The Dark Side of AI: What Market Volatility & Super Bowl Ads Reveal About the Future of Strategy

I recently wrote about a biological advantage of your Narrative Brain. Our unique human ability to use conjecture (imagining a future) rather than just correlation (analyzing the past).

But as we head into Super Bowl weekend, a tension is emerging. It’s a conflict between the comfort of data-driven certainty and the messy, unpredictable nature of human creativity. And it’s making the market nervous.

The Market’s “Dark Side” of AI

Yesterday’s New York Times was direct: “The Dark Side of AI Weighs on the Stock Market.” After a year of AI euphoria, we’ve entered a phase of volatility.

The index was down for the year, after large gains over the last 12 months.

The anxiety isn’t just about AI taking jobs. It’s that AI might render business models obsolete by doing exactly what those models were designed to do: optimize the known. If we only train human employees and students to act like algorithms (sorting data and following “best practices”) we make them replaceable by definition.

As a recent Op-Ed argued, AI is unparalleled at pattern recognition, but lacks human judgment. Our ability to decide if an analysis is wise. For too long we’ve only been training leaders to be the things the market is now devaluing.

In Defense of the Map

To be clear, this isn’t an argument against data. I have many colleagues who have built their careers on the mastery of spreadsheets and analytics. Their work is vital. As S.I. Hayakawa might say, they are the Map-makers.

They provide clear, rigorous data that tells where we are standing. Without them, we are flying blind. You can’t make an imaginative leap to the future if you don’t have a grounded understanding of the present. The “Map” (the spreadsheet) is the essential foundation.

The problem arises when we confuse the Map for the Territory. For decades, business schools and C-suites have suffered from Physics Envy or the desire to turn strategy into a “hard science” with universal, immutable laws. We want to believe that if we input enough data, the “correct” strategy will be revealed.

Business is a human science, not a natural one. In physics, if you drop a ball, it falls. In marketing, if you drop a product or an ad, the result depends on culture, timing, and narrative. There are no universal laws of marketing success hidden in a spreadsheet.

When we demand that every move be “statistically significant,” we create a ceiling. Statistical significance requires a large sample of the past, but innovation is a statistical outlier.

The Snickers Paradox: Why AI “Fails” at the Super Bowl

Nothing illustrates this better than a masterclass in human insight: the Snickers “Betty White” spot, recognized as one of the best Super Bowl ads of the last 25 years.

My former agency, BBDO, created this campaign (though I didn’t work on this specific account). This week, predictive AI tools like Neurons Inc. released an analysis claiming the ad is “imperfect” because the branding and logo appear too late.

Despite the Snickers Super Bowl ads marketing success, A.I. says the problem is it focuses too much on the people and not enough on the brand.

From a “best-practice probability” standpoint, the AI is right. The “Map” of past successful ads says you should brand early.

From a “best-practice probability” standpoint, AI is right. The “Map” says you should brand early. But the “Territory” of human emotion tells a different story. The ad worked because it used conjecture to build tension.

You’re hooked by a 90-year-old woman being tackled in a mud pit, and the product is the “Aha!” solution. If you give away the ending in the beginning, you remote the interest. You create an ad shows the brand early to follow a “best practice” but is ignored.

Math, Meet Magic

Data did play a role in the campaign. As David Lubars, BBDO’s Global Chief Creative Officer, has noted, qualitative research identified a globally consistent “code of conduct” for how people interact within a group.

The creative team synthesized this into a profound human and product truth: When you’re hungry, you’re not on your game. Snickers is substance that “sorts you out.”

They didn’t just find a data point. They designed a narrative. And the world responded:

  • The Recognition: The ad topped the USA Today Ad Meter as the #1 Super Bowl spot.

  • The Buzz: It generated over 91 days of media coverage from a single 30-second spot and 400 million unpaid media impressions—a value of $28.6 million, or 11.4 times the initial investment.

  • Effectiveness: It won an EFFIE for both creativity and marketing effectiveness helping sales of Snickers increase $376m during the two-year period from 2010-2012
  • The Bottom Line: Sales grew by 15.9% in the first year, increasing market share in 56 of its 58 global markets.

Number one in the Super Bowl ad ratings and still engaging today. Click on the image to view in YouTube.

Math, Confirm Magic

After my advertising creative career, I entered academia as a professor. One of the first academic studies I did was on this very phenomenon. My research partner Michael Coolsen and I proved that for brands, “For Brands, A Little Drama is a Good Thing.

Our research proved telling complete stories following a five act form increases Super Bowl ad ratings and YouTube shares and views. We used the “Math” of academic research to confirm the “Magic” of storytelling. A Narrative Brain isn’t just a creative preference. It’s a measurable business driver.

