Could a brand ever know you as well as your best friend? With AI, it’s not just possible—it’s already happening. From hyper-personalized Spotify playlists to chatbots that seem to “get” you and know what suits you best, AI is reshaping how we bond—not just with tech and eachother, but with brands as well.

By 2028, 70% of consumer-business interactions on mobile devices will involve AI, according to a Gartner report. Same report shows organizations are set to replace 20–30% of customer service agents with generative AI, while the EU considers mandating a “right to talk to a human” in customer service.

Can AI finally make brand love—that deep, emotional bond marketers have chased for decades—a reality? With the ability to personalize, customize, predict, and even mimic empathy, maybe it just might…

What Is Brand Love, Anyway?

Brand love, a term that sits somewhere between a marketing buzzword and a psychological deep dive. Drawing psychological frameworks such as Sternberg’s Triangular Theory of Love (1986), parasocial relationships theories and experiential theories, the concept of brand love emerged and gained significant attention in the early 2000s. Defined as a deep emotional attachment to a brand, it promises all the good stuff: loyalty, word-of-mouth hype, a willingness to pay extra and forgiveness in case of mess ups. Naturally, it’s been pitched as the holy grail of consumer-brand relationships.

Some key contributions to the field include:

    • Kevin Roberts (2004): In Lovemarks, he argued for emotional branding that goes beyond traditional strategies, positioning brands as irresistible objects of desire.
    • Carroll and Ahuvia (2006): hey described brand love as “the degree of passionate emotional attachment a satisfied consumer has for a particular trade name,” focusing on passion, attachment, and those warm, fuzzy feelings.
    • Albert et al. (2008): Expanded the framework with 11 dimensions, including trust, self-congruity, dreams, and memories.
    • Batra et al. (2012): Proposed a prototype-based definition, describing brand love as a relationship rather than a specific emotion.
    • Fournier and Alvarez (2012): Positioned brand love as central to consumer-brand relationships, emphasizing its relational dynamics.

Healthy Debate: Is Brand Love Too Much to Ask For?

As a marketer, I’m all about crafting strategies that hook consumers—but “love” has always felt like a stretch. At the end of the day, consumers want great products and services, and most brands? They’re here to turn a profit. That said, I’ve teared up at a Christmas ad or two, so maybe there’s something there.

Critics of the brand love concept, like Mark Ritson, have called it a myth. While he acknowledges its value, he warns against oversimplification, advocating for a balanced view that highlights loyalty and affection without exaggeration. Susan Fournier, a pioneer in consumer-brand relationship research, takes it further, arguing for a more nuanced understanding of these relationships—some of which can be negative, like dependencies or adversaries (aka toxic exes 😏).

Other scholars add to the debate. Fetscherin (2014) critiques brand love models for lacking predictive reliability, while the Ehrenberg-Bass Institute challenges the entire paradigm, suggesting that salience, not love, drives brand success.

So, is brand love real? Well, its a theory and like most theories, it’s evolving. Maybe AI is the secret sauce to building those deeper, more meaningful but also complex consumer connections we dream about.

How AI Is Redefining Brand Love

Digital tech gave marketers a treasure chest of tools—data, analytics, tracking—to understand consumers and, let’s be honest, nudge them emotionally. But with AI in the mix we’re talking about a whole new era of emotional engagement. AI can help brands move from being transactional to feeling genuinely human. By personalizing experiences, analyzing emotions, and predicting needs, AI can assist in making connections between consumers and brands that feel more meaningful than ever, maybe even intimate. Here are three ways I think AI is already reshaping brand-consumer relationships: through hyper-personalization, emotional intelligence, and anticipatory design.

1. Hyper-Personalization and Customization

AI’s real magic? Making every consumer feel like the one. By analyzing data, preferences, and behaviors, AI turns generic marketing into highly specific, crafted interactions. It’s not just about slapping your name on a promo email or suggesting products you’ve clicked on before—it’s deeper. AI dives into your vibe, mood, and is able to create moments that feel made just for you. Think of it as data alchemy: transforming cold numbers into emotional touch points that actually hit.

  • Spotify Wrapped: It might not be AI driven or assisted but for me this is a great example of using data to create a moment that feels both intimate and shareable. It’s not just about stats; it’s about connection, nostalgia, and the joy of seeing your quirks validated. Each year, Spotify analyzes its users’ listening habits and create personalized summaries of their music preferences. The Wrapped campaign doesn’t just reflect what users listened to—it tells a story about their year in music. For me it gives an amazing insight  the feeling of reminiscing about the year with a good friend. By offering a deeply personal experience, Spotify strengthens emotional bonds, turning data into a joyful, shareable moment.
  • TUI uses AI for personalized travel recommendations and creating conversational booking experiences. A chatbot powered by ChatGPT can bring a lot
    Source: https://skift.com/2023/12/08/tuis-ai-chatbot-puts-experiences-first/

    more information and recommendations about your trip than only departure times, ticket prices and room availability. Depending on details consumers provide on their likes (food, diving etc) in the conversation, the bot can then advise on excursions and things to do just for you.

Why it works: Personalization taps into a universal human desire: the need to feel seen and valued. When a brand “gets” you, it’s not just marketing—it’s trust-building. It makes you feel understood, which can inspire loyalty and turn casual customers into lifelong advocates. Would be some really interesting research to see if AI can really increase trust and loyalty. But at the very least a brand that taps into my exact needs at the right time will have me reaching for my wallet for sure.

