How AI Is Changing Business Processes in Fashion
AI adoption in fashion is often discussed in terms of tools. For companies, however, the more useful question is how AI changes the way work gets done: which processes can be improved, which activities can be automated, and what new responsibilities emerge as a result?
The AI Impact & Opportunities Framework maps these changes across two dimensions: existing versus new processes, and AI-driven versus AI-assisted work. It identifies four areas for organisations to assess.
1. Transform existing processes
In many cases, AI supports employees within an established workflow. A merchandising team, for example, can use AI to analyse sales and assortment data more quickly, identify patterns and evaluate options. The team remains responsible for commercial decisions, while gaining more time for work that requires judgement and collaboration.
The opportunity is to improve productivity and the quality of decisions by giving people better support.
2. Automate selected activities
Some activities within existing processes can be carried out by AI. A customer service agent, for example, may answer routine questions without direct intervention from an employee.
Effective automation requires clear boundaries. The company must decide which requests the agent can handle, when a case should be escalated to a person, how performance will be monitored and who is accountable for the outcome. Human supervision remains essential, particularly where an error could affect a customer relationship or the brand’s reputation.
3. Introduce new processes and capabilities
AI can also enable work that was previously beyond an organisation’s capacity or expertise. A fashion brand might use AI to explore concepts for a product category outside its design team’s current specialisms, or to test a wider range of creative directions before committing resources to development.
These possibilities expand capacity, but they also call for new skills. Teams need to evaluate outputs, apply technical and creative expertise, and decide which ideas are appropriate for the brand and commercially viable.
4. Build processes to manage AI
AI systems require ongoing work of their own. Prompts and agents need to be designed, tested, maintained and updated. Content may need to be structured for discovery through AI-powered search. Automated workflows need monitoring, ownership and clear rules for escalation.
This makes process engineering increasingly important for fashion companies. To use AI reliably, organisations need to understand how work flows between teams, systems and decision-makers, then define where AI contributes and where people retain control.
The starting point for AI adoption is therefore a careful assessment of existing processes. By mapping how work is performed today, fashion companies can identify where AI should assist employees, where automation is appropriate, which new capabilities are worth developing and what it will take to manage them responsibly.
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