Headlines have focused on Disney’s billion-dollar investment in OpenAI and speculated why Disney chose OpenAI over Google, which it is suing over alleged copyright infringement. While these questions matter, the more important issue for marketers is what this partnership reveals about the future economics of content, advertising, and audience attention. Disney partnered with OpenAI not to create better creative content but to enable average creative work to operate at massive scale—a crucial distinction. To recap: Disney licensed over 200 characters from Marvel, Pixar, Star Wars, and its classic catalog to OpenAI’s generative systems like Sora and ChatGPT’s image tools. In exchange, Disney took an equity stake in an exclusive partnership. Though the dollar amount made headlines, the true currency is Disney’s intellectual property. OpenAI gains access to exclusive content that enhances user engagement and stickiness. Familiar characters evoke emotional connections that generic AI output cannot replicate, encouraging users to stay engaged, experiment, and create. For Disney, this move isn’t about immediate revenue but strategic positioning. After a century of monetizing IP by controlling its timing and appearance, Disney is now embedding its characters within systems optimized for speed, scale, and iteration. Marketers should pause here. Generative AI is often seen just as a tool for faster, cheaper production, but this overlooks a deeper shift in how meaning circulates. According to James Kirkham, co-founder of brand consultancy Iconic, when characters become embedded inside generative systems, they cease to be “event-based, ” becoming instead “environmental. ” They can appear anywhere, with any tone, next to any content, increasing speed and frequency. While this scale is attractive, it is also destabilizing. Kirkham warns the bigger threat than low-quality AI output is the normalization of “just good enough” creative produced massively. Platforms like Sora make it easy to capture minimal attention without the craftsmanship traditionally expected. This trains audiences to accept less, leading to content becoming predictable, noisy, and monotonous, thereby eroding the premium tier where agencies and brands competed on originality and judgment. The power of brand assets traditionally comes from context — deliberately staged narratives that reinforce authority and intent. Generative systems remove these guardrails, making context optional, increasing frequency but reducing specificity. This risks ushering in a “just good enough” economy. Brands must critically decide which work merits investment, time, and human judgment, and which is disposable. Criticism of AI-generated content as formulaic and synthetic captures “AI slop” but misses the economic mechanism behind it. Generative AI lowers barriers to “watchable enough” content that holds minimal attention— not great or distinctive storytelling, but functional content that keeps feeds moving. At scale, this retrains audience expectations downward without overt awareness. Content becomes more interchangeable and noisier, thinning the premium layer where brands and agencies excelled in creativity. Thus, the threat is not poor quality but competent creative at massive scale establishing the default aesthetic. Brands face a strategic choice: either treat characters as flexible assets designed for fast, adaptive, disposable environments, or maintain them as rare, deliberate cultural symbols. Doing both simultaneously is difficult.

Once characters become ambient, context-free, and endlessly generated, they lose ownership and authority, spreading like memes. Kirkham emphasizes brands must set boundaries now before platforms impose them, as reclaiming meaning afterward is challenging. This context drives a shift in advertising economics. Historically, one key barrier preventing technology platforms from capturing more TV ad budgets is content economics—TV-quality programming is costly, slow, and culturally misaligned with automated platforms. Even streaming platforms have inherited these costs. Generative AI transforms this dynamic. If viewing habits shift toward AI-generated content optimized for economies of scale over human labor, content becomes a commodity, and economics start to resemble cloud computing more than Hollywood production. Here, success isn’t measured by best-in-class work but by efficiently occupying viewer time. Two hours of daily viewing don’t require two hours of premium storytelling, but two hours of frictionless, watchable content that meets a minimum attention threshold. Generative systems already achieve this and improve rapidly. Should platforms shift viewing time to AI-generated content under their control and demand advertising dollars proportional to audience share, it could unlock budgets traditionally reserved for television. Opening TV budgets to this model is just the first effect; the second, more profound effect is a redefinition of brand meaning—from an outcome to an input. The “just good enough” economy leverages familiar brand elements to legitimize average content at scale. Key figures to note: - $2 billion: Sales achieved by Platform X in the first nine months of 2025 - 30, 000: Peak viewers of Kim Kardashian’s Skims TikTok Live shopping event - 2029: Year Oscars will shift exclusive broadcasting rights from ABC to YouTube - $100 billion: OpenAI’s targeted funding raise to sustain AI model training and operations Recent reads include: - Meta tolerates significant ad fraud from China to preserve billions in revenue; about 19% of Chinese ad money in 2024 involved scams and banned content (Reuters). - OpenAI contemplates raising up to $100 billion at a valuation near $750 billion to fund AI development (The Information). - Kim Kardashian’s Skims brand boosts TikTok Live’s status in U. S. shopping, attracting 30, 000 viewers at peak (Bloomberg). - Oscars will be exclusively broadcast on YouTube from 2029 to 2033, reflecting shifting viewing habits away from linear TV (Axios). Recent coverage highlights: - Pinterest’s acquisition of tvScientific signals its push into connected TV ads with performance-based models. - YouTube is increasingly targeting TV ad budgets with an evolved selling approach aligned to its dominant watch time and video viewing. - Ebiquity’s new chief marketing effectiveness officer role signals marketing’s focus shift from metrics toward meaning and guided decision-making. - The NBA is expanding in Europe by leveraging sponsorships, meeting partners’ expectations, and capitalizing on growth momentum. In conclusion, Disney’s OpenAI deal underscores a transformative shift in content economics, brand meaning, and ad strategy, marking a move toward scalable, “just good enough” AI-driven content that challenges traditional creative craftsmanship and brand control. Marketers must grapple with these changes to strategically position their brands in a rapidly evolving landscape.