Thinking

AI Default Brand Strategies: Win AI Recommendations

Thinking Header Default Brand Strategies Large

The ideal world for a marketer has always been clear.

To know when a person needs something. To understand the goal they’re trying to achieve. To respond in that moment with an offer that fits. To see how the person reacts. And to learn from it, immediately.

Not once. But millions of times, at the same time.

That’s been the dream since marketing became a discipline. Philip Kotler probably sketched it on a napkin in 1967. John Wanamaker famously complained he was wasting half his advertising budget—he just didn’t know which half. Every CMO since has nodded in painful agreement.

It was never a lack of ambition that stopped us. It was constraint.

Why the old system was built

Humans and organizations could not do this at scale.

We could not sense demand as it formed. We could not decide in real time. We could not coordinate actions across functions. We could not learn continuously from every interaction.

So we invented workarounds.

We created segments, and froze people into them. The soccer mom. The millennial foodie. The business traveler. As if humans stayed put in neat boxes instead of living messy, multi-dimensional lives.

We created campaigns, so activity could be planned in bursts. The fall launch. The holiday push. The Super Bowl spot. Because organizing thousands of people and millions of dollars required advance planning, not real-time response.

We created annual plans, because learning was slow. Last year’s data informed this year’s strategy. By the time you learned what worked, the world had moved on.

We created channel silos, because coordination was impossible. TV did awareness. Print did consideration. Direct mail did activation. Digital did… well, digital did whatever was left. Everyone fought over budgets and blamed each other for suboptimal results.

These were not bad ideas. They were necessary.

Procter & Gamble didn’t become a $300 billion company by being stupid. Coca-Cola didn’t conquer the world with bad marketing. Nike didn’t build a religion around sneakers by accident.

This is what we now call the attention economy.

An economy built on interruption. On inferred demand. On proxies instead of reality. You interrupted people watching Friends with a commercial, hoping they’d remember your brand when they went shopping three days later. Sometimes it worked. Often enough, anyway.

Marketing became the art of managing abstractions: reach, frequency, impressions, clicks. We got very good at it. We built entire careers on optimizing CTR by 0.3%. We A/B tested button colors. We argued about attribution models in conference rooms.

Growth was linear. Profit was indirect. You spent money, waited, measured, adjusted, repeated. Spray and pray. The feedback loops were long. The causality was fuzzy. But it was the best we had.

What changes now

Today, AI removes the original constraints. That’s not my idea. Sangeet Paul Choudary wrote in this book, Reshuffle (2025): new technologies, especially AI collapse the core constraints in systems.

Not partially. Structurally.

Technology now makes it possible to sense needs and intent as they emerge. When someone searches “best running shoes for bad knees,” you know exactly what they need. When they abandon a cart at 11 PM, you know the moment to re-engage. When they browse your competitor’s site, you know they’re shopping.

You can act in the moment, not after the fact. The offer appears. The discount triggers. The recommendation surfaces. Right now. Not next week during the next campaign.

You can coordinate decisions across the system. Pricing adjusts based on inventory. Content adapts to behavior. The chatbot knows what the customer service rep said yesterday. The system operates as one organism, not twelve warring departments.

You can learn while operating, not in hindsight. Every interaction teaches the system. Every click, every conversion, every bounce refines the model. Learning compounds continuously.

This is not about better targeting. Amazon already knows you want The Godfather trilogy before you do.

It is not about better personalization. Spotify already created a playlist that knows your mood better than your therapist.

It is not about productivity. Sure, AI writes your email copy faster. That’s nice. That’s not the point.

It is about making the interaction between company and customer operational. It brings the interaction field I conceptualized a few years to live, it makes it real (The Interaction Field, 2020).

This is the intent economy.

The real shift: from proxies to signals

The old system optimized proxies because there was no alternative.

Segments stood in for people. You sold to “suburban moms 35-54” instead of Tamar, who’s training for her first half-marathon, worried about her knees, and researching shoes at 10 PM because that’s when the kids are finally asleep.

Campaigns stood in for interactions. You launched in September because that’s when budgets freed up and the agency finished the creative, not because September was when people actually needed your product.

Funnels stood in for journeys. Awareness, consideration, purchase. Clean. Linear. Logical. Except nobody’s actual journey looks like that. They see an ad, ignore it, hear about you from a friend, read reviews, forget about you, see another ad, click, get distracted, come back three weeks later, and finally buy. Or don’t.

Channels stood in for coordination. TV built awareness. Digital captured intent. Retail closed the sale. Each measured separately. Each optimized independently. Each convinced they deserved more budget. The customer experienced it as chaos.

AI changes this.

Intent becomes a live signal, not a statistical guess. You don’t infer that suburban moms might want minivans. You detect that Tamar is researching seven-seaters because she’s carpooling to soccer practice and her Civic isn’t cutting it anymore.

Decision-making moves from planning cycles to continuous orchestration. You don’t decide in January what to promote in October. You respond in real time to what people need right now.

Learning compounds with every interaction. Netflix doesn’t wait for quarterly surveys to figure out what works. Every view, every pause, every rewind teaches the algorithm. The system gets smarter while you sleep.

