performing random acts of AI. Basic prompting. No workflow integration.

2. Integrators (20-25%): Embedding AI into specific processes, but navigating corporate governance hurdles and struggling to scale.

3. Transformers (3-10%): Redesigning workflows. Helping to define governance. Creating and scaling agents. Measuring ROI.

My brain is no longer on tilt, but I’m definitely thinking that the presenter should have led with this information.

Which leads me to an important question: what type of AI user are you?

I myself have self-identified an integrator, or, more accurately, an integrator working towards becoming a transformer. But, as I’ve mentioned in previous posts, I love technology and would go bonkers if I wasn’t always dabbling in something new, so my constitution for this stuff is higher than most.

What really makes this data interesting is how each segment is engaging with AI:

• Experimenters treat AI as a task tool: “Help me write this email. Summarize this doc.”

• Integrators treat AI as a process tool: “Help me draft, then refine, then check for brand voice.”

• Transformers treat AI as a system: “Here’s the workflow. Here are the constraints. Here’s how outputs get validated before they ever reach a human.”

The research also tells us that high-performing marketing teams are 2.8x more likely to have fundamentally redesigned their workflows, reinforcing the usage data.¹

​​Before we go further, I want to introduce a quick pause into this story. I call these moments Purpose Plays. They are short prompts designed to help you translate the ideas being discussed into your own context.

Purpose Play

Think about the recurring workflows in your world — drafting strategies, launching campaigns, producing content, approving creative, tracking results. If you could rebuild one of them today, how would you use AI to change the architecture? Are there any steps you could eliminate or automate? Are there any you absolutely couldn’t?

The Skill That Moves You Forward

In reality, the gap between AI Experimenters and AI Transformers isn’t all that big.

I’ve said this before, but it is worth repeating: It’s not about access. Everyone has access to the same tools.

It’s also not about knowledge. There is a learning (aka experimentation) curve with AI, but prompt engineering isn’t as complicated as it’s made out to be. At its core, it’s about clarity — which I like to think of as the 5W’s (who, what, why, where, and when) + how.

So, what exactly is the gap?

Mostly, it’s understanding how AI works, when to use it, and what to use it for. I am defining this skill as judgment, or, more specifically, the ability to direct AI with intention towards the result you want to achieve.

Take my work for example. I built a proprietary custom GPT for a service I offer called The Brand Blueprint™. This GPT worked so well that I created a client-facing version, assuming it would help people get ‘Amy’ level results at a fraction of the cost. But it didn’t. Not even close. Here’s why: most people don’t have the knowledge and experience to know if the AI output is on-brand—structurally, tonally, strategically—or not. That’s my lane. Not my clients.

Think about it: you can’t become a rocket scientist, botanist, mechanic, or anything really, by asking AI to give you all the answers—you need to first possess the knowledge and experience necessary to determine whether the AI is giving you good information or not.

Purpose Play

Choose one area where your expertise is already strong — and test how AI changes the shape of your work. Not the speed. The shape.

Pay attention to what improves. Pay even closer attention to what degrades. The contrast is where your competitive edge lives.

What This All Really Means

The conversation around how AI is going to affect marketing work needs to shift from “What roles will it replace?” to “What skills do we need to cultivate?”

The truth as I see it: We don’t all need to become developers. But we do need to understand where AI amplifies expertise—and where it exposes gaps in judgment.

Recent reports from both the Marketing AI Institute and McKinsey point to a need for what can best be described as a new version of the ‘T-Shaped Marketer’: people who have both domain expertise and AI competency. Think vertical depth in a marketing discipline (brand strategy, growth, content, performance) and horizontal breadth in AI fluency across how the work gets done—knowing when to use it, how to direct it, and when to step in. ^2,3

Additionally, new roles are emerging fast. The hot job titles right now¹:

• AI Search Specialist

• AI Transformation Lead

• AI Trainer

• AI Governance Lead

Look, I don’t think I’m unique in feeling the pressure to stay on top of how AI is changing my vocation of choice. I fall prey to headlines. I worry about getting left behind. And I have hot debates with my friends about whether AI is good or bad.

But, in the end, my POV is this: AI isn’t the real differentiator. Judgment is.

