We’re witnessing large language models (LLMs) change the world: From search to automation to productivity, the possibilities of harnessing this rapidly evolving technology are staggering. With these advancements comes the emerging promise of personalized artificial intelligence (AI). Although not yet ubiquitous and evolving slower than promised, early examples like Apple Intelligence and Alexa+ hint at what’s on the horizon for personalized artificial assistants, while already-introduced protocols like the Model Context Protocol (MCP) demonstrate early examples of how LLMs can trade context across services. All of these examples provide frameworks for third-party integration and opportunities for a brand to integrate and supply data to these AI systems.
You shouldn’t sleep on this potential. Consumers are excited about agentic AI delivering tailored information retrieval, automated actions, and context-aware decision-making. But for a modern brand, personalized AI represents a fundamental, momentous shift in user interaction. How will this affect discoverability and user retention? For good reason, this shift is met with trepidation, even fear — and that’s warranted. Most analyses agree we’re on the precipice of a profound change in how users engage with the world of information. It’s easy to see a future where AI poses a threat to the status quo, dramatically changing today’s advertising and marketing channels. Yet, with proper preparation, these changes can become opportunities for you as a motivated brand — provided you’re ready.
History as a primer: SEO changed how brands reach consumers
Before readily available digitized information, brands relied on traditional advertising: print, mailers, billboards, and television. In-person stores and massive distribution networks were essential to physically reach customers. These routes favored brands with big budgets, broad appeal, and strong distribution — like Coca-Cola, who dominated the soft drink sphere by airing expensive TV ads and monopolizing retail shelf space. This led to consumer demand tilting toward large, established players.
As the world digitized, consumers turned to search engines for access to brands. This behavioral shift birthed search engine optimization (SEO), and brands optimized discovery and engagement for search intent. High-quality, relevant content became king, allowing the tying of searches like “best organic juice near me” to purchases along with measurable ROI. A niche player like Joe and the Juice could outmaneuver Coca-Cola by ranking well, iterating faster on offerings, and adapting to new advertising methods like paid search placements. Success in SEO required a new set of demands: mobile-friendly, fast-loading websites and esoteric tweaks to climb algorithms. The status quo flipped: Agile, content-focused, digitally native companies thrived, while large established companies fell behind. SEO’s lesson? Changing the medium changes the game.
How personalized AI is taking shape
Much like the shift to SEO, personalized AI will redefine how users discover and interact with brands. In broad strokes, personalized AI is a context-aware LLM, leveraging user data and historical interactions to craft an ever-evolving, personalized model for each user. For the user, this promises better access to tailored information, faster adaptation to their unique preferences, and superior connectivity to the world’s information and actions. Think of personalized AI as a highly customized, highly aware agent acting on the user’s behalf.
But here’s the opportunity: Personalized AI is a proxy, not the system. It handles end-user interactions, but it doesn’t own the user. What does this mean for brands? The AI agent may manage how users engage with brands, but the brands can still influence what they see. Personalized AI might know a user’s habits — like ordering pizza — but brands hold the business data: inventory, purchase history, or item popularity. The AI agent doesn’t enforce business logic like pricing, eligibility, or special offers. It’s a smart UI layer interacting with your brand’s ecosystem, surfacing information or taking action based on what you provide. For example, if Alexa+ suggests a dinner recipe, Instacart can feed it real-time data (“20% off pizza”) to shape the outcome. The brand’s role? Supply the raw material for AI to personalize.
Making personalized AI work for your brand
If AI acts as a proxy for the end user, brands must still engage the end user and influence them toward ideal outcomes. To do this effectively, consider three steps:
1. Focus on the medium used to reach the end user
SEO taught businesses to distill purchase intent from search. “Mexican food near me” became a monetizable term directly mapping to business return on investment (ROI). A restaurant ignoring search and instead investing in a new storefront awning missed the new medium — and became more or less invisible to a large number of potential customers. Personalized AI shifts the focus again. It’s not impressed by flashy webpages, slick animations, or pretty pictures — it consumes data: text, customer reviews, product specs, and availability. A streaming platform like Netflix might have a stunning site, but if its API doesn’t expose what’s currently available to watch, AI could skip it for Peacock’s structured data (e.g., “Die Hard, 4.8 stars, available to stream”). When it comes to AI, clean, accessible API access trumps UI. Wikipedia just proved this point by launching a cleaned, pre-parsed dataset, explicitly for API access. Audit your infrastructure — is your data labeled, accessible, and AI-understandable? Can AI parse your catalog effortlessly?
2. Determine the best data to surface
Beyond data accessibility is data applicability. Can you rely on user identity for context? Take a clothing brand scenario: I ask my AI agent for “clothes for my upcoming vacation.” It checks my calendar, sees the forecast, and searches for “warm-weather shirt in men’s medium.” Without context, a brand like Nike might suggest a generic bestselling T-shirt. But a brand with my purchase history like J.Crew knows I prefer blue, collared linen shirts and then wins my purchase by offering exactly that. Building user profiles (with consent) and integrating them into your data layer via APIs or JSON feeds can increase the value of your end-user offering. The brand surfacing the best offering using contextual data can have the edge.
3. Measure and iterate
Any marketer can attest to the need to test to find optimal results. However, the battle lines for personalized AI are just starting to form, and the eye-watering funds being deployed by the heavyweights indicate we’re looking at a long drawn-out fight. The good news is that this will extend the timeline for a clear winner, giving brands room to experiment. The bad news is brands will need to integrate with multiple platforms during this shakeout. A brand like Spotify might approach this by feeding Apple Intelligence “recently played” data versus sending Alexa+ “mood-based” metadata to see what drives more user listens. Spotify can use both channels to discover which approach delivers better results. Like SEO, success demands constant measurement — it will just need to be spread across multiple platforms while the winners emerge. Start small: Expose a feature on each (e.g., “start streaming” via Siri’s App Intents, “play again” on Alexa+) and optimize based on results. The agile will adapt; the rigid will fade.
Opportunities amid disruption
We’re witnessing a fundamental shift in brand-user interaction — it’s scary. Some companies will adapt, new ones will emerge, and others will fail. SEO changed the world by enabling faster iteration, broader reach, and new engagement methods. Personalized AI promises this at warp speed. Imagine Peet’s Coffee feeding my AI agent “large latte, extra shot” for frictionless reordering, locking in loyalty — or a brand like Instacart winning my attention by suggesting my favorite meal for reordering. The risks are real: Sloppy data or misread intent could render your brand invisible. But the opportunities are vast. By learning from SEO’s past, brands can turn personalized AI’s disruption into a competitive edge — master the changing medium, leverage your data, iterate relentlessly. The opportunity is knocking. Start prepping now.
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