AI is overwhelming our senses—Edward Enninful has an answer for that

EE72 is positioning itself as an AI-adjacent media brand built on human curation, with founder Edward Enninful saying the company will not take ads and will keep humans in the lead. The article highlights partnerships with Google and Moncler, plus use of Google’s AI-powered try-on tool at New York Fashion Week, while an earlier Rihanna cover sold out online. Overall tone is positive toward AI as an enhancer of creative and commerce workflows, but the piece is largely commentary rather than price-sensitive news.

Analysis

The most important signal here is not “AI vs human,” but that premium content is trying to reprice scarcity around curation, trust, and distribution discipline. That is structurally favorable for platforms that provide high-conviction discovery or utility, not generic content factories: when attention is saturated, the market will pay for outputs that are visibly differentiated and operationally efficient. For GOOGL, the near-term read-through is that AI in retail and media is moving from novelty to conversion tooling; the monetization opportunity is less about headline AI features and more about higher ad efficiency, lower return rates, and better shopper confidence.

The second-order effect is pressure on mid-tier publishers and creator networks that rely on volume and algorithmic reach. If “slow digital” proves commercially viable, it implies a bifurcation: a small set of premium brands with loyal audiences and a long tail of undifferentiated content businesses facing deteriorating CPMs and higher content costs. That is bearish for ad-supported media monetization broadly over the next 6–18 months, while being modestly positive for companies that can own the trust layer, tooling layer, or recommendation layer.

For GOOGL specifically, the risk/reward is asymmetric but not immediate. The upside catalyst is product pull-through from AI-assisted commerce and virtual try-on into measurable retail conversion; the downside is that consumer acceptance of AI-enhanced experiences could remain localized and fail to scale beyond fashion/beauty niches. A bigger medium-term risk is regulatory and brand-safety scrutiny if AI content starts to be perceived as deceptive rather than helpful, which could slow adoption and cap multiple expansion.

Consensus seems to underappreciate that AI may increase demand for human-made premium content rather than replace it outright. The real competitive moat is not generation capacity, but editorial taste and distribution trust — a dynamic that should benefit scarce brands, while commoditizing “good enough” content. That implies the current market may be overpricing broad AI exposure and underpricing selective winners in commerce-enablement and premium media curation.

Key Decisions for Investors

• Long GOOGL on a 3–6 month horizon via common stock or call spreads: thesis is incremental monetization from AI-assisted shopping/retail utility and higher engagement quality; stop if ad-product adoption data or retailer rollout cadence disappoints.
• Short a basket of ad-dependent, mid-tier digital publishers over the next 6–12 months: expect CPM pressure and audience fragmentation as premium curation wins share; use a basket to avoid idiosyncratic risk.
• Pair trade: long GOOGL / short IAC or another undifferentiated content platform over 1–2 quarters, targeting a relative re-rating as utility-driven AI wins over volume-driven media models.
• Buy out-of-the-money GOOGL calls into the next product cycle if there is evidence of retail adoption inflection; risk/reward improves if management starts quantifying conversion lift rather than just feature launches.
• Avoid chasing broad AI media beneficiaries here; favor businesses with measurable conversion or trust economics, as the market is likely to fade generic AI hype over the next 60–90 days.