What's generative AI doing to brands?
Disruption is coming fast.
I’ve been a brand strategist for almost a decade now. It’s near and dear to me. As generative AI has taken off, I’ve seen a ton of thought about disruption across virtually every industry, but one place I haven’t seen a lot of thinking has been in assessing brand disruption across two key areas:
Disruption to the creative and strategic process of developing and managing a brand
Disruption of the consumer-brand dynamic
Based on my experience, job interviews, and candid conversations with mentors, I think this lack of assessment is partly due to the industry not moving quickly enough. Let’s call it for what it is: firms aren’t moving quickly because change is hard. I don’t want to take away from the brand leaders on the cutting edge, either. I see you out there. But to really thrive during this wave of disruption, it’s time for more leaders to take a holistic look at the implications to drive more effective change. We’re moving towards augmented brands, and that means augmented teams and strategies need to get ahead of this.
First, some context-setting
A brand is the living, breathing personification of a company or product. It’s not just a logo or a tagline, but a complex web of perceptions, experiences, and emotions that exist in the minds of consumers. Brand managers have long been the shepherds of this intangible, amorphous asset, carefully nurturing and steering consumer perception. But their “control” has always been somewhat of an illusion – a matter of degree and not of kind — because true brand identity has always been defined by the collective consciousness of its audience. It’s this delicate balance of control that has always been at the center of building great brands. It’s never about total control, rather, consumers should help shape brands, and a key component of great brand management is listening and responding to consumers.
So what happens when Generative AI is thrown into this dynamic? How will deeper personalization impact brand authenticity? How can brand teams maintain the balance of control over their brand’s identity in a world where consumers have the tools to shape and influence brands in a previously unimaginable way? In this series of three (maybe four) posts, we’ll explore these questions and more, examining how Generative AI is rewriting the rules of engagement—from immediate disruptions to long-term transformations.
To analyze the impact of Generative AI on branding, we can start by examining its cascading effects on how brands connect, create, and grow over time, focusing on the following six components of the brand value chain:
Brand Strategy Development
Brand Identity Creation
Brand Positioning
Brand Communication
Brand Experience Delivery
Brand Equity Management
In this first article, we will focus on the first-order effects—the tangible, immediate changes happening right now—charting the impact through each component of the value chain. This is Prompt Thinking, so we’ll of course use gen AI to make some cool prototypes along the way, showing just how close we are to these applications becoming readily available and user-friendly for both consumers and brand managers. In later articles, we will unpack the second and third-order effects, thinking about what the near-future implications hold.
Part 1: Brand Strategy Development
Generative AI will fundamentally transform how brand managers articulate and develop their strategy. Brand strategists are already getting access to large language models (LLMs) customized and trained on brand IP, business needs, and consumer insights that simply were not integrated and actionable before. Soon, organizations will invest in building fully customized LLMs that are trained on all brand-related content, tone, guidelines, campaign elements, and more, enabling them to think like a personified version of the brand. Brand managers will be able to talk to their brand. This “brand agent” will be able to act as a sidekick, helping to pressure-test strategies, generate new ideas, and provide competitive analysis on demand.
For example, let’s look at a simplified GPT I created for Coca-Cola. I trained it on all of Coca-Cola’s publically available information about the brand, identity, campaign, and other high-level details. Based on this information, here’s how it performs when asked to create a campaign for the Christmas season:
The example above uses very minimal data. Now imagine when companies are building fully customized LLMs and diffusion models with their entire IP catalog and strategies, and then deploying that across their teams. Brand teams will need to be upskilled to augment their capabilities with gen AI while maintaining a strong emphasis on creative differentiation. The critical factor here and along all aspects of brand strategy remains the “human in the loop”. Strategists will be more important than ever as they will provide empathy, cultural relevance, and client context into the deliverables. Agents like this will only make brand experts more valuable, because ultimately, as we will see, the depth and breadth of branding’s scope will multiply as gen AI will scale to deliver a more personalized, rich, and powerful brand experience for consumers.
Disruption Meter: Medium - The disruptions here are significant but manageable with the right balance of AI and human input. While AI greatly enhances agility and insight generation, the need for a creative human touch remains essential to avoid bland, homogeneous branding.
Part 2: Brand Identity Creation
Brand identity—the visual and verbal elements that embody the brand’s personality—is where Generative AI is already having an outsized impact. Tools like Midjourney, Stable Diffusion, Pencil, and Runway allow creative teams to produce design concepts, mood boards, and branding assets in a fraction of the time it used to take. The creative cycle can now be compressed from weeks to days. That’s concerning. Because it does lead to a productivity trap for managers. If timelines are protected, this will allow for more depth of thought and the team has the opportunity to drastically improve in quality of content. But if this is viewed as simply automation and productivity achievement, then we run into a potential disaster as teams shrink and “AI-generated” brands diminish the quality and authenticity of brands.