Marketing stops managing representations of reality. It starts operating on reality itself.

Why this changes the architecture of growth

In the attention economy, growth started with messaging. You crafted a campaign. You bought media. You interrupted people. You hoped some of them remembered you when they had a need. Growth depended on memory structures and mental availability. It was probabilistic. Indirect. Slow.

Demand was stimulated. You created desire where none existed. You convinced people they needed things they didn’t know they wanted. “Just Do It” didn’t respond to demand for sneakers—it created a movement. It worked. But it required massive investment, patience, and faith.

Efficiency was optimized inside silos. TV got more efficient at reach per dollar. Digital got better at cost per click. Retail improved conversion rates. But nobody optimized the whole system, because nobody could see the whole system.

Profit was inferred at the end. You spent $10 million on marketing, revenue went up $30 million, you assumed causality, and hoped the CFO didn’t ask too many questions. Marketing mix modeling tried to untangle it. Mostly it produced consultant reports gathering dust.

In the intent economy, growth starts with demand. You detect Tamar searching for running shoes. You appear with the right shoe, the right content, the right offer. You don’t create demand—you capture it as it forms.

Intent triggers action. The system responds automatically. The product gets recommended. The email gets sent. The ad appears. The price adjusts. No planning cycle. No approval process. No waiting for the quarterly campaign.

The system coordinates end-to-end. Uber doesn’t have separate teams for “ride awareness” and “ride consideration” and “ride conversion.” You open the app, you see cars, you book, you ride, you pay. One system. One experience. One optimization.

Profit is traceable and causal. Amazon knows exactly which recommendation drove which purchase. Google knows which ad generated which revenue. The line from intent to action to profit is direct and measurable.

This is a different architecture, not an upgrade.

It collapses the distance between intent, action, value creation, and economic profit.

And here’s where it gets interesting.

How brands compound in the intent economy

In the attention economy, brands compounded in one way: in consumers’ minds. You built associations into a memory network around your brand. You created salience, easy to come to mind when it matters. When someone needed a cola, they thought Coke. When someone needed shoes, they thought Nike. This compounding was real but slow. It took years. Decades, even.

In the intent economy, brands compound in two ways.

First, they still compound in consumers’ minds. That hasn’t gone away. Mental availability still matters. You still want people to think of you first.

But second—and this is new—brands now compound through attention itself.

Attention is the scarce resource. Not reach. Not impressions. Attention. Real, focused, valuable attention from someone who actually needs what you’re selling right now.

And brands capture attention through a four-part model of competitive advantage:

Relevance: Do I consider you? Are you even in my consideration set when I have this specific need, in this specific moment? If you sell running shoes but you’re not relevant to “bad knees,” you don’t exist.

Distinctiveness: Do I recognize you? In a sea of options, do you stand out? Can I recall you? Distinctiveness gets you noticed. It gets you considered. But it doesn’t get you chosen.

Differentiation: Do I have a reason to choose you? What makes you different from the seventeen other options I’m looking at? This is where most brands stop. They think differentiation is the pinnacle. It’s not.

Default: Do I even consider alternatives? This is the summit. Default means you’re the reflexive answer. The automatic choice. When Tamar needs running shoes, she goes straight to your site. She doesn’t Google. She doesn’t compare. She doesn’t think. You’re the default.

Google is the default for search. Amazon is the default for shopping. iPhone is the default for smartphones (if you’re in the Apple ecosystem). These brands don’t fight for attention anymore. They own it.

And here’s what matters: as you climb this hierarchy—from relevance to distinctiveness to differentiation to default—each level amplifies the next. It compounds.

Relevance gets you in the game. Distinctiveness gets you noticed. Differentiation gets you chosen. Default gets you chosen again and again and again without effort.

This compounding through attention creates exponential growth in economic profit, not linear growth.

In the attention economy, you spent more to get more. Double your ad budget, maybe you doubled your sales. Linear. Expensive. Exhausting.

In the intent economy, once you reach default status, growth becomes exponential. You capture more intent. You learn faster. You optimize better. You become more relevant, more distinctive, more differentiated, more default. The flywheel spins faster.

Netflix didn’t win streaming by having the best content (though they do). They won by becoming the default. “Netflix and chill” entered the language. When people think streaming, they think Netflix first. That’s default. That’s compounding. That’s exponential profit growth.

The uncomfortable truth is this: most brands are still fighting at the relevance and distinctiveness levels. Very few reach differentiation. Almost none reach default.

But the intent economy makes default achievable for more brands than ever before. Because you can now operate on intent directly, in real time, at scale.

The future is already here

And it’s not theoretical anymore.

Google Gemini and ChatGPT are already implementing this new architecture. Right now. Not in some distant future. Today.

ChatGPT has memory. It remembers your preferences, your past conversations, your needs. It has shopping research built in. It has an agentic browser called Atlas that can navigate the web on your behalf. And it has Instant Checkout—you can complete a purchase without ever leaving the conversation.

