Welcome to the Vogue Business Careers Guide: AI Edition. Based on a survey of over 300 industry professionals and students, this series explores how AI is transforming careers in fashion and beauty at every level, and how you can future-proof your path in the AI era.

AI has moved beyond pilot projects in fashion, beauty, and retail and is now being integrated into everyday workflows. It’s also reshaping how employees think about their careers. Across roles and seniority levels, workers are adjusting their expectations around career progression, skills development, and job security faster than most organizations are updating training, job descriptions, promotion criteria, or governance.

In this environment, there’s a risk of fragmenting the workforce. Without clear direction, teams are more likely to develop inconsistent practices, forming their own assumptions about when and how AI should be used, what “good” looks like, and how their value is measured.

According to a Vogue Business survey of over 300 current and aspiring fashion, beauty, and retail professionals, the vast majority (88%) believe there will be an expectation to understand and use AI in their roles in the future. Most managers (82%) are already discussing AI with their teams, and many employees say they have started upskilling themselves in the absence of formal AI training programs from their companies.

Experts stress that leaders should set guidelines for AI use before habits become entrenched. “Leaders need to be very clear—when hiring, communicating, or speaking at company meetings—that the priority is for employees to understand AI in their roles in a specific way,” says Grace McCarrick, a workplace culture expert and soft skills coach who works with Amazon, Uber, and Spotify. A clear AI strategy should define where the organization draws the line on capability, ethics, brand values, and cultural priorities. That clarity must also extend to governance—covering everything from intellectual property ownership and supplier contracts to data leakage and disclosure.

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Once a clear AI strategy is in place, experts recommend that brands introduce AI into workflows gradually, starting with function-specific pilots that demonstrate the technology’s usefulness to the teams who will use it. As workflows evolve, leaders should reward employees who connect AI tools to better business decisions or outcomes, rather than simply praising experimentation for its own sake. Executives will also need to decide who is accountable when AI-assisted work fails and how to audit decisions.

Clarity and boundaries must go hand in hand with psychological safety, reassuring teams that AI is meant to support their work, not replace it. Executives face a balancing act between encouraging experimentation and preserving human value. Ultimately, speed should not come at the expense of craft, brand voice, or judgment.

Here, we break down our data on how different generations view AI and careers, how promotion paths and leadership expectations are changing, and what this means for the future structure of the workforce.

What the Workforce Believes About AI
Vogue Business survey data reveals a divided workforce when it comes to perceptions of AI. When asked how they feel about AI’s future impact on their careers, responses are almost evenly spread across the spectrum, from very negative to very positive. This disparity will complicate executive decision-making. The challenge will be to build a cohesive company culture: organizations that communicate at either extreme—claiming “AI will save us” or “AI is the enemy”—will struggle to unite cross-functional teams with nuanced views, especially…In larger companies, one of the clearest signals from our data is that employees expect AI to become a basic requirement for future roles, and many are already preparing for this shift. While 88% of respondents believe AI skills will be needed for their future jobs, only 32% say their company currently offers any AI training, and just 27% report having access to a budget for AI tools. This gap between expectation and support is already influencing behavior: 46% believe it is their own responsibility to upskill, compared to 31% who see it as their employer’s duty. For executives, this indicates a workforce that is moving forward regardless of formal strategy or guidelines. However, the risk is a lack of consistency in brand standards and ways of working.

For executives shaping company-wide strategies, it is essential to account for differences across generations, seniority levels, and business functions. Employees under 25 are more likely to view AI through a lens of fear—concerned about job loss, ethics, and reduced creativity. Mid-career employees are more tool-oriented, prioritizing technical AI proficiency more than any other group. Those aged 45 and over are both the heaviest daily users and the most optimistic about AI’s role in complex problem-solving, reflecting a pragmatic and cyclical view of technology shaped by their experience with multiple innovation cycles throughout their careers.

For leaders, these differences translate into competing needs: younger teams asking for boundaries and values, mid-career managers seeking capability and recognition, and senior professionals focused on strategic leverage.

