What new AI roles do fashion companies need, and what do they actually do?

Fashion companies are adding a small set of new AI roles: an executive owner who sets priorities and budget, AI product owners who turn use cases into working tools, data and governance roles who keep inputs reliable and usage compliant, and champions inside each team who drive daily adoption. Job titles vary widely, but the responsibilities behind them are becoming consistent.

Why are fashion companies creating new AI roles at all?

For most of the last decade, analytics and machine learning sat with IT or a small data science team. Generative AI changed the picture because almost every function, from design and copywriting to planning, customer service and sales, can now use AI tools directly. McKinsey's State of Fashion 2026 report, published in November 2025, says more than 35 percent of fashion executives report already using generative AI in functions such as customer service, image creation, copywriting and product discovery, and describes AI as shifting from a competitive edge to a business necessity.

The same report argues that some existing jobs are becoming more AI-centric, and that companies need to redesign processes and compete for AI talent beyond the fashion ecosystem. When usage spreads across departments, someone has to decide which use cases deserve investment, who owns the data each one depends on, and how employees learn to use the tools safely. That is what the new roles are for.

What does a chief AI officer do in a fashion company?

At the top sits an executive who owns the AI agenda. Some companies give this to the chief information or chief digital officer; others create a dedicated post. Lululemon named Ranju Das as its first Chief AI and Technology Officer, a newly created position effective 2 September 2025, reporting to CEO Calvin McDonald, according to Retail TouchPoints. The company linked the role to advancing product innovation, improving agility and speed to market, and bringing more engagement and personalisation to the guest experience. The appointment coincided with the planned departure of its CIO, which shows that such roles often merge AI with broader technology leadership rather than sitting beside it.

In practice the executive owner is accountable for a short list of priorities, the budget, the vendor strategy and the risk framework. The title matters less than the mandate: without authority over data, budget and process change, a senior AI role becomes an advisory post.

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Which AI roles sit below the executive level?

Below the executive layer, the roles fall into recognisable groups. The table summarises what each typically owns.

Gartner's survey of 321 customer service and support leaders, conducted in October 2025, gives a sense of how common this is: 42 percent of organisations were hiring specialised roles such as AI strategists, conversational AI designers and automation analysts to support AI deployment. The same survey found only 20 percent had reduced agent staffing because of AI, which suggests that new roles are being added around existing teams rather than replacing them wholesale.

Who owns AI training and literacy?

Training has become a defined responsibility for a legal as well as a practical reason. Article 4 of the EU AI Act has applied since 2 February 2025 and requires providers and deployers of AI systems to take measures to support AI literacy among staff and others operating AI on their behalf. The European Commission's guidance says no certificate is required and organisations can keep internal records of training instead; supervision by national authorities starts in August 2026.

Some retailers have built formal programmes. FashionUnited reported in August 2025 that Debenhams Group launched an AI Skills Academy with the workforce development platform Multiverse, open to all employees and funded from its 1.35 million pound Apprenticeship Levy, covering both the use of AI tools for productivity and building AI systems in-house. Whether the owner sits in HR, a digital team or the AI office, someone must be accountable for who is trained, on what, and how that is recorded.

Does a mid-sized fashion brand need all of these roles?

Usually not as full-time hires. A brand with a few hundred employees can cover the ground with a handful of clear assignments:

• One executive sponsor with budget authority and a short, written list of priority use cases.
• One or two product owners drawn from the business, not only from IT, each responsible for a live use case.
• Named data owners for product, customer and order data, because poor data quality is the most common reason AI outputs disappoint.
• A governance checklist maintained by legal or compliance, with a simple approval route for new tools.
• Part-time champions in design, merchandising, sales and customer service.

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How do existing fashion jobs change?

The larger shift happens inside existing roles. Copywriters edit and approve drafts rather than writing every product description from scratch. Planners review model-generated forecasts and focus on exceptions. Customer service teams handle escalations while routine queries are answered automatically. Designers use image tools for early ideation but still own fit, fabric and construction decisions. McKinsey's State of Fashion 2026 describes this as roles moving towards higher-value creative and analytical work, which only happens if companies redesign the process, not just add a tool.

For leaders the practical question is not which titles to create, but which decisions and data each person will own once AI is part of the workflow. Writing that down, function by function, is the most useful first step.