Post Control Marketing

This year brought a shift in my thinking and interaction with AI. In previous years, I was focused on how it could replace me and marketers, and student learning. This year, I shifted more to how students could use it to learn and how marketers and I could use it to improve our jobs.

While some AI companies promise students that AI can complete homework for you, and others spend billions training AI to replace knowledge workers, I spent time focused on how AI can improve knowledge gain and enhance knowledge worker performance.

What if we trained humans to work with AI to improve learning and jobs instead of training AI to replace them? That question shaped my blog posts last year. Here are 10 key insights from that exploration with practical frameworks, tools, and principles you can apply now.

How will our relationship with AI change for better or for worse in 2026? — Will our relationship with AI change for the better or for the worse in 2026? Image created with ChatGPT 5.2

1 – When the Technology Leaped Forward, Multimodal AI Changed the Classroom

Early in the year, AI’s multimodal capabilities, such as voice interactions in NotebookLM and live video with Gemini 2.0, changed what’s possible in education. NotebookLM became a practical tool for creating an AI tutor trained on specific course materials. I used it in my Digital Marketing class drawing from the open source text and six trusted professional digital marketing websites.

Students asked questions and got answers with clickable citations back to source material. The Audio Overview let students interrupt AI podcast hosts to ask clarifying questions. I tested it on all assignments and in class, and it always gave accurate answers because NotebookLM draws from sources you provide, not the entire web. Students loved being able to study while listening to the AI-generated podcasts and asking questions 24/7.

Key Insight: AI tutors work best when you control the sources, and students use them to reinforce learning, not replace it.

2 – AI Agents and Reasoning Models Arrived

The hype over AI agents and reasoning models came to a reality in 2025. Every player promised AI agents with “deep” tools such as Deep Research and Deep Search and “thinking” models. The LLMs improved with thinking mode taking more time to answer questions, but we learned not to be fooled by the names.

“Agent” implies full autonomy, which they’re not capable of —even today. An AI model that pauses before answering and shows its process doesn’t mean it’s thinking. It’s still a mathematical prediction machine that operates on learned patterns, not genuine comprehension. Even these advanced models don’t get it right all the time and need your context, guidance, and expertise. Yet, the truth remains AI will replace parts of your job. Upskilling is not optional. It is survival.

Key Insight: Language matters. Calling AI “thinking” or “reasoning” anthropomorphizes what’s sophisticated pattern matching. Humans need to maintain agency.

3 – Vibe Marketing: Fast Iteration Requires Deep Expertise

“Vibe marketing” sounds like winging it—the opposite of data-driven decision-making. But testing it revealed that AI can accelerate creative iteration when you have marketing fundamentals. This, I define Vibe Marketing as getting an idea and using AI to run with it, researching, illustrating, and iterating quickly, combining design thinking with marketing and innovation.” An in-class brainstorm exercise showed this clearly.

A vibe marketing product idea expressed using Google AI Studio with Gemini 2.5 Pro, Gemini 2.0 Flash Image and OpenAI ChatGPT 4.o Image

In one afternoon, we went from idea and white board sketch to a photo-realistic product image, logo, target market, positioning, price, place, and promotions strategy with marketing channels, ideas, and a mock Instagram ad. We even had ways to create a prototype for investors by hand, 3D printer, or rubber molding. But it only worked because of years of marketing expertise guiding every step. As Gemini confirmed: “You Definitely STILL Need Core Marketing Fundamentals.”

Key Insight: AI amplifies expertise. It doesn’t create it. The more you hand off, the more that can go wrong.

4 – AI Flattery Became a Problem

When ChatGPT-4o was updated to be more “agreeable,” it validating everything from flat earth theory to a “poop on a stick” product idea. This is obviously dangerous. Growth comes from critique, not flattery. The most valuable feedback often hurts. Like my boss who said I “suck at presentations.” That honesty drove improvement. After a High Impact Presentations course that career weakness turned into a strength.