2. Emotional Intelligence: Reading and Responding to Feelings in Real-Time

Handling data is one thing, but detecting emotions and responding in real-time? That’s next-level—and exactly where AI is headed. While still in its infancy, emotional intelligence in AI is redefining brand connections by analyzing facial expressions, vocal tones, social media sen

Paitoni, C. (2023). Robotics24. Emotion AI: Technology that understands our emotions.
Website: https://robotics24.net/blog/emotion-ai-technology-that-understands-our-emotions/

timent, and interaction patterns. The result? Interactions that feel intuitive, empathetic, and eerily human.

AI has already graduated from “press 1 for frustration” chatbots to systems that (almost) feel emotionally aware. It’s no longer just about personalization; it’s about emotional resonance—crafting interactions that meet consumers where they are, whether they need a pep talk, a bit of info that links to a hobby. a laugh, or just a little patience.

I think this capability of AI is still a while away, but these examples show we are heading there, it will become possible and commonplace:

  • Replika AI Companions: Designed for companionship, these chatbots offer empathetic responses tailored to users’ moods. While their primary focus is emotional support, they show how emotional intelligence can deepen consumer-brand interactions by fostering trust and care.
  • H&M’s AI Stylist: This chatbot goes beyond suggesting outfits—it asks about your mood and plans, tailoring recommendations to how you feel and what you need. Sure, this could fall under personalization, but the way it adjusts its tone and suggestions based on emotional cues feels like a step up. By learning from user interactions—likes, dislikes, or even hesitation—it refines its recommendations, creating an emotionally satisfying shopping experience.

Why It Works: Emotional intelligence transforms AI interactions from robotic to relatable. When a brand feels human—when it seems to understand your frustrations, celebrate your wins, or simply acknowledge your emotions—it builds trust and loyalty. These emotionally intelligent systems strengthen the consumer-brand bond, making interactions feel less transactional and more like genuine connections. It’s a glimpse of the future where brands aren’t just trying to sell—they’re showing they care.

3. Anticipatory Design: Knowing What You Need Before You Do

AI doesn’t just respond to consumers—it predicts what they’ll want or need next. AI algorithms analyze vast datasets to anticipate customer needs, predict future behaviors, and provide proactive recommendations. These systems transform historical data into forward-looking strategies that help brands understand and meet consumer desires before they are explicitly expressed. This is something most of us are familiar with already, while binge-watching on Netflix for instance and many eCommerce experiences already feature some kind of “maybe you also like this” category.

  • Amazon’s Alexa: Alexa anticipates user needs, from reordering household essentials to creating custom playlists.
  • Netflix Recommendations: Netflix’s algorithm predicts what you’ll love next, making content discovery seamless and satisfying.

Why It Works: Anticipation makes brands feel intuitive and reliable, like they’re really paying attention. But get too predictive, and you might hit the creepy “how do you know that about me?” zone. Balance is everything. With the right use of historical data and pattern recognition, AI can deliver proactive recommendations and marketing strategies that feel almost psychic—boosting ROI and making customers come back for more.

What’s Next? Agentic AI and the Future of Brand Love

If you think today’s AI is impressive, wait until agentic AI steps into the spotlight. Most current applications are reactive—they analyze, respond, and adapt when prompted. But agentic AI? It’s the overachiever that doesn’t wait to be asked. These systems don’t just react; they act, taking initiative, reasoning, and even planning based on what they learn over time. Most current AI applications are reactive, but agentic AI—systems that act autonomously—could take emotional branding to the next level.

Agentic AI doesn’t just wait for input—it learns, evolves, and takes initiative. It learns, evolves, and makes decisions autonomously, bridging the gap between passive tools and proactive agents. Unlike generative AI, which creates content, agentic AI takes actions that drive outcomes. Companies are already testing these capabilities in areas like sales, marketing, and customer service to create seamless, intelligent interactions (Forbes Technology Council, 2025).

How It Could Change the Game

  1. Proactive Engagement: Imagine a fitness brand’s AI that doesn’t just suggest workouts because it is time,  but notices when your motivation needs a pick me up and it sends you a personalized pep talk. Or a shopping assistant that starts looking for the best outfits once you’ve booked that trip.
  2. Emotional Adaptation: By analyzing real-time cues—like voice tone, expressions, or even stress levels—agentic AI could tailor its tone and responses to match a user’s emotions, creating interactions that feel authentic and empathetic. Think about a fitness app that not only sends you a ping when its time to work out notices when your motivation is low, or reschedules your PT while you are still in that meeting.

Conclusion: Can AI Create Brand Love?

AI might not make us love brands the way we love people—but it’s closer than ever. By personalizing interactions, demonstrating emotional intelligence, and even acting autonomously, AI will help brands move beyond transactions to create moments of connection that feel real.

However, there are limitations that AI may never fully overcome. While it can analyze emotions and tailor responses, it lacks genuine empathy—the ability to truly understand and feel emotions the way humans do. AI’s reliance on algorithms means it might occasionally misinterpret emotional cues or overstep boundaries, leading to interactions that feel awkward or inauthentic. Recognizing these limitations is essential for brands to set realistic expectations and avoid alienating consumers.

With great power comes great responsibility. As AI gets better at understanding emotions, knowing what we want, and learning so much about us in general, it’s crucial for brands to handle this power ethically. Transparency is non-negotiable—consumers need to know how their data is being used and give clear consent. And while AI can simulate emotional connections, maintaining authenticity is key. Nobody wants to feel like they’re talking to a robot that’s “trying too hard.”

Brand love may always have its skeptics, but with AI, brands have their best shot yet at turning the myth into reality.

Sources and further reading

Scientific articles and books

Marketing insights

Brands using to check for in-class examples:

Images created with Midjourney and special thanks to ChatGPT for AI-powered writing assistance for helping declutter and refine this post and Perplexity to find some additional sources. Sources are important to me, I do my best to include them all with working links. If you feel I have forgotten you, send me a DM on Linkedin

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