This aligns with Angus Fletcher’s research into the Narrative Brain shows that the human mind isn’t a logic processor. It’s a story processor. While AI is stuck in the world of probability (what usually happens), the human brain is built for narrative intuition (imagining what could happen). This is our “Primal Intelligence.”

The Human Edge

This is the approach we’re exploring in the Markets, Innovation & Design program at Bucknell University. We’re not “anti-data.” We’re “pro-human integration.” The spreadsheet is the starting line, not the finish line.

  1. Analyze the Map: Use data and analytics to see where the market is.

  2. Enter the Territory: Use empathy and observation to find the human insight.

  3. Make the Creative Leap: Move from Correlation (Map) to Conjecture ( Driver) to design a future the data hasn’t seen.

The Competitive Advantage of the Unpredictable

The market is currently punishing companies that look like they can be replaced by an algorithm. The antidote to that fear is a more balanced approach to business education.

We need the Map-makers to show us where we are, but we need the Narrative Designers to decide where we’re going. The most successful strategies, the ones that win the Super Bowl ads and dominate markets, aren’t found in a “best-practice” log. They’re designed by people who look at the Map and then choose to drive somewhere the Map never saw coming.

About This Post’s Creation It was developed in partnership with Gemini. AI helped bridge the market news with my last post, the core perspective, first hand experience and research insights remains my own.

Beyond the Binary: Your Narrative Brain vs. AI’s Rear-View Mirror

I’ve been forcing myself to regularly read physical books again.

Not articles. Not threads. Not AI summaries. Actual books. Cover to cover. It’s my way of reclaiming an attention span fragmented by years of algorithmic feeds designed to keep me scrolling on shallow tidbits.

If AI can consume a library of data in seconds, maybe my competitive advantage is going slower and deeper.

Two books that have been sitting on my shelf are S.I. Hayakawa’s Language in Thought and Action and Angus Fletcher’s Primal Intelligence. The first was written in 1939 and the second 2025. As I read them over several weeks, something clicked.

My brain, the neural synapses Fletcher writes about, made a connection no algorithm would have surfaced: Hayakawa’s framework for “sane” thinking during WWII and Fletcher’s research on how human brains “imagine” new paths or plans in the future.

S. I Hayakawa Language in Thought and Action and Angus Fletcher Primal Intelligence.
No AI would have picked up these two books and made a connection to imagine a new path forward.

Our Narrative Brain

This is what your Narrative Brain does. It makes imaginative leaps across disparate ideas. It asks “What if these two things connect?” A semantics book and neuroscience book written 86 years apart. No dataset, predictive analytics, or AI could have made this creative leap.

It’s a unique capability we risk losing if we don’t understand how to partner with AI correctly.

Many conversations about AI in business and marketing position it as an all or nothing proposition. AI will and should replace employees or (because of this threat) we should avoid using AI at all.

In AI lessons from 2025, I shared how I explored AI partnership versus replacement last year. But I still didn’t understand the core biological barriers and benefits.

Hayakawa and Fletcher gave me the answer. Fletcher explained the fundamental difference between how AI processes information and how our brain works. Hayakawa helped me understand the challenges in AI adoption. Both are key to staying sane (and essential) as a knowledge worker in the AI revolution.

Light Switch vs. Dimmer

Hayakawa described two ways of looking at the world. A Two-Value Orientation is like a light switch. It’s binary: people are all evil or all good. Knowledge work should be all human or all AI. When we approach business, marketing or communications this way, we ask “Should we use AI?” and expect a simple Yes or No.

A Multi-Value Orientation, however, is like a dimmer switch. It recognizes that reality exists on a scale. Instead of automatically labeling people as good or evil, we consider nuance like perspective, circumstance, and intent. Instead of asking “If” we should use AI, we ask, “To what degree and in what context is AI appropriate for each task?”

Key Insight: Two-value thinking creates conflict. Multi-value thinking creates a roadmap for collaboration.

Light Switch vs Dimmer AI Integration
Let’s consider a more nuanced approach to AI integration.

Your Biological Advantage

In his book Primal Intelligence, Angus Fletcher points out a biological truth that changes how we may view AI.

AI runs on transistors that perform Correlation. Its logic is A = B. It looks at massive datasets of the past to see what usually happens. Given A, there’s a 95% chance that B comes next.

If you ask AI for a business or marketing idea, it calculates the statistical probability of which words usually go together. It is, effectively, a high-speed rear-view mirror. It can tell you where the market has been.