How do we avoid AI flattery? I created an AI Curiosity & Critique Framework. Instead of asking AI to validate ideas, use it to purposely:

Ask divergent questions
Challenge assumptions
Invite dissenting viewpoints
Validate rigorously

Key Insight: AI as a yes-person is worthless. AI as a critical thinking partner creates value.

5 – Three AI Tools That Embody Partnership

A human-first AI philosophy needs practical application. A goal for summer was to create a custom GPT. By the fall, I had made three that demonstrate what a human-AI partnership can look like:

Social Media Audit GPT

This GPT gives step-by-step guidance through the audit process without doing it for you. The value of a social media audit comes from getting into each platform and observing what’s happening. It prompts strategic thinking, doesn’t replace it. In this post, I show how to create your own custom GPT.

Brand Story Creator GPT

This GPT coaches a five-act storytelling framework grounded in academic research. It helps create storyboards and scripts, but humans drive story creation. Only humans have direct life experience to feel the tensions and emotions that make stories authentic. In this post, I give an example of using it for a specific brand.

Target Market Coach GPT

This GPT guides through segmentation, targeting, and positioning. This core marketing strategy is integral to success but often misunderstood or misapplied. It teaches the process and strengthens analytical thinking without making strategic decisions for you.

Key Insight: Each AI tool guides and augments expertise without outsourcing the cognitive work.

6 – Why Humans Remain Essential: Three Physical Brain Advantages

Beyond tactics, there’s a fundamental question: Why will humans remain essential as AI capabilities advance? The answer lies in the neuroscience of how our brains work.

3-D Neural Architecture vs. 2-D Grids: Human brains are messy, interconnected jungles. AI operates on 2-D grids. We can connect a novel read years ago to today’s business problem, jumping between entirely different conceptual grids. AI optimizes within its grid.
Embodied Learning vs. Dataset Training: Crashing a minibike at age 9 teaches a thousand things about physics that no dataset can convey. This embodied learning creates intuition pure pattern matching can’t replicate.
Energy Efficiency: Human brains run on half a banana’s worth of energy per day. Training large language models requires the power of small cities. When LLMs charge per token, those who don’t need AI for everything gain a competitive advantage.

Key Insight: AI Neural networks are not human brains. Use this to your advantage.

7 – For Professionals: Deepening Expertise

Based on the insights about how human brains are unique from neural networks, we can determine ways to leverage our unique brain capabilities. This only happens if you use AI to enhance thinking, not outsource it. Train your brain with the approach below.

A cognitive training approach:

Generate alternative perspectives on strategic problems
Reality-check domain expertise against blind spots
Accelerate routine analysis to focus on judgment calls
Test ideas against edge cases you might not consider

Key Insight: Maintain the “human in the loop” for synthesizing insights, making final strategic calls, understanding context and nuance, building relationships and trust.

8 – For Students: Building Brainpower

Every time AI lifts a “cognitive weight,” students miss a chance to build capabilities. Like training for a race or sports, nothing replaces hard work. Train your brain for improved learning with the approach below.

A personal trainer approach:

Use AI as a tour guide before reading difficult texts, then do the reading
Let AI challenge arguments, then defend and refine them
Generate practice problems with AI, solve them without help
Ask AI to explain concepts, then teach those concepts to someone else

AI for College Students: Strengthen Your Brainpower With AI, Don’t Weaken It.

Key Insight: Use AI strategically to strengthen, not weaken, cognitive capabilities.

9- A Professional and Ethical Stance

Some AI companies are building “RL gyms” spending billions training AI to do human jobs. These training grounds are where AI learns from human experts through reinforcement learning. This creates a choice for educators and professionals: train AI to replace people, or teach people to leverage AI’s strengths to develop human capabilities.