Function also shapes expectations. Respondents in marketing, PR, and communications expect to use AI to automate benchmarking, campaign testing, and administrative tasks. Creative direction and content professionals anticipate a shift from asset production to concept testing and systems design, freeing up time for strategic work. Those in merchandising, product development, and buying see AI as a way to improve visibility, forecasting, and reduce production errors. Finance, sales, and operations professionals emphasize AI’s support in analytics and decision-making. Creative roles, from designers to stylists, express the greatest anxiety about originality and the erosion of junior learning. These contrasts show that a single narrative about AI will not resonate internally; what feels like an opportunity in one department can feel like a setback in another.

Among business owners and freelancers, nearly half (49%) predominantly see AI as an advantage, while 55% believe it will allow them to scale without hiring—a mindset likely to influence expectations as talent moves between independent and corporate work. Employees, meanwhile, already anticipate that junior and entry-level roles will be most affected as administrative tasks are automated, and that promotion criteria will shift in ways that make progression beyond middle management less linear.

Experts say the workforce is preparing for a less traditional career ladder and more skills-based work—changes that will test traditional models of management, succession planning, and workforce design.

The Workforce Architecture Shift

The next phase of AI adoption will reshape how work is divided between entry, middle, and senior levels, and how organizations balance human craft with AI-enabled decision-making.

For decades, many corporate teams in fashion, beauty, and retail have been organized as a relatively clear ladder. Entry-level roles were often heavy on coordination—sorting schedules, compiling research, drafting pitches. These tasks were not glamorous, but they provided a training structure. Middle managers were the connective tissue, translating strategy from above into execution below. Their value lay in owning processes and aligning teams. Senior leaders, in turn, relied on this structure.These layers help surface the right information and support judgment calls on brand, risk, and investment. AI challenges this model, and if ignored, it could hurt employee retention. Often, entry-level tasks are now the easiest to automate, raising concerns that an already risk-averse generation might have fewer opportunities to enter the workforce and learn through hands-on repetition and exposure. Survey respondents worried that AI will “hinder the development of younger adults, making them more dependent and less able to think for themselves.” For mid-level roles, AI is expected to handle planning and routine decision support, meaning promotion criteria may shift from simply “running the machine” to “improving the machine.” For senior leaders, the challenge becomes redesigning career paths and performance criteria in a workforce where attitudes toward AI vary widely.

Experts predict three structural shifts. First, a move from task execution to decision quality: as AI produces more first drafts and provides analysis and options, roles will tilt toward evaluating outputs, stress-testing assumptions, and making trade-offs. “As a leader, you have to show what good critical thinking, judgment, and discernment look like in your organization, and teach that—otherwise you’re setting people up for failure,” says McCarrick. In creative industries, this human layer includes taste, storytelling, and brand judgment, which will become more valuable as increasingly easy content and idea generation risk creating sameness.

Second is a gradual shift from role-based progression to skills-based progression, as organizations prioritize portfolios of capability over a single, linear career path. Anu Madgavkar, a partner at the McKinsey Global Institute, describes a shift from a T-shaped model (deep expertise in one area) to an M-shaped model (multiple areas of depth connected by broad, transferable skills). This opens up opportunities for cross-functional problem-solving as both a capability and a retention tool. “The research shows us that people who work in organizations that bring diverse teams together to solve problems in real-time end up creating the most upwardly mobile career ladders,” Madgavkar says. AI tools can either concentrate power in a few high-leverage operators or democratize capability across teams, depending on how access and incentives are designed.

In this sense, workforce design is a crucial leadership challenge rather than just an HR afterthought. If administrative work no longer serves as a training ground, companies will need new entry routes—such as structured rotations, supervised AI use, clearer quality standards, and earlier exposure to appropriate levels of decision-making. Learning models and promotion criteria will also need to evolve to teach and reward skills like judgment and adaptability, over pure output.