Let’s look at an example: Imagine a luxury eco-friendly skincare brand aiming to create a new visual identity system for product packaging. Using Midjourney, it’s fairly easy to generate multiple visual identity mood boards based on themes like "minimalist nature," "sustainable luxury," and "urban eco-chic." Each of these mood boards can be generated within minutes, allowing the creative team to rapidly explore different aesthetics and directions.
Prompt: A luxury skincare brand mood board focusing on minimalist nature, featuring soft pastel color palettes, organic textures, and botanical elements. Clean, open space with white and earth tones, subtle branding, smooth fonts, and natural imagery. Created using: soft-focus photography, flat lay design, modern minimalism, nature-inspired branding, soft shadows, organic textures, light wooden surfaces, hd quality --ar 16:9 --v 6.0
Prompt: A luxurious and sustainable skincare mood board, highlighting premium, eco-friendly packaging in natural hues of green and gold, with high-end typography and intricate botanical motifs. Elegant, recyclable materials paired with a calm, balanced layout. Created using: metallic accents, eco-friendly luxury branding, sustainable packaging design, muted greens, organic forms, balanced lighting, hd quality --ar 16:9 --v 6.0
Prompt: An urban eco-chic skincare brand mood board, blending sleek city vibes with eco-conscious design, featuring muted industrial grays, vibrant greenery, and minimalist, modern typography. Sustainable urban aesthetics with clean, eco-luxury appeal. Created using: modern urban textures, concrete, greenery, eco-chic styling, bold fonts, muted industrial palette, natural light, sleek packaging, hd quality --ar 16:9 --v 6.0
From here, you could then iterate on these AI-generated designs by adding brand-specific elements such as unique color palettes inspired by natural ingredients. This not only speeds up the creative process but also ensures that the brand's unique values are reflected in the visuals. Having this much speed and scale is a superpower for creatives, giving them time to evaluate and refine as needed.
Brand managers need to rethink their approach to creative development, focusing on how to best augment creatives with AI models to supercharge their creative output while preserving the essence of the human-driven creative process. AI augmentation can enhance efficiency, but human creatives must lead with a clear vision to maintain authenticity. Teams should leverage AI to explore design variations, generate ideas, and accelerate production, but again, the designer needs to provide oversight to guide final decisions.
Disruption Meter: High - The level of disruption here is high due to the democratization of creative tools and the risk of losing control over brand assets. Brands must be proactive in leveraging AI for creative augmentation while maintaining strong oversight. This requires a deliberate approach to ensure AI-generated content aligns with brand standards and does not compromise brand identity.
Part 3: Brand Positioning
Brand positioning traditionally falls in with brand strategy, but there’s a caveat here. By conducting brand positioning in an augmented way - training models or GPTs on the current positioning of a brand and the competitive category - will enable brand managers to craft messaging that speaks directly from its analysis of the category and identified white space. AI tools such as ChatGPT and Jasper allow brand teams to generate nuanced content variations tailored to different consumer archetypes, ensuring that each segment feels personally addressed by the brand’s messaging.
Consider a shoe and apparel brand aiming to position itself differently across multiple consumer segments. To simulate this, I built a brand positioning GPT, which allows the user to analyze aspects of each competitor - the logo, tone, taglines, campaigns, and other visual identity aspects- and ultimately make a recommendation to identify white space.
Implications for Brand Teams: Brand teams can utilize tools like this to enhance the precision of their positioning efforts while ensuring that all communication ties back to the brand's core story. While this use case shows the unprecedented opportunity for deeper analysis, brand strategists need to leverage AI as a tool for personalization while ensuring that teams provide the necessary oversight to retain consistency and authenticity in recommendations.
Disruption Meter: Medium - The disruption level is medium, as AI-driven hyper-personalization presents both opportunities and challenges. The key is managing personalization without fragmenting the brand identity. Teams must strike a careful balance, ensuring that AI augments positioning efforts without compromising the overall brand narrative.
4. Brand Communication
Brand communication has been one of the earliest areas of disruption, with tools like ChatGPT allowing marketers to generate high-quality, personalized content at scale, significantly reducing dependency on traditional agencies. This shift has shortened production cycles, enabling brands to respond swiftly to market changes with adaptive messaging and dynamic campaigns.
Example Case: Consider a retail brand launching a seasonal campaign. By using tools like ChatGPT or Pencil, the marketing team can generate personalized email campaigns, social media posts, and product descriptions tailored to different customer segments. This requires a ton of work on the personalization front. I’ll be the first to admit that LLMs are notorious for writing terrible copy. But this process of augmenting the existing creative teams holds the real opportunity. This approach allows the brand to deploy hyper-personalized communications at scale but carries the big warning label that simple automation is NOT the answer. There is a major risk of losing the brand's distinct tone of voice, or outright producing bad content. The challenge lies in ensuring that even AI-generated content is used to supercharge creatives, not replace them.
