Artificial intelligence (AI) is no longer just a technical tool. It is becoming a constant companion in the everyday lives of many consumers and is fundamentally changing the relationship between people and brands.
According to the current Accenture study “Consumer Pulse 2025”, around 30 percent of active users already trust AI tools, including for shopping and style advice. The technology has the potential to significantly supplement or take over the work that influencers, search engines or personal recommendations have carried out in recent years.
AI is increasingly becoming a personal stylist, a confidant and an emotional anchor point in the purchasing process. This means a profound change for the fashion industry. It affects not only communication and marketing, but the entire value chain – from digital brand positioning to product range design and pricing strategies to stationary shopping experiences.
The authors
- Tobias Göbbel is Head of Strategy & Consulting for Consumer Products at Accenture. Claudia Specht is a consultant in the Strategy & Consulting department for consumer goods and retail at Accenture.
AI is becoming the new influencer and purchasing advisor
The role of classic search engines is changing. Consumers no longer enter simple keywords, but rather formulate questions and expect immediate, personalized, context-relevant answers. Generative AI replaces the search engine as the first point of contact. According to the study, every second active user has already made a purchase decision based on AI. For brands, this means: visibility no longer comes from SEO alone, but also from Generative Engine Optimization (GEO). Accordingly, content must be designed in such a way that it can be recognized, understood and recommended by AI systems. A consistent tone of voice, an emotional approach, correct product data and a clear brand identity are crucial.
This development presents the industry with a central question: How can fashion brands successfully establish AI as style advice and a trusted person? The answer begins with a change of perspective. Consumers increasingly see AI as more than just a tool. 36 percent of active users even describe the technology as a kind of “good friend”. This emotional closeness opens up new opportunities for brands to actively shape the interaction. This includes specifically feeding your own content, data and brand assets into AI ecosystems instead of relying exclusively on third-party models. Anyone who remains passive here risks becoming invisible in an AI-controlled recommendation process.
Artificial intelligence creates emotional experiences
The emotional dimension is a central driver for purchasing decisions. Consumers are 1.7 times more willing to pay a higher price if they feel emotionally appealed to. Generative AI can be used specifically to create personalized, empathetic experiences. Possible starting points include virtual style advice, individual outfit suggestions or immersive shopping formats with augmented reality, in which the AI suggests suitable outfits that customers can try on virtually. The AI provides context-based combination ideas and, for example, recommends outfits that are statistically absolutely appropriate for certain situations.
Replaced for consumers. The AI thus complements the original function of brands, namely to provide orientation and security when selecting products and making purchasing decisions. It is important that the AI is not only functional, but also human. Users are more likely to distrust content if it appears impersonal, generic or inauthentic. The development of an “AI personality” that fits the brand becomes a strategic success factor.
Pioneers are already showing how this can work. L’Oréal, for example, is investing in AI-based beauty tech solutions such as “Noli,” which provide hyper-personalized recommendations and build an emotional bond with customers. “Noli” uses over a million skin data points and thousands of product analyzes to create individual beauty profiles. This model can also be transferred to the fashion industry. Another example is Marks & Spencer, which offers virtual style advice. Users fill out a style quiz about body shape and style preferences, whereupon the AI creates suitable outfit suggestions from millions of possible combinations. The approach to customers is also personalized depending on their style and mood.
Lack of end-to-end integration slows down the use of AI
Despite the potential, the strategic integration of AI remains inadequate in many fashion companies. Although numerous players are experimenting with pilot projects, the problem here is often a lack of an overall strategy along the customer journey. The greatest potential lies in end-to-end integration. Because AI can not only inspire, but also prepare purchasing decisions, trigger transactions and provide after-sales services. For technical reasons, however, this requires a clean, centralized database: product data must be classified completely, correctly and uniformly. Customer data from the web shop, app, CRM and stationary retail must be brought together. In addition, the interoperability of the systems and the ability to react in real time are crucial.
