Key Takeaways
- Automation and generative AI are expected to have a transformative impact on the fashion industry, with companies predicted to unlock productivity gains of over 30% in the next five years.
- The adoption of AI will require significant changes in organizational design, ways of working, roles, and talent, with a focus on cross-functional collaboration and cultural shifts.
- Fashion companies need to reskill their teams and recruit tech expertise to mature their AI pilots, with a focus on practical training programs and attracting talent from beyond the traditional fashion ecosystem.
- Leaders must prioritize change management and culture transformations, recognizing that the shift is not just about skills but about culture and mindset.
- The most effective transformations will balance quick wins with long-term ambition, targeting high-value tasks with relatively easier implementation and reinvesting gains to advance core product and customer-facing processes.
Introduction to Automation and Generative AI
Automation and generative AI are set to have a significant impact on the fashion industry, comparable to the disruption created by computers and the internet in their early stages of adoption. Companies across industries are expected to unlock productivity gains of more than 30% over the next five years due to automation and generative AI. Fashion brands such as Zalando and Nike are already seeing benefits from early AI adoption, with automation reshaping routine tasks such as customer service and inventory management, and generative AI being used across functions, from image generation to product design and personalization.
Organizational Design and Ways of Working
The impact of AI will be felt across different functions and types of organizations, but fashion companies of the future will be more efficient, with employees focused on higher-value tasks. Some transactional functions with highly repetitive tasks may become heavily automated, with 28-38% of consumer goods and retail workers’ current activities in Europe and the US potentially being impacted by technology by 2030. Cross-functional collaboration will become the cornerstone of better-informed decision making, with design teams using AI to access real-time material prices from preferred suppliers, enabling quicker choices in conjunction with sourcing and procurement teams.
Roles and Talent
The nature of work will shift from manual tasks, data processing, and record-keeping to activities such as troubleshooting and programming, with up to 40% of workers in consumer goods and retail industries in developed countries potentially needing to reskill or transition to new roles by 2030. However, technology skills remain scarce, and technology talent churn is high, with 47% of US consumer goods and retail employees saying training is the most important factor for generative AI adoption, but nearly half feeling they are receiving only moderate support or less.
Culture and Leadership
Fashion and luxury companies have traditionally attracted talent from within the industry, limiting change, but leaders must widen their approach to talent acquisition and foster cultural changes to support new ways of working. Company culture is seen as the biggest obstacle to tech-related change, with 60% of leaders across industries citing it as a major challenge. Leaders must prioritize change management and culture transformations, recognizing that the shift is not just about skills but about culture and mindset.
Marketing, Merchandising, and Sales
Generative AI is accelerating shifts in marketing, merchandising, and sales, with marketing moving from content production to curation, and generative AI allowing creative teams to shift from manual production to curating and directing AI-generated assets. Merchandising decisions can be accelerated and more informed, with applications ranging from automating assortment selection to detecting microtrends via social listening and translating them into actionable guidance for stock volumes and marketing priorities. Sales teams can be equipped with valuable customer data, with digital ordering systems and AI tools increasing sales associates’ effectiveness and elevating the shopping experience.
Reskilling and Recruiting
Fashion players need to reskill their teams and recruit tech expertise to mature their AI pilots, with employees eager for AI training, yet many organizations not meeting this demand. Companies should offer practical programs, whether focused on general-purpose AI tools or domain-specific, custom-built applications, and attract talent from beyond the traditional fashion ecosystem. However, Big Tech’s competition for AI talent is driving up costs and limiting availability for fashion players, with demand rising for roles such as product flow engineers, integrative marketing strategists, and consumer experience designers.
Executive Response
Executives should respond to these shifts by making AI a strategic priority and starting with high-value processes, scaling and maturing investments to lock in efficiency gains as cost pressures rise from multiple angles. They should build the talent base to support technology goals, widening their recruitment net to secure capabilities outside the traditional fashion ecosystem and creating a compelling employee value proposition that highlights innovation and creativity. Every investment in advanced technologies must also be matched with deliberate workforce development, requiring close collaboration between chief technology officers and chief people officers, as well as targeted upskilling and reskilling employee programs.