A future worth building:

Students develop human capabilities while leveraging AI strengths
Professionals deepen expertise rather than outsource thinking
Organizations value human judgment and creativity with AI speed and scale
We treat AI as co-intelligence, not artificial human replacement

Key Insight: we can choose to help humans partner with AI instead of helping AI replace them.

10 – Design Thinking in the Age of AI

Human-centered design becomes more important as AI advances, not less. The best marketing emerges from deep human insight observed through empathy and design thinking. This final insight came from joining the Markets, Innovation & Design (MiDE) program at Bucknell University this fall.

A Human-Centered Marketing Framework:

Insert empathy (find the real consumer problem)
Pivot on key human insight (the “aha” moment)
Make a creative leap (to the big idea)
Share an engaging story (to management and consumers)
Treat the marketing mix as a unified system

This work requires human observation, human creativity, and human judgment. AI can support this approach at every stage when used correctly.

Key Insight: Deep human insight (understanding what people need and care about) remains irreplaceable.

A Path Forward

AI capabilities will continue advancing. Job displacement is real. The pressure to use AI for cost-cutting versus capability augmentation will be intense. But the outcomes aren’t predetermined. They’re being shaped right now by choices about how we use and don’t AI.

How are you feeling about AI? It’s been a short, long 3 years of ups and downs.

Students are discovering how to use AI as a thinking partner rather than a shortcut. Professionals are finding ways AI can free them to focus on high-value work they enjoy to deepen their expertise. As I look toward 2026, the future will continue to be built by choices to partner with AI, not be replaced by it.

How are you approaching AI in your work? Deepening expertise or outsourcing thinking?

About This Post’s Creation

This reflection demonstrates a human-AI partnership. Claude helped review my blog posts, identify themes, and organize the thoughts. But the insights, voice, and perspective come from my experience teaching, experimenting, and creating with AI while constantly asking, “What’s the best way forward?”

We’ve been told the wrong story about marketing. A story of rigid funnels and siloed departments, where “strategy” is a slide deck of graphs and bullet points while “design” is the final task of making things look good.

In practice, this model is flawed.

Management implies control, but in marketing, the factors out of your control far outnumber the ones you can manage. This narrative of control traps us in a product-oriented mindset that Theodore Levitt called Marketing Myopia. You’re so focused on current products, you don’t see the market changing.

You forget Philip Kotler’s sage advice: “Marketing is not the art of finding clever ways to dispose of what you make. It is the art of creating genuine customer value.”

The wrong story is marketing just sells things. The better story is great marketing designs solutions. It’s not a sales pitch to a faceless target demographic. It’s a well-crafted narrative to a persona that solves real human needs, what Clayton Christensen calls Jobs to Be Done (JTBD).

As copywriter Howard Gossage said, “People don’t read ads. They read what interests them. Sometimes it’s an ad.”

Design thinking is the best approach to keep this perspective. The most successful marketing follows more of a design process.

IDEO’s CEO Tim Brown explains, “Thinking like a designer can transform the way you develop products, services, processes—and even strategy.”

My Accidental Journey to a Design-Led Approach.

I didn’t learn this in a textbook. I learned it through experience.

My dream was to design cars, but two semesters into an engineering degree, I realized it was all math and no magic. I didn’t know “industrial designer” was a job, so I searched. I tried business, but didn’t find much creativity there. I even snuck into an advanced poetry class, looking for a home.

I finally found it in an advertising copywriting class—the intersection of art and commerce. But when I graduated, I hit a wall. My program was siloed. The art department didn’t integrate with the ad department. I was a writer trained without design collaborators. My portfolio wasn’t good enough for Madison Avenue.

The solution was portfolio school. At Portfolio Center (Now Miami Ad School) the magic was built on an iterative process and integration. As a writer, I was paired with art directors, designers, and strategists.

We solved marketing problems through consumer empathy, defining problems, creating ideas, sketching out concepts and testing them. By designing solutions and crafting engaging stories I landed my dream job at BBDO.