Implications for Brand Teams: Brand teams must redefine their workflows to integrate AI tools seamlessly, allowing for rapid content production while ensuring that brand messaging retains its unique character. Augmentation is key—AI can provide the scale, but humans must provide the nuance. Brand teams should focus on training their own AI models or customizing frontier models on their specific brand tone and guidelines, while creative leads should provide oversight to maintain consistency across channels.
Disruption Meter: High - The disruption here is high, as AI's role in content creation introduces efficiency and adaptability but also demands careful oversight to prevent loss of brand voice. The key is to leverage AI for scale without compromising the human touch that makes brand communication authentic and engaging.
Brand Experience Delivery
Generative AI is transforming brand experience delivery by enabling more dynamic and interactive consumer touchpoints. AI-driven personalization means every interaction—from customer service chatbots to product recommendations—can be customized to individual preferences, making the brand experience feel more intuitive, relevant, and seamless.
Example Case: Imagine a travel company that wants to create a highly personalized experience for its customers. By integrating an AI-driven recommendation system, the company can provide tailored vacation suggestions, real-time travel support, and even personalized itineraries based on past preferences and behaviors. This wouldn’t be the traditional feel of an ML-driven recommendation engine, instead, it would feel like a travel agent that the consumer could work with to curate their experience. This is already happening at scale and key players in the industry are already working on this.
However, this level of personalization also raises consumer expectations. Customers now anticipate every interaction to be frictionless and tailored, which increases the pressure on brands to ensure consistency across all touchpoints. To meet these expectations, brand managers must align AI-driven experiences with the brand’s core values and ensure seamless integration across channels.
Implications for Brand Teams: Brand teams need to rethink how they approach consumer interactions, integrating AI to enhance touchpoints while ensuring that these experiences consistently reflect the brand promise. AI can enhance responsiveness and personalization, but teams must maintain oversight to align each experience with the brand's overarching narrative. AI mustn’t lead to fragmented experiences—every interaction should be part of a cohesive consumer journey.
Disruption Meter: High - The disruption here is high due to the increasing consumer expectation for personalized, consistent experiences. Brand teams must be proactive in managing these AI-driven interactions to ensure that they are always aligned with the brand’s core promise, making sure that technology enhances rather than diminishes the human element of brand experience.
6. Brand Equity Management
Brand equity management is perhaps the most complex area affected by Generative AI. User-generated content, powered by AI, allows consumers to shape the brand narrative in ways that are both exciting and unpredictable. This can boost authenticity and foster deeper loyalty, as consumers feel a sense of ownership over the brand.
Example Case: Let’s say a person using Midjourney creates a concept for a Star Wars x Nike shoe line. They post it on social media, and it quickly goes viral, generating significant buzz and consumer demand. Is this a problem or an opportunity?
While this kind of user-generated content can create excitement and engagement, it poses challenges for brand control. Nike never officially endorsed this collaboration, yet the public's enthusiasm can lead to confusion or disappointment if the product isn’t realized. This lack of control over the brand narrative is something brands need to carefully manage in the era of AI-generated content. Surely this isn’t possible, right? Well, look at what I was able to make in less than 30 minutes:
Implications for Brand Teams: Brand managers need to establish frameworks that balance creative freedom with brand integrity. Brands that are sitting on a bank of rich IP might consider developing their digital ecosystems to allow a more controlled space for consumers to play with their brand-approved products - generating NFTs, digital and gaming-centered products that would allow for an unprecedented area to foster deep connections with the niche groups, it's essential to clearly distinguish between fan-made content and official brand assets. Brands should look at this as a way to crowdsource ideas and track interest, it’s a huge market of untapped creatives that are co-creating and shaping the brands they love in their image.
Disruption Meter: High - The level of disruption is high due to the unpredictability of user-generated content and the potential for loss of brand control. Brands must proactively create systems to manage and leverage consumer enthusiasm while protecting the consistency and integrity of the brand. This requires thoughtful engagement strategies that celebrate creativity but also maintain clear distinctions between fan concepts and official products.
Key Takeaways: Embracing Both Opportunity and Responsibility
Generative AI is fundamentally transforming how brands develop strategy, shape identity, position themselves, communicate, deliver experiences, and manage equity. It opens up unprecedented opportunities for creativity, hyper-personalization, and consumer engagement—but these opportunities are accompanied by significant challenges. Brands that successfully navigate this landscape will do so by balancing the immense possibilities that AI provides with the imperative of maintaining brand integrity. Those who manage this balance will not only adapt but lead in this new era. The future of branding must be scalable, deeply engaging, and authentically human, blending the best of technology with irreplaceable human insight.
In the next installment, we'll explore the second-order effects of Generative AI—how it’s reshaping internal structures, shifting roles, and redefining resource allocation to set the stage for long-term transformation.