The marketers who will move ahead aren’t going to be the ones who know the most about AI. They’ll be the ones who know how to use AI to do their job better. Not because they mastered the tool but because they mastered their lane.

From Insight to Integration

If this piece clarified anything for you, it’s probably this: AI isn’t the differentiator. How you design the work is.

Next week, I’m leading an AI-Powered Growth Marketing workshop where we’ll look at how AI integrates into real marketing systems — what to automate, what to redesign, and where judgment matters most.

It’s application-first, not hype-driven.

Two sessions. Details can be found here: Feb 25 or Feb 27.

Sources

¹ Jasper (February 2026) The State of AI in Marketing 2026
² Marketing AI Institute SmarterX (January 2026) Marketing Talent AI Impact Report
³ QuantumBlack, AI by McKinsey (November 2025) The State of AI in 2025

About the Work

I’m Amy Zwagerman—brand strategist, fractional CMO, and founder of The Launch Box. I work with founders and marketing leaders to translate durable marketing principles into strategies and systems that fit their specific context, stage, and goals.

Marketing Jam sits alongside my client work as a place to explore ideas more openly. If the thinking here resonates and you’re curious about working together, you can learn more about my services or get in touch here.

AI-supported, human-led. All ideas and insights are my own. Curious how I use AI and where I draw the line? See my AI Disclosure Policy →

Integrity Pledge 🙋🏻‍♀️: The books, newsletters, shows, podcasts, and client work shared here are 100% reflective of my world. I will always disclose if and when I have a relationship with a brand I mention in a post or am sharing an affiliate link.

TL;DR

Realizing how disconnected I am from the rhythm of movie releases sent me into reflection mode. The POV I landed on: In a world where discovery is increasingly automated, awareness isn’t created by being louder or more frequent — it’s created when something feels clear, relevant, and meant for the right people to notice.

I woke up the other day with a thought that surprised me: I miss movies.

Not in a nostalgic, everything-was-better-before Covid way — more like a quiet realization. I mean, I live in Los Angeles, and I spent a good chunk of my career working in entertainment, so, ipso facto, opening weekend used to play an outsized role in the rhythm of my life. But, like a lot of people, going to see the latest movie fell off my to-do list in 2020 and never really found its way back. I was honestly pretty content to think those days were behind me.

But I recently decided to watch Tron: Ares on one of my TV apps and realized it was exactly the kind of film I would’ve liked to see in a theater. Big screen. Loud sound. A shared experience. Which made me wonder: why didn’t I go see it?

The answer: I barely knew Tron: Ares existed, but, and also, maybe a little because the last Tron bored me enough that I hadn’t been looking for another sequel.

What hit home as I went all deep about my movie going behavior is that I really didn’t know anything about the film before last week. I hadn’t seen a trailer. I hadn’t clocked a release date. I didn’t have a sense of what kind of experience it was meant to be. I do remember actress Greta Lee crossing my social media feed more than a few times, but the clip, while delightfully entertaining, didn’t get me to search out the film. And that feels meaningfully different from how movies used to enter our lives.

Do you remember this clip? Did it make you want to go out and see Tron: Ares?

Which brings me to the topic of marketing. I see this as a classic discovery (aka awareness) problem.

Here is my chain of thought:

1. Web 2.0 changed the way we receive news and information. People used to hear about things in environments designed for exploration — flipping channels, browsing a magazine rack, listening to the radio. This is a very lean-back model where information is pushed out to the public.

2. Today, discovery is mostly lean-forward. This means the onus is on the public to search out and pull information out of the systems we have access to. A person needs to know what they want to watch, read, or listen to or they will find themselves looking for a needle in a haystack.

3. In that shift, something else happened quietly: computers replaced curators. Platforms became the primary way content reaches us, and algorithms took over the job of deciding what we might like next. Their goal isn’t to help us discover something new in a meaningful way — it’s to keep us engaged.

4. What surfaces, aka registers in our brains, are optimized moments, familiar patterns, and things adjacent to what we’ve already shown interest in. Over time, that makes discovery narrower, not broader.

Web 2.0 (noun): websites that emphasize user-generated content, ease of use, participatory culture, and interoperability (i.e., compatibility with other products, systems, and devices) (Wikipedia).