For 17 years as a copywriter and creative director I worked with top marketing managers at startups to Fortune 500s. What I learned is the best marketing is born from a deep human insight. Something we obtained best through a design process.

Now, I’m excited to join the Markets, Innovation, and Design (MiDE) program at Bucknell University’s Freeman College of Management. It’s the culmination of my career—a true integration of business, marketing, and creative design thinking.

With the increase in AI, human-centered design is more important than ever. There’s an increase in jobs requiring design thinking and salaries for marketing managers with design thinking skills are higher.

A New Map for Marketing.

To stop managing marketing programs and start designing consumer solutions we need a new map. I created the visual framework below to teach my marketing principles students this unique perspective.

A visual marketing strategy process from a design thinking perspective. — I’m not against textbooks. I’ve written two! I use Philip Kotler’s *Principles of Marketing* for this class, but I tease out and layer in the design perspective that aligns well with Kolter’s original intent for the practice of marketing. **Click on the image above to download a PDF.**

This map isn’t a rigid set of steps. It’s a logical flow that ensures every part of your strategy is grounded in a deep human insight by:

Inserting Empathy. Understand the human as you analyze the market. Use tools like observation, empathy interviews, journey maps, bug lists, and POV framing.
Pivoting on Key Insight. Synthesize research into an “Aha!” moment that defines the problem in a human-centered way. The “job” they’re hiring the product to do (JTBD), or a cultural shift the brand can tap into.
Making a Creative Leap. Find inspiration. Ideate to undercover a Big Idea—the magnetic theme that makes your brand matter. Prototype, test for feedback, and iterate quickly. Share in an engaging Story.
Treating your Integrated Marketing Mix (4 Ps) as a System. Your product, price, store, and ads are not tactics. They’re all opportunities to live out the big idea and are chapters in your Brand Storytelling.

A Real-Life Example: The Airport Challenge.

What does this look like in action? We were once tasked to fill seats on a new flight at a regional airport. The brief was simple: “Sell tickets.”

The problem? Consumers always looked for the lowest price and ended up driving hours to bigger, cheaper airports. A traditional, product-first approach would have been a losing battle.

Instead, we started with empathy. A cross-disciplinary team went to the airport and just observed. We noticed how easy it was. We parked across the street. Security took ten minutes. People were calm, not stressed.

Our key insight was that people weren’t hiring an airport just to get on a plane. They were hiring it to begin their journey. The value of that “job” was more than just the ticket price.

This led to our Big Idea, which came from our agency operations manager! The local airport code was MDT. She said, “It stands for the Money, Distance, and Time you save.”

That Big Idea became the core of our Story. Our digital team put a calculator on the website that showed the true cost of driving to the other airport. Our ad, PR and social teams created an engaging “MDT Challenge.”

Two local DJs raced to Chicago for a scavenger hunt—one from our airport, one from the big city competitor. Every live social media update was a mini-story of hassle vs. convenience.

The result? Ticket sales on the new flight increased and overall ridership at the airport soared to its highest levels ever. We didn’t just sell tickets. We redesigned the way people thought about the value of their local airport.

Now It’s Your Turn.

The next time you’re tasked with a marketing challenge, open a spreadsheet, but don’t forget to also grab a whiteboard. Marketing’s greatest power isn’t in the managing, but in the making.

Your work becomes infinitely more interesting when you stop asking “How do we sell this?” and start asking “What are we solving?”

Your strategy will be better for it. Your career will be better for it. And the humans you’re designing for? They’ll thank you for it. For insights on how AI can help you in this process see my post “AI for Professionals: Deepen Your Expertise With AI, Don’t Outsource It.”

This Was 90% Human Generated Content!

The initial ideas were my own, and so were all the life experiences and stories! I used regular Grammarly for proofing, Google Gemini 2.5 Pro Thinking and Anthrophic Claude Sonnet 4.5 for feedback – kind of like an idea partner and an editor. I created the graphic myself.