Today’s read: 5 minutes
May 1, 2026: Brand identity, “dupe” strategy, AI claims, likeness rights, and pricing control are all being tested – and not in isolation. Across cases and filings this week, the question is less about individual rights and more about whether companies are stepping into the recognition, positioning, or value frameworks built by others.
Taylor Swift is helping to shape a legal playbook for protecting likeness in the age of AI. In new trademark applications, her company is seeking registrations for two short voice clips – “Hey, it’s Taylor Swift” and “Hey, it’s Taylor” – along with a single Eras Tour performance image.
The applications (filed by Venable’s Rebecca Liebowitz) fit into a growing effort by public figures to expand beyond names, signatures, and logos, adding more elements of identity into the trademark system. While trademark law does not protect likeness in the abstract, it can protect uses that function as source identifiers.
>> In practice: Likeness is being broken down into pieces that can be defined, registered, and enforced. That makes this approach narrower than a broad right of publicity claim but may prove more workable in commercial settings. If registered, marks like these can provide a clearer basis to challenge unauthorized uses of specific elements – including in AI-generated or digitally replicated content – without relying solely on state-by-state likeness claims.
The result could be a shift toward more modular IP portfolios, as identity becomes easier to replicate.
Two beauty disputes this week – Squish v. Coty Inc. and Glow Recipe v. MCoBeauty – turn on the same question: how far a competitor can go in adopting the elements that make a product recognizable. In Squish’s case, the claim is not limited to the “SQUISHY” name. It points to overlapping packaging, imagery, and marketing, arguing that those elements together make the products appear connected.
Glow Recipe takes a similar approach, citing “dew”-focused naming, pink packaging, comparison-style content, and keyword advertising to argue that the accused product does more than resemble its Dew Drops serum – it competes in the same discovery flow.
Taken together, the focus shifts away from names or packaging in isolation and toward how consumers encounter products across channels.
This is not new. Earlier cases (the since-settled Daily Harvest v. Revive Organics case comes to mind) have made similar arguments about copying website design and brand presentation rather than products themselves. What is changing is where it is showing up. The same logic is now being applied to “dupe” strategies in beauty, where recognition is built across naming, visuals, and platform-specific marketing.
>> The takeaway: The line is moving from copying products to replicating recognition systems. And so, the risk is no longer just similarity in design or naming, but whether a competitor can adopt the same mix of visual, linguistic, and marketing cues to capture demand at the point of discovery.
Allbirds has been met with no shortage of criticism in pivot from sneaker-maker to AI infrastructure company “NewBird AI.” The backlash comes against the backdrop of a market in which “AI” is not just a fluffy marketing term but a claim that can carry legal and financial weight.
Across retail, companies are invoking AI to describe personalization, inventory systems, marketing automation, etc. But the underlying reality is often more fragmented – a mix of tools, processes, and human oversight – and the gap there is where risk emerges.
Regulators, including the SEC, are already signaling that:
> AI-related statements fall under existing anti-fraud frameworks
> There is no separate standard for emerging tech
> Tech-centric claims must be accurate and substantiated
This mirrors earlier “washing” cycles, but with a key difference: AI claims tie directly to performance, valuation, and growth expectations.
>> In practice: “AI-forward” is no longer just branding language. It is a representation that companies will be expected to prove – to regulators, investors, and increasingly skeptical consumers.
A widely-reported lawsuit against Stella McCartney and LVMH adds another layer to the question of luxury-level control. While the case is framed as an employment dispute (a VP is waging unequal pay, discrimination, and retaliation claims), the underreported aspect of the case is the allegations that executives were pressured to participate in coordinated pricing practices – including halting shipments to push retailers toward price increases.
The case stops short of asserting standalone antitrust claims but situates the alleged conduct within an equation we frequently touch on: brand-driven price harmonization vs. competition law constraints. It also raises a practical issue: centralized control across markets may collide with local legal regimes, particularly where pricing autonomy is restricted.
>> The takeaway: Pricing isn’t just about setting prices. When brands push retailers to follow certain pricing or act in coordination, it can raise legal issues beyond antitrust, including employment and compliance risks.
This week’s stories point to a common shift: value is increasingly tied to things that are hard to claim outright, but critical to how products compete in the market.
In beauty, the fight is over recognition – not just what a product looks like, but the mix of cues that make it identifiable at the moment of discovery. In Swift’s filings, it shows up in the opposite direction, as an effort to define identity more precisely, breaking it into elements that can be registered and enforced. And in AI-related claims, the issue is not adoption, but substantiation – whether what companies say about their capabilities matches what they are actually doing.
What ties these together is a shift in how companies are defining what they’re actually claiming. In the beauty cases, brands are pointing to a mix of naming, packaging, and marketing to show how products are recognized. In Swift’s filings, identity is broken into specific elements that can be registered and enforced. And in AI, the issue is whether companies can back up what they are saying about their capabilities.