The term represents the shift from static, publisher-driven media to interactive, user-generated, platform-based systems where content is discovered, shared, and ranked through user behavior and algorithms.

Bottom line: brand awareness is much more complicated today than it was even 5 years ago.

In a system optimized for engagement, the challenge becomes: how do you ensure the people you actually want to reach receive your message? Or, in my case, how does someone like me — a person who genuinely would have enjoyed seeing Tron: Ares in a theater — ensure that I find out about it?

Historically, marketers assumed repetition would do the work and adopted the Rule of 7. This logic, however, while still being applied to basic marketing models today, starts to break down in an environment where people can skip, or, gasp, block ads and scroll past thousands of messages a day without really seeing any of them. In that context, showing up seven times doesn’t guarantee awareness. It just adds to the noise.

Rule of 7 (noun): a marketing principle that suggests a potential customer needs to encounter a brand’s message at least seven times before they take action and make a purchase (Growth Media).

This is why I keep coming back to an idea that media strategist Even Shapiro describes as the affinity economy (ESHAP, Media War & Peace).

His position is that people are shifting away from scale-for-scale’s-sake in a move toward finding more connection, relevance, and belonging. Awareness isn’t being created by volume here, it’s being created by fit. Out in the real world, I’m seeing this trend come to life in social communities curated around values and behaviors vs roles. For example, I’m going on a LA Tech Walk to meet other people interested in AI that live in my neighborhood and am thinking about joining Dog PPL, a hybrid park, café, bar, and lounge for people who want to hang out with their canines. (I’m even willing to drive to a different part of LA to check it out. IYKYK.) This highlights a broader cultural signal: in an environment this crowded, awareness is no longer being created by being louder or more frequent. It’s created when something feels like it is for you. Put another way, when something aligns with your interests, your identity, or the way you see the world, it cuts through the noise in a way repetition alone never will.

One additional note: On a societal level, there’s another dynamic at play: age. Discovery systems are no longer operating against a single, shared audience. Increasingly, they’re supporting two distinct audiences, often split along generational lines, with different habits, platform preferences, and expectations (Evan Shapiro also covers this shift here). That split adds another layer of complexity to building awareness — but it’s a deeper conversation for another day.

For brands, this changes the work. If awareness is earned through affinity, then clarity and relevance matters more than coverage. People don’t connect with everything — they connect with people, places, and things that reflect something they already care about. That means ‘brand marketing’ can’t be an afterthought layered on top of distribution. It has to do the orienting work up front: what something is, who it’s for, and why it exists. Technology can amplify that signal — or flatten it entirely — depending on whether it’s used to express a point of view or simply to scale output, and purpose now matters in a very practical way. It means more than a price, slogan, or positioning exercise.

When a brand knows how it wants to show up and can do so consistently, its signal gets easier to read. Decisions get simpler. Messages cohere. And the right people connect with it.

Purpose Play

For those who are new here, a Purpose Play is my way of helping you connect what I’m writing about to your own business. It’s a moment to step back from the ideas, check for alignment, and consider whether—and how—something applies to what you’re actually building.

Take a moment to think about the brand you’re building—or rebuilding.
Not the logo. Not the content calendar. The idea of it.

Ask yourself:

• What do I want this brand to be known for?

• If someone only encountered it in fragments—a headline, a post, an ad—what would they understand about what it stands for?

• Would that signal be clear enough to create recognition?

I don’t miss movies because I want to go backward. I miss what they represented: shared context, anticipation, a sense that something was worth showing up for.

That feeling is harder to create now: not just for studios, but for any brand trying to be noticed in a crowded, fragmented system. Building awareness just asks for a different kind of work. Less volume. More intention. Less chasing attention, more earning recognition.

And I think that matters.

About the Work

I’m Amy Zwagerman—brand strategist, fractional CMO, and founder of The Launch Box. I work with founders and marketing leaders to translate durable marketing principles into strategies and systems that fit their specific context, stage, and goals.

Marketing Jam sits alongside my client work as a place to explore ideas more openly. If the thinking here resonates and you’re curious about working together, you can learn more about my services or get in touch here.

