The Future of Marketing With AI and Attention | Adweek Interview
When Hype Meets Habit: What Founders Learned from NFTs That Now Shapes Thinking About AI
There is a familiar rhythm to new technologies: an initial frenzy, a reputational hangover, and then a slow, practical assimilation into everyday life. That pattern played out publicly with NFTs and is now unfolding with generative artificial intelligence. What once felt like speculative day trading of digital trinkets has matured into a broader conversation about provenance, trust and the cultural meaning of creativity. The stakes are no longer only financial; they are social, legal and deeply personal.
Provenance as a Social Contract
One clear lesson from the blockchain era is that provenance matters. NFTs exposed a friction point that had been invisible in the analog world: how do we know who created something and when? With AI’s capacity to produce photorealistic video and fluent-sounding voice clones, that question has become urgent. The proposal to anchor original content to immutable ledgers reframes authenticity as an infrastructure problem rather than merely an artistic debate.
Trust, not just technology
Giving consumers an on-ramp to verify origin—whether through a tokenized timestamp or a persistent digital signature—repositions trust as something brands and creators can build into their work. That shift matters because it converts a cultural panic about deepfakes into a solvable design challenge: how to make verifiable truth as easy to access as a play button.
Consumers Will Both Fear and Embrace Automation
Fear of displacement is real. The narrative that robots will replace jobs has followed every major leap in labor technology. But history also shows a pattern of coexistence and reinvention. Musicians who once relied on studio gatekeepers now experiment with new tools; chefs still insist their food is authentic even when marketing enhances the plate. Many consumers will distrust generative outputs at first, yet others—especially younger cohorts—may never remember life without AI augmentation.
Layered value for art and craft
Human-made art and algorithmic creation will not be mutually exclusive. Cultural value is rarely determined by purity alone; it is negotiated in marketplaces, communities and personal tastes. Some audiences will prize the artisanal violinist, others will celebrate the laptop-produced anthem, and many will do both. This duality will shape careers, festivals and marketing plans as creators decide which parts of their practice to keep tactile and which to scale with code.
Brands Walk a Thin Line Between Ethics and Competition
Major consumer brands are wrestling with public commitments that may be admirable but strategically risky. Pledges to avoid generated humans or synthetic spokespeople sound principled, yet they also set the stage for future commercial trade-offs. If generative assets become a cost-efficient way to serve consumers at scale, brands that refuse to experiment may cede ground to more flexible rivals.
Policy before panic
For marketers, the pragmatic path lies in measured experimentation coupled with legal clarity. Decisions about when to substitute AI for human labor must reckon with trademark, copyright and reputational risk. In practice that means pilot programs, transparent labeling and corporate governance that treats content provenance as a compliance issue, not just a creative brief.
The Algorithmic Habitat and the Fragmented Public Sphere
Algorithms did not invent fragmentation, but they accelerated its scale and narrowed the shared cultural moments of mass media. Fragmentation reshapes civic conversation, commercial discovery and even friendship. As feeds become tailored, the old social glue of a single primetime program or front-page headline loosens, producing both niche intimacy and communal erosion. The counterweight may be intentional curiosity: a renewed social discipline to engage with others’ tastes.
Designing for shared experiences
Platforms and creators may find new value in engineering moments of overlap—short, simple experiences that invite strangers into a common frame. Whether that becomes a business model or a social corrective will depend on cultural incentives and the human appetite for connection beyond algorithmic comfort zones.
Advertising, Authenticity and the Next Creative Economy
Advertisers are already experimenting with hyper-personalized creative, using data to tailor versions of a spot to many unique audiences. Generative tools accelerate that capability but also raise questions about ownership and truth. The industry that once called Madison Avenue is now forced to negotiate with engineers and IP lawyers about what a truthful advertisement even is in a world of synthetic visuals.
Human judgement as the durable skill
As production becomes cheaper and volumetric, strategic taste—knowing which moments to humanize, which to automate and when to declare provenance—becomes a scarce asset. The companies that thrive will be those that treat authenticity as a product attribute and human judgment as a core competency.
Culture, History and the Long Arc of Acceptance
Every new creative tool has faced cultural resistance. Canvas painting, recorded music and photo editing each had detractors. The pattern is instructive: initial hostility, institutional debate, and eventual normalization with pockets of elevated human craft. The present moment is not the end of art’s authority; it is an inflection point that will reorder who holds cultural capital and how people define trust in media.
Reflective note: The essential tension is not between humans and machines, but between immediacy and veracity; building systems that honor both will determine whether the next decade feels like empowerment or erosion.
Insights
- Treat provenance as a design problem: integrate verifiable metadata into content workflows.
- Adopt a phased approach to generative tools—pilot internally, label outputs, and measure brand impact.
- Preserve human-led creative roles by differentiating tactile craftsmanship from scalable AI-generated work.
- Prepare legal frameworks now by mapping data sources and documenting training inputs for generative models.
- Design marketing experiences that create moments of shared attention in an increasingly fragmented media landscape.
- Educate stakeholders with concrete demonstrations of generative outputs to reduce irrational fear and inform policy.