Agentic AI, i.e. AI that carries out tasks independently, plays a central role here and is increasingly becoming a reality. According to the study, 75 percent of consumers are open to trustworthy AI taking over their purchases. In this case, the touchpoints change radically again. Classic banner advertising, search results or even the websites of individual providers could then increasingly be bypassed. Brands must therefore find new ways to remain present in AI-driven decision-making processes.
Data and trust determine visibility in the AI age
Trust is becoming the new currency. Consumers expect transparency about how AI influences their decisions. 41 percent of those surveyed distrust AI content that does not appear authentic, and 45 percent complain about a lack of personalization. Responsible AI therefore also means data protection, consent-based personalization and clear communication. Brands that invest here – both technologically and culturally – create the basis for long-term customer loyalty. Loyalty programs can serve as a testing ground. Your members are 1.6 times more likely to be emotionally motivated, more willing to share data, and actively participate in the development of new offerings.
Partnerships are also playing an increasingly important role. In these, databases from different brands and channels are shared in order to generate context-based, synthetic data sets. These provide a competitive advantage that individual players cannot provide. This includes data on customer preferences, purchasing history as well as sizes and material properties. They are needed to train AI models that work along the entire customer journey – from initial inspiration to product recommendations and after-sales service.
Common platforms are also emerging on which several brands and retailers define system standards, provide interfaces and exchange product and sustainability data. Another important component are data clean rooms or data protection mechanisms that allow data to be shared securely and anonymously without disclosing sensitive customer information. Collaborations with platforms, technology companies and other brands will become essential to ensure reach and relevance in the AI-supported ecosystem.
AI is changing the role of stationary retail and employees
Brick-and-mortar retail has not been left untouched by the AI revolution either. AI-powered tools can free up employees by taking on repetitive tasks while providing access to customer preferences and product knowledge. This creates more time for personal advice and more emotionally intensive interaction with customers. The role of a retail store is changing to that of a curated, AI-supported showroom in which digital recommendations can be physically experienced.
Employees are increasingly acting as brand ambassadors and curators who individually adapt and emotionally enrich the looks suggested by AI. You get access to customer profiles with style preferences, measurements and previous purchases. In practice, they could use tablets or smart mirrors to show AI suggestions live, adjust the color or design of outfits on the spot, and thus offer an emotionally charged experience. Instead of just presenting goods, they facilitate an interactive experience in which digitally generated recommendations can be physically experienced. In this way, trust is created because the advice given to customers is visibly personal and creative.
Only those who actively design AI remain part of the purchasing decision
In order to successfully establish AI as a style advisor and confidant, fashion brands should act strategically now. Accenture’s STYLE framework, developed specifically for the fashion industry, helps to set the right priorities:
strategy
Your own AI strategy should clearly define the attitude of management and the importance of AI in the company. Which “big bets” along the value chain offer the greatest AI potential for the company?
Touchpoints
The contact points in the customer journey where the use of AI makes sense should be clearly defined. Less is more. Strong use cases at individual “moments of truth” in the purchasing process can already be valuable.
Yes
Employees must be empowered and support the use of AI. The combination of human and artificial intelligence creates the greatest added value.
LLM
Content, data and brand assets must be specifically fed into large language models so that brands remain visible and relevant in AI-supported decision-making processes. Generative Engine Optimization requires structured product data, consistent tonality, emotional appeal and current availability – this is the only way AIs can correctly understand, classify and recommend brand content.
Efficiency
AI can optimize processes in the background and reduce costs. Agentic AI in particular offers extensive options for using artificial agents to stabilize or accelerate standard processes.
The fashion industry is at a turning point. Generative AI is becoming the crucial interface between consumers and brands. It increasingly determines which products are perceived, recommended and purchased. Anyone who continues to view AI as just a technical tool is falling short. Brands that invest now in strategic data integration, emotional brand management and trustworthy AI interaction will ensure a lasting presence in their customers’ decision-making processes.