Google launched AI-powered shopping with Gemini. Virtual shopping agents that know what you want, find it, compare it, and help you buy it. All conversational. All transactional. All in one place.

Both systems use an open standard called Universal Commerce Protocol (UCP). This isn’t a proprietary play. It’s infrastructure. Like HTTP for commerce.

Think about what this means.

Search has fundamentally changed. It’s no longer ten blue links. It’s a conversation that becomes a transaction.

You don’t type “best running shoes for bad knees” and click through twelve websites, read reviews, compare prices, open new tabs, bookmark options, come back later, forget what you were doing, and start over.

You ask: “I need running shoes. I have bad knees. I’m training for my first 10K. Budget around $150.”

The AI responds: “Based on your knee issues and training goals, I’d recommend the Brooks Adrenaline GTS or the ASICS Gel-Kayano. The Brooks are $140, the ASICS are $160. Both have excellent cushioning and stability. Which matters more to you—lighter weight or maximum support?”

You answer. It refines. It shows you options. It checks inventory near you. It finds a discount code. You buy. Done.

You never left the conversation. You never visited a retailer’s website. You never saw a brand’s carefully crafted landing page. You never encountered their conversion funnel.

The entire journey collapsed into a dialogue.

This is not an incremental improvement. This is a different system.

What this means for brands

Every brand built for the attention economy just became vulnerable.

If the customer never visits your website, what happens to your direct relationship? If they never see your brand story, what happens to your positioning? If they never experience your carefully designed customer journey, what happens to your conversion optimization?

The AI becomes the interface. The AI becomes the recommendation engine. The AI becomes the moment of purchase.

And the AI doesn’t care about your brand guidelines.

It cares about solving the customer’s problem. Right now. In this conversation.

This is why the four-part model matters more than ever.

Relevance: If you’re not in the AI’s training data, if you’re not connected to the Universal Commerce Protocol, if you’re not accessible through these systems—you don’t exist. You’re not even considered.

Distinctiveness: If the AI can’t articulate why you’re different, you’ll be lumped in with alternatives. “Here are five similar options” means you’re a commodity.

Differentiation: If you don’t have a clear, compelling reason to be chosen, the AI will default to price, availability, or ratings. You’ll compete on the lowest common denominator.

Default: If you can’t become the automatic answer—”For your needs, I recommend X”—you’ll always be fighting for consideration. The AI will keep presenting alternatives.

Brands that reach default status in these AI systems will capture exponential value. They’ll be the first recommendation. The trusted answer. The reflexive choice.

Brands that don’t will become invisible.

The architecture of the future

The intent economy isn’t coming. It’s here.

Google and OpenAI have already built the infrastructure. ChatGPT and Gemini are the new front door to commerce. The Universal Commerce Protocol is the plumbing that makes it work.

This is the system that collapses intent, action, and transaction into a single continuous experience.

You express intent through conversation. The system acts immediately. The transaction completes without friction. Learning happens in real time. The next interaction is smarter.

No websites. No funnels. No campaigns. No channel attribution debates.

Just: intent → response → value creation → economic profit.

All happening in seconds. All traceable. All optimizable.

The brands winning in this system won’t be the ones with the biggest ad budgets. They’ll be the ones who understand how to operate within conversational commerce. How to make themselves relevant, distinctive, differentiated, and ultimately default within AI systems.

They’ll be the ones who stop managing attention and start capturing intent.

Because in a world where the AI is the interface, attention is table stakes.

Intent is everything.

The old system was not wrong. It was limited.

We managed proxies because we had no choice. We interrupted people because we couldn’t detect intent. We ran campaigns because we couldn’t orchestrate continuously. We measured reach because we couldn’t measure impact.

The people who built this system were brilliant. They optimized under constraint. They created enduring brands with limited tools. They deserve respect, not dismissal.

Now we do have a choice.

AI does not improve marketing inside the attention economy. It makes the intent economy possible.

It doesn’t make your campaigns 10% better. It makes campaigns obsolete.

It doesn’t improve your segmentation. It makes segments irrelevant.

It doesn’t optimize your funnel. It collapses the funnel into a moment.

And that changes not just how we market, but how growth itself works.

The question is no longer: how do we get better at attention?

The question is: how do we build systems that operate on intent?

Because the companies that figure that out won’t just grow faster. They’ll compound. They’ll reach default. They’ll capture exponential profit growth.

And the companies that don’t will keep optimizing proxies while their competitors operate on reality.

That’s the shift.

Welcome to the intent economy.

Frequently Asked Questions

How is artificial intelligence transforming marketing?

AI allows companies to analyze data, automate decisions, and personalize customer experiences.  

Why is marketing architecture changing in the AI era?

Traditional marketing systems relied on manual processes, while AI enables intelligent automation.

What opportunities does AI create for growth?

AI enables organizations to identify demand signals and optimize customer engagement.

What challenges arise when implementing AI-driven marketing?

Companies must integrate technology, data governance, and strategic planning.

How does Vivaldi help companies build AI-driven marketing strategies?

Vivaldi designs growth strategies that integrate artificial intelligence with brand and business strategy.