AI-supported, human-led. All ideas and insights are my own. Curious how I use AI and where I draw the line? See my AI Disclosure Policy →

Integrity Pledge 🙋🏻‍♀️: The books, newsletters, shows, podcasts, and client work shared here are 100% reflective of my world. I will always disclose if and when I have a relationship with a brand I mention in a post or am sharing an affiliate link.

🙋🏻‍♀️ Hi! I’m Amy Zwagerman——Fractional CMO, brand strategist, and founder of The Launch Box. I help founders and creative experts build brands that feel like them and actually work.

If you’ve noticed I’ve been quiet since June… you’re right. What started as a vacation turned into a full-blown summer sabbatical. I didn’t plan it, but I needed it. And honestly? I’m glad I pressed pause. Writing this piece felt like stretching muscles I’d been neglecting—my storytelling ones—and it reminded me why I love this work so much.

If you’re new here, welcome. If you’ve been with me for a while, thank you for sticking around. I’ve got more stories, strategies, and Purpose Plays coming your way this fall.

→ If your brand feels scattered or invisible, and you want to find it’s voice, let’s talk. You can book a free discovery call or explore my services here.

TL;DR

AI can draft, dazzle, and even deceive—but it can’t tell your story. Used with context, curiosity, and a human touch, it becomes an amplifier, not a replacement. Join me as I explore the messy middle between tradition and technology.

I want to have a conversation. Not a debate, not a pitch—just an honest reflection on how AI is reshaping creativity and productivity in every aspect of our lives.

Case in point: I was writing about authenticity in marketing and the presidential race when ChatGPT handed me quotes that fit my story angle perfectly. Except… when I went back to check the sources, I found out they didn’t exist. When pressed, the tool admitted it had stitched them together from “sentiment.” WTF? I had asked for quotes.

(Side note: that piece never saw the light of day—my theory unraveled as soon as I discovered the facts I had so expertly woven into the story were fake. 🤦🏻‍♀️)

That moment landed hard. It’s when I realized LLMs like ChatGPT, Perplexity, Gemini, and Claude are just smarter, faster machines coded to please (and, ahem, make us feel smart)—even if that means bending the truth. Which is why I see AI less as a replacement for creativity and more as a mirror: it amplifies what you bring to it, blind spots and all.

For me, AI is a magnifying glass, a creative sparring partner, and a way to get to the heart of what I want to say, faster. It doesn’t replace my originality—it unlocks it when I know what to ask and where to push back. Maybe you disagree and find my premise bananas. I’m ok with that. How and when to use AI—or not—is a choice I believe everyone has to make for themselves. But denying that AI is changing how we work, play, and live? That’s a risk I don’t want anyone to take.

A quick note for those of you who are new here: I like to pause in my posts with something I call a Purpose Play. Think of it as a moment to step back from the ideas, reflect on how they connect to your own work, and maybe spark a fresh perspective.

Purpose Play

Before we dive deeper, pause: What’s your relationship with AI—excitement, skepticism, curiosity? If you’ve used AI, have you noticed moments where it’s helped or held you back? If you haven’t played around with it yet, why not?

I’m convinced the secret to unlocking AI’s potential is context—and a lot of it.

This isn’t new. You might remember the early days of computing (it wasn’t that long ago), when the adage “Garbage In, Garbage Out” (GIGO) was a common rule of thumb. And, IMHO, it still applies.

For those of you who are unfamiliar, the theory goes like this:

AI doesn’t make you brilliant. It gives you speed. It gives you access to more information than you could ever cull yourself. It organizes things. But it also reflects blind spots. And panders. And hallucinates. AI is like the overeager intern who desperately wants to impress, so much so that they don’t admit when they’re in over their head.

Let me give you an example. If I feed AI vague or broad requests, I get generic output that is reminiscent of a thousand other landing pages, marketing emails, and blog posts we’ve all seen. This is not good work. Is is not AI making my job easier, and it certainly isn’t work I would ever put in front of a client. But when I layer in the context I’ve earned through years of watching a brand’s heartbeat, understanding human psychology, and dissecting market behavior, the tool suddenly becomes a turbocharged extension of my thinking. It sharpens my ideas, surfaces fresh angles, and frees me up to focus on what truly matters: the story, the strategy, and the connection, i.e., my zones of genius.

