o understand how the luxury industry is opening its work streams to AI – and how this cutting-edge technology is shaping its offerings, organisations and values – Europa Star, in partnership with DLG, the strategic growth partner for luxury and lifestyle brands, has conducted the first comprehensive research into how luxury is approaching this paradigm shift.

The State of AI in Luxury is the first survey dedicated to decision-makers in the luxury industry, focusing on AI adoption. Based on a sample of over 250 respondents, the research examines the major discourse on how organisations have integrated AI into their businesses, encompassing levels of adoption, pain points, internal enablement and strategic priorities. This special feature highlights the study’s key findings, distills its suggested actions and shares direct verbatim insights from respondents.

About the research

A survey of 250+ respondents on AI adoption within the luxury industry

71% OF LUXURY EXECUTIVES AGREE THAT AI ADOPTION CANNOT BE DELAYED

Nearly 1 in 3 luxury executives report that AI is already woven into the fabric of their organisations, while over 43% expect full integration within the next year.

This suggests an inflection point that will soon fundamentally reshape the sector.

This isn’t a gradual evolution; it’s a compressed transformation that leaves little room for hesitation. The window for strategic positioning is narrowing rapidly and the stakes are considerable. Those who move now will likely define the standards and capture advantages that become much harder to replicate later.

31% state that AI is already implemented and integral

43%expect full integration within 6 - 12 months

Only 6% expect the transformation to take more than 3 years

31% of those respondents that say AI is “already implemented”:

• Watches & Jewellery: 28%
• Hospitality & Travel: 28%
• Fashion & Leather Goods: 20%
• Beauty & Cosmetics: 15%
• Automotive: 9%

“Artificial Intelligence, deep learning, machine learning: whatever you’re doing, if you don’t understand it – learn it. Because otherwise you’re going to be a dinosaur within 3 years.” Mark Cuban, Entrepreneur and Investor

42% ARE TRAPPED IN EXPERIMENTATION BOTTLENECKS

The luxury industry stands at a crossroads. While 55% of brands remain stuck in early-stage adoption – with the largest cohort (42%) trapped in an “experimentation bottleneck” – a substantial 43% have already crossed into implementation (22%), integration (13%) and optimisation (9%).

This isn’t a story of tentative exploration across the board; it’s a tale of two diverging paths emerging within luxury. The question is no longer whether to adopt AI, but which side of this divide brands choose to position themselves on – and how quickly they can make that leap.

55% stuck in early stages (13% Exploring + 42% Experimenting)

42% already implementing (22%), integrating (11%) or optimising (9%).

42% of those respondents that say they are still in the “Experimenting” phase:

• Watches & Jewellery: 38%
• Hospitality & Travel: 24%
• Fashion & Leather Goods: 17%
• Beauty & Cosmetics: 17%
• Automotive: 3%

22% Of those respondents that say they are already in the “Implementing” phase:

• Watches & Jewellery: 25%
• Hospitality & Travel: 32%
• Fashion & Leather Goods: 20%
• Beauty & Cosmetics: 17%
• Automotive: 7%*

“From 2023 onwards, we significantly accelerated our AI efforts, launching numerous initiatives across the LVMH group. We have a dedicated strategy team with some 70 high-level data experts, comprised of our Chief Omnichannel Officer and Data Officer, and myself, the CIO. Data scientists, data engineers and data architects collaborate on a number of algorithms, which we will make available to our brands.” Franck Le Moal, Chief Information Officer, LVMH.

6% OF LUXURY EXECUTIVES ARE MAKING USE OF AUTONOMOUS AI

The data reveals an unambiguous truth: luxury brands mainly use AI as a supporting tool, shying away from scenarios of autonomous “agentic” systems. Nearly all respondents report that humans remain involved throughout most operational flows, in critical interaction stages of varying AI systems (not just chatbots). From crafting prompts, validating recommendations and editing outputs to approving critical decisions, AI handles discrete tasks while people maintain creative and strategic control.

Only 6% report deploying true autonomous AI for complete workflows with minimal supervision. These early adopters are predominantly from larger enterprises (over 80%) with dedicated AI budgets (over 50%) – organisations positioned to experiment at the frontier. But that small percentage isn’t reflective of an industry-wide failure. Instead, it suggests that luxury continues to hold on to its instincts that what makes it survive are the “human touch” and craftsmanship.

At the opposite end of the spectrum, 11% of respondents state that AI is not used in their daily operations at all

What is the one business challenge you wish AI could solve for you?”

“Full and seamless integration across our business, that is non-threatening to our employees. Our business can never lose the human touch. Human authenticity is what we are built upon.” C-Suite Executive, Hospitality & Travel

“Personalising the customer experience at scale while maintaining the exclusivity and human touch that luxury brands are known for.” Senior Executive, Watches & Jewellery

73% CHATGPT IS CURRENTLY THE MOST WIDELY ADOPTED TOOL

ChatGPT’s overwhelming dominance reflects its first-mover advantage and massive public popularity, making it the most accessible entry point for AI. However, it is difficult to say whether these are validated enterprise licenses, as over 35% of respondents claim that AI initiatives are funded through ad-hoc budgets. Many organisations may be relying on unvalidated individual subscriptions while enterprise AI strategies remain underfunded and undefined.

Interestingly, the number of responses indicates that individuals do not rely on just one AI tool, but at least 2.5 tools on average. This points to two possibilities: executives are still shopping around, testing different platforms to find the right fit, or they’re deliberately deploying multiple tools, each tailored to specific business needs.

Who’s Who?

OpenAI (ChatGPT): OpenAI leads by leveraging its massive consumer adoption to drive business use. It’s now expanding this lead by integrating e-commerce and apps like Canva and Shopify directly into its chat interface.

Google (Gemini): Google’s Gemini is the primary challenger, using the unparalleled distribution of its 3+ billion-user ecosystem (Search, Android). Key partnerships, including with Apple’s iOS, aim to embed Gemini as the default AI in global workflows.

Anthropic (Claude): Anthropic’s Claude is the enterprise-focused challenger, differentiating with a “safety-first” architecture. Its massive context window makes it the preferred solution for high-stakes, complex tasks like legal or financial analysis.

DATA FRAGMENTATION IS THE #1 CHALLENGE FACED IN AI ADOPTION

The Data Foundation Gap

• Fragmented systems isolate critical data across functions and touchpoints
• Quality issues produce unreliable insights and flawed recommendations
• Legacy infrastructure prevents seamless integration of AI tools – this is reflected in novel research stating entirely new data architectures are required to sustain agentic AI systems*
• Poor data hygiene undermines model accuracy and business value

* Salesforce study: 84% of technical leaders need data overhaul for AI strategies to succeed (2025).

“AI still has a long way to go before it becomes reliable. We consider it’s only around 60% correct, hence we spend a lot of time doublechecking the information it provides. This minimises gains in efficiency from using AI. I wