AI Moves Into Apparel’s Inventory Decisions, With Guardrails

By Tom Whitfield

Aily Labs has developed a Fashion Momentum Index that compares fashion-show moments with business performance, giving apparel companies a claimed basis for deciding where to invest. No customer deal, pricing, rollout schedule or measured result accompanied the announcement.

At the WWD Apparel and Retail CEO Summit, Aily Labs founder and chief executive officer Bianca Anghelina discussed AI decision support with Fairchild Media Group chief executive officer Amanda Smith. Their fireside chat formed a special episode of WWD Voices.

Anghelina described AI-powered decision-making as a competitive differentiator for retail operations, with potential gains in customer experience, inventory use and speed of response. She said: “The winners will turn out who are brave to actually let some of the old ways of working drop and take some bets with AI.” The statement sets a strategic direction, not an operating result.

What exactly is Aily Labs selling?

Anghelina compared the technology to a business version of a fitness tracker: it collects data and provides insights that help users move toward goals. Aily’s system draws on data from a company’s operations and value chain, plus external data. The intended users extend from the chief executive to the wider organization.

That breadth makes the unanswered question larger. The presentation identified no customer deployments, independent performance study, number of users or implementation cost. It also did not say whether customers pay per user, per company or for data feeds and integrations. Those omissions prevent a buyer from calculating the tool’s commercial burden.

Where AI should stop

Anghelina said AI should not intrude on creativity or the customer experience. Her proposed division of labor is straightforward: automate optimization elsewhere so fashion companies can invest more in those human-led activities. She also said AI may not suit designing a collection, a limit that narrows the pitch from replacement to decision support.

The more immediate commercial claim concerns inventory. Aily’s automated suggestions can reallocate and optimize stock, which Anghelina said can materially affect sales. No sales figure, margin change or comparison period accompanied that claim, so the size of the benefit remains unmeasured rather than proven.

Aily can also run scenarios, letting companies assess the likely effect of an action before taking it. This is the clearest potential cost-control use in the discussion because it places a proposed inventory action against likely business effects before execution. The presentation did not explain how the scenarios are built or which inputs carry the greatest weight.

For apparel, the Fashion Momentum Index tracks moments such as fashion shows against performance, with the stated aim of helping companies focus investment. Anghelina summarized the proposition as follows: “AI can help to say, ‘What do you do next?’” The index turns event timing and business outcomes into a decision prompt, though no calculation method or validation is disclosed.

What changes for apparel decision-makers?

The practical change is a proposed planning layer around allocation, scenario testing and investment timing, not an automated design function. For buyers and retailers, that could matter where stock commitments, reallocation rules and markdown exposure are decided. Neither Anghelina nor the presentation specified whether Aily accounts for supplier lead times, landed cost or compliance constraints.

The answer, therefore, is conditional rather than expansive. Aily has described tools that could shorten the distance between operating data and a management decision, but has not supplied the evidence needed to judge return on investment. The WWD format offered a founder’s thesis and a product outline, not a deployment review with named buyers, rollout dates or measured results.

Before Aily’s recommendations can influence apparel buys or allocations, the next test should be a named customer installation with stated cost, governance and data requirements, followed by a measured inventory or sales result on a dated rollout.