Your brain, however, runs on neural synapses that perform Conjecture. Your logic is A → B. You don’t just see two things are typically related. You can imagine a potential causal link. You can look at a set of facts and ask, “What if we did the opposite?” or “Why can’t these go together?”

You can also see possible ways forward when faced with missing, incomplete, or unexpected information. Whereas AI is prone to hallucinations when faced with a lack of data.

For example, AI looks at the data and says: “90% of successful luxury brands use minimalist black-and-white logos.” That’s correlation. But a human looks at a crowded, monochrome market and asks: “What if we used neon yellow to signal a different kind of rebellion?” AI follows the trend to be safe. You break the trend to be noticed.

When correlation said people wanted better keyboards on their phones, Steve Jobs used conjecture to imagine a different story: a single piece of glass that could hold the internet. That strategy drove Apple to fill in the gaps to make that “improbable” narrative happen. AI could not have “imagined” that possibility based on previous data.

AI is a map of the past (Correlation). You are the driver of the future (Conjecture).

The Abstraction Ladder

Hayakawa also taught us about the Ladder of Abstraction. For business and marketing the top would be the “Map” with vague labels like “Customer Satisfaction.” At the bottom is the “Territory” such as the actual, concrete facts and interactions with real people.

AI is great at the top of the ladder. It can summarize the Map of “General Trends” all day. But because it lacks a physical body and lived experience (what Fletcher calls “Embodied Intelligence”), it can’t feel the Territory. Stepping into a customer’s perspective to understand their motives is a human act. AI can track a click, but it can’t feel a wince.

It is why your human empathy can’t be outsourced to AI.

Example: AI can tell you “Gen Z engagement is down 15%.” That’s a top of the ladder abstraction. You climb down to the Territory by observing and talking to Gen Z customers. By understanding their lived experience, you sense an erosion in trust or a shift in culture that doesn’t hit a data log. Territory AI can’t access without embodied experience.

A multi-value approach uses AI to handle the high-level abstractions, which frees up your human brain to climb down the ladder to the real lived experience. We use our Narrative Brain to find the specific, human story, the A → B sequence, that makes a brand feel real.

In a world where AI levels the data playing field, competitive advantage returns to the humans companies employ. Your edge is no longer who has the most data. You’ll need people who can look at a spreadsheet and still see the human story.

Instead of acting in the past you’ll begin imagining new futures and designing marketing actions to make them happen.

5 Levels of AI Integration

To help us navigate this, I created a 5-level scale of AI Integration based on multi-value orientation and our biological advantage. Not every task deserves Level 5 automation. As a professional you’ll know when to turn the dimmer switch up or down based on the human value required.

5 levels of AI integration with a multi-value orientation that leverages our brain’s primal intelligence advantage. Click image to download a PDF.

Now It’s Your Turn

If you’ve been avoiding AI, start at Level 1. This week, ask it to proofread an email you’ve already written. That’s it. You’re still the author. You’re still making all the decisions. Notice how it feels, what it catches and misses.

Then try Level 2. Or if you’re doing that try higher. Try deep research, brainstorming, outlining, drafting, feedback or variations with a reasoning model. Don’t know how? Ask AI.

The goal isn’t to become a better prompt engineer. It’s to become a better thinker.

Become someone who knows when to leverage speed and when to trust your human ability to imagine what doesn’t exist yet. Leverage AI to speed up low value tasks to free up more time for your unique human contribution.

This is why I’m back to physical books. Reading deeply is training for your Narrative Brain. It builds the stamina to stay “low on the ladder” and follow complex stories in the market, in your life and in our world. Real life is not black and white, one’s and zeros.

It ensures that when you step into a meeting, you aren’t just looking at the rear-view mirror of data. You’re the one who can internalize the customer’s perspective and imagine a future the data hasn’t seen for true innovation.

Two Books on a Shelf

Remember those two books on my shelf? No AI would have recommended I read them together. No algorithm would have surfaced their connection. But my Narrative Brain, the same you use every day in your work, made an imaginative leap that created this framework.

That’s what makes you irreplaceable: the ability to make connections that don’t exist in any dataset. Only a human can see the gray areas where the next big idea usually hides.

AI can tell you the most likely next word, but only you can imagine the most meaningful next chapter.

Moving from a two-value “Either/Or” mindset to a multi-value “Degrees-of” mindset, enables you to start imagining and start creating a better future with your narrative brain.

About This Post’s Creation

This was developed in partnership with Google Gemini 3.0 and Claude Sonnet 4.5. Both helped organize and refine. The connection of General Semantics and Narrative Science is my own. One that came from the kind of deep, sustained reading and cross-pollination of ideas that only a human narrative brain can produce.