Purpose Play

Think about your own “zones of genius.” Where do you feel most alive in your work—where ideas flow, time disappears, and you’re fully in it? Now, ask yourself: how could AI support you in those spaces without diluting what makes them uniquely yours?

I’ll name my lane: I’m not an artist by training. I’m a strategist, a business builder, and—only recently—a curious explorer of creativity.

I’m going to give a quick nod to Julia Cameron here. ‘The Artist’s Way’ helped me see that creativity isn’t about titles or temperament. It shows up in everyday choices: cooking a meal, decorating my home, planting my first (smart)garden, even designing a strategy that clicks. That shift changed how I approach my work, my life, and even how I think about AI: it’s power isn’t in what it is, but in how you channel it.

Put another way, I don’t think AI is inherently creative. It’s how you use it that makes the difference.

I learned a similar lesson back in my home entertainment days, when the industry was evolving at warp speed (all hail Star Trek 🙇🏻‍♀️). In less than two decades, we went from VHS to DVD, DVD to Blu-ray, Blu-ray to 4K UHD, and from video rentals to streaming (And for the videophiles out there—yes, I skipped Betamax and LaserDisc. They were before my time, forgive me.). I loved it. I sought out projects on the bleeding edge and even bought a 3D TV—glasses and all—because I wanted to see what was possible.

The takeaway?

Technology can package and distribute stories at new speeds and scales, but the human spark is always the anchor. AI feels like the next iteration of that truth—only now the speed is faster, the stakes are higher, and the margin for passivity is shrinking.

Purpose Play

Where does your creativity—and your storytelling—come alive? Imagine bringing AI into that process: does it help you spark new angles, sharpen your voice, or expand your reach? If you’re afraid it will make your work less distinct, ask yourself—what if it could actually make your voice clearer, stronger, and more your own?

I have so much respect for the purists—the people who insist on the handmade, the unscripted, the deeply human.

Their devotion to craft is a reminder that what’s real will always matter.

For me, that devotion shows up most clearly in storytelling. It’s the thread that runs through my career, from my start at People magazine to the brand strategies I shape today. Stories are how we connect—and why the human element can never be replaced.

But it doesn’t have to be purity or technology. The real art is in weaving them together—honoring tradition while experimenting with what’s next. That’s where I live: in the overlap, where strategy meets curiosity and AI adds fuel without ever grabbing the wheel. My job is to stay curious, skeptical, and human enough to keep the work grounded.

Because the magic isn’t in choosing sides—it’s in the messy middle.

(And let’s be honest: the last thing I want is an AI that thinks it’s The Terminator.)

Purpose Play

Where do you see yourself in the balance between tradition and technology? If you leaned into both with intention, what kind of work—or story—could you create that wouldn’t be possible any other way?

AI’s here to stay. It will shape our future in ways we’re only starting to imagine.

Whether you embrace it, analyze it cautiously, or avoid it intentionally, its impact is undeniable—and ignoring it could mean missing real opportunities.

But the heart of creation, innovation, and connection remains squarely with us: the people who ask, who feel, who translate raw input into meaning.

Because here’s the truth: AI can generate content, but only humans can tell stories. And it’s story—the way we connect dots, share meaning, and create belonging—that makes the difference.

Purpose Play

What’s one project you could take on right now—big or small—where you bring in AI alongside your own expertise, curiosity, and personal story? Pick it. Try it. See what happens.

So let’s keep this conversation going. Which parts of your work are you amplifying with AI? Where do you push back? What surprises have emerged when you let AI work alongside your brain, not instead of it? Share your stories in the comments or send me a DM—I read every one.

If AI is the amplifier, your story is the song.

Ready to make your brand sound like you—clear, authentic, and magnetic to the right customers?

→ Book a free discover call or subscribe to Marketing Jam for more real talk, brand strategy, and tools that turn context into clarity.

AI-supported, human-led. All ideas and insights are my own. Curious how I use AI and where I draw the line? See my AI Disclosure Policy →

Integrity Pledge 🙋🏻‍♀️: The books, newsletters, shows, podcasts, and client work shared here are 100% reflective of my world. I will always disclose if and when I have a relationship with a brand I mention in a post or am sharing an affiliate link.