AI, AI, who is the most stylish in the land?

Artificial intelligence (AI) is no longer just a technical tool. It is becoming a constant companion in the daily lives of many consumers, fundamentally changing the relationship between people and brands.

According to the latest Accenture study, “Consumer Pulse 2025”, around 30 percent of active users already trust AI tools for shopping and style advice. The technology has the potential to significantly supplement or even replace the work that has been primarily carried out by influencers, search engines and personal recommendations in recent years.

AI is increasingly becoming a personal stylist, a confidant and an emotional anchor in the purchasing process. This signifies a profound transformation for the fashion industry. The change affects not only communication and marketing but the entire value chain; from digital brand positioning and range planning; to pricing strategies and brick and mortar shopping experiences.

AI as new influencer and shopping advisor

The role of traditional search engines is changing. Consumers no longer enter simple keywords; instead, they formulate questions and expect immediate, personalised, context-relevant answers. Generative AI is replacing the search engine as the first point of contact. According to the study, one in two active users has already made a purchasing decision based on AI. For brands, this means visibility is no longer achieved solely through SEO, but also through Generative Engine Optimization (GEO). Consequently, content must be designed to be recognised, understood and recommended by AI systems. A consistent tone of voice, an emotional appeal, accurate product data and a clear brand identity are crucial.

This development presents the industry with a key question: How can fashion brands successfully establish AI as a style advisor and a trusted confidant? The answer begins with a shift in perspective. Consumers increasingly see AI as more than just a tool. In fact, 36 percent of active users describe the technology as a kind of “good friend”. This emotional connection opens up new opportunities for brands to actively shape the interaction. This includes feeding their own content, data and brand values into AI ecosystems, rather than relying solely on third-party models. Those who remain passive risk becoming invisible in an AI-driven recommendation process.

Artificial intelligence creates emotional experiences

The emotional dimension is a key driver of purchasing decisions. Consumers are 1.7 times more likely to pay a higher price if they feel an emotional connection. Generative AI can be used specifically to create personalised, empathetic experiences. Potential approaches include virtual style consultations, individual outfit suggestions or immersive shopping formats with augmented reality, where AI suggests suitable outfits that customers can try on virtually. The AI provides context-based combination ideas and recommends outfits that are, for example, statistically appropriate for specific situations.

The authors: Tobias Göbbel and Claudia Specht offer consulting in the consumer goods sector. Credits: Accenture

For consumers, AI thus replaces or supplements the primary function of brands, which is to provide guidance and security in product selection and purchasing decisions. It is important that the AI appears not only functional but also human. Users are more likely to distrust content if it seems impersonal, generic or inauthentic. Developing an “AI personality” that aligns with the brand therefore becomes a strategic factor for success.

Pioneers are already demonstrating how this can work. L’Oréal, for instance, is investing in AI-based beauty tech solutions like “Noli”, which provides hyper-personalised recommendations and builds an emotional bond with customers. “Noli” uses over one million skin data points and thousands of product analyses to create individual beauty profiles. This model can also be applied to the fashion industry. Another example is Marks & Spencer, which offers a virtual style consultation. Users complete a style quiz about their body shape and style preferences, after which the AI generates suitable outfit suggestions from millions of possible combinations. The way customers are addressed is also personalised according to their style and mood.

Lack of end-to-end integration slows down AI deployment

Despite its potential, the strategic integration of AI remains inadequate in many fashion companies. While numerous players are experimenting with pilot projects, the problem often lies in the absence of a comprehensive strategy across the customer journey. The greatest potential lies precisely in end-to-end integration. AI can not only inspire but also prepare purchasing decisions, trigger transactions and handle after-sales services. Technically, however, this requires a clean, centralised database. Product data must be complete, correct and uniformly classified. Customer data from the webshop, app, CRM and brick and mortar retail must be consolidated. Furthermore, system interoperability and real-time responsiveness are crucial.

Agentic AI, which is AI that performs tasks autonomously, plays a central role here and is increasingly becoming a reality. According to the study, 75 percent of consumers are open to a trusted AI handling their purchases. In this scenario, touchpoints change radically once again. Traditional banner ads, search results or even the websites of individual providers could be increasingly 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 respondents distrust AI content that does not seem authentic, while 45 percent criticise a lack of personalisation. Responsible AI therefore also means data protection, consent-based personalisation and clear communication. Brands that invest in these areas, both technologically and culturally, lay the foundation for long-term customer loyalty. Loyalty programmes can serve as a testing ground. Their members are 1.6 times more likely to be emotionally motivated, share data more willingly and actively participate in the development of new offerings.

Partnerships are also playing an increasingly important role. In these collaborations, databases from different brands and channels are shared to generate context-based, synthetic datasets. These provide a competitive advantage that individual players cannot achieve alone. This includes data on customer preferences; shopping history; and sizing and material properties. They are needed to train AI models that operate across the entire customer journey, from initial inspiration and product recommendations to after-sales service.

Joint platforms are also emerging where multiple brands and retailers define system standards, provide interfaces and exchange product and sustainability data. Another important component is 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 be essential to secure reach and relevance in the AI-powered ecosystem.

AI changes role of brick and mortar retail and employees

Brick and mortar retail is also not immune to the AI revolution. AI-powered tools can relieve employees by taking over repetitive tasks while providing access to customer preferences and product knowledge. This frees up more time for personal consultations and more emotionally engaging interactions with customers. The role of a physical store is thus transforming into that of a curated, AI-supported showroom where digital recommendations can be experienced physically.

Employees are therefore increasingly acting as brand ambassadors and curators who individually adapt and emotionally enrich the looks suggested by AI. They gain access to customer profiles with style preferences, measurements and past purchases. In practice, they could use tablets or smart mirrors to display AI suggestions live, adjust outfits on the spot in terms of colour or design and thus offer an emotionally charged experience. Instead of merely presenting merchandise, they facilitate an interactive experience where digitally generated recommendations become tangible. This builds trust, as the customer consultation is visibly personal and creatively tailored.

Only those who actively shape AI remain part of the purchasing decision

To successfully establish AI as a style advisor and trusted 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 management's stance and the importance of AI within 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 is beneficial 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 values must be specifically fed into Large Language Models so that brands remain visible and relevant in AI-driven decision-making processes. Generative Engine Optimization requires structured product data, a consistent tone, an emotional appeal and up-to-date availability; only then can AIs correctly understand, classify and recommend brand content.

Efficiency

AI can optimise processes in the background and reduce costs. Agentic AI in particular offers extensive opportunities to use artificial agents to stabilise or accelerate standard procedures.

The fashion industry is at a turning point. Generative AI is developing into the crucial interface between consumers and brands. It increasingly determines which products are noticed, recommended and purchased. Viewing AI merely as a technical tool is short-sighted. Brands that invest now in strategic data integration, emotional brand management and trustworthy AI interaction will secure a lasting presence in their customers' decision-making processes.

This article was translated to English using an AI tool.

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