Finally, organizations will need to plan hybrid human and AI capacity together: determining how many roles are needed and what they are for. “Are we going to trim costs by shedding people, or capture this value by training and using people to do things we couldn’t do before, like spending more time with customers?” says Madgavkar. “If you have a billion dollars of free capacity, how are you going to use it to further your business mission? This is the real C-suite leadership challenge.”

Methodology and demographics
Vogue Business launched a five-minute survey to understand how AI is impacting careers in fashion, beauty, and retail, open from October to December 2025. It was shared with Vogue Business newsletter subscribers, LinkedIn followers, and directly with 500 industry contacts. Respondents were aged 16 or older, working in the fashion, beauty, or retail industries (including employees in any function, business owners, and freelancers), or students aspiring to work in those sectors.Of those surveyed, 31% were between 16 and 24 years old, 33% were 25 to 34, 24% were 35 to 44, and 12% were 45 or older. Women comprised 85% of respondents, men 13%, non-binary individuals 0.8%, and 1.2% preferred not to state their gender.

Sixty percent of respondents currently work in fashion, while 6% work in beauty and 7% in retail. Students made up 27% of the group. Among the working professionals, 37% are business owners or freelancers, and 63% are employees. Of those employees, 41% work for a luxury company, 26% for a mid-level or accessible luxury brand, and 21% for a mass-market fashion, beauty, or retail company. The rest work in areas such as fashion councils, agencies, media, and higher education.

The roles of these employees break down as follows: 48% work in marketing, PR, or communications; 10% in creative direction or content creation; 7% in merchandising, product development, or buying; 6% in fashion or beauty product design; 4% in sales or commercial roles; 4% in business operations or project management; 2% in supply chain or logistics; and 2% in tech, digital strategy, or innovation. The remaining employees work across HR, customer service, client relations, finance, legal, compliance, data, analytics, photography, hair and makeup, styling, modeling, talent agencies, editorial, and education.

The survey reached a primarily Western audience. Geographically, 37% of respondents live in the UK, 14% in the US, 13% in France, 6% in Germany, and 6% in Italy. The remaining 24% live in Australia, New Zealand, India, the UAE, the Philippines, Iran, Pakistan, Bangladesh, China, Japan, Türkiye, Norway, Poland, Portugal, Spain, Sweden, the Netherlands, Croatia, Ireland, Cyprus, Latvia, Kosovo, Belgium, Denmark, Greece, Canada, Colombia, Peru, Argentina, Venezuela, South Africa, Uruguay, Brazil, and Mexico.

Frequently Asked Questions
Frequently Asked Questions The Fashion Executives Guide to a Career Reinvention with AI

Beginner Foundational Questions

1 What does career reinvention with AI even mean for a fashion executive
It means strategically using Artificial Intelligence tools and concepts to pivot your role skills and value within the fashion industry Its not about becoming a data scientist but about leveraging AI to enhance creativity strategy and decisionmaking in areas like design merchandising marketing and supply chain

2 Im not techsavvy Is this guide still for me
Absolutely This guide is specifically designed for fashion professionals not technologists It focuses on the application of AI in a business context explaining concepts in simple terms and showing how to use accessible userfriendly AI tools

3 What are the most immediate benefits of using AI in my current role
You can save massive amounts of time on repetitive tasks gain deeper insights from customer and market data enhance creative processes and make more informed predictive decisions

4 Wont AI just replace fashion jobs
AI is a tool for augmentation not wholesale replacement Its likely to replace specific tasks not visionary leadership creative direction or nuanced human relationships The guide focuses on how to position yourself as the irreplaceable human who expertly wields these new tools

Advanced Strategic Questions

5 How can AI specifically help with creative processes like design or styling
AI can analyze global trend data and social imagery to predict emerging styles generate unique textile patterns or color palettes based on keywords create rapid visual prototypes and help personalize styling recommendations at scale by understanding individual customer aesthetics

6 Whats a practical first step I can take next week to start this reinvention
Identify one repetitive timeconsuming task in your weekly workflow Then find and test one AI tool to automate or enhance that single task

7 What are the biggest pitfalls or mistakes to avoid when integrating AI
The main pitfalls are relying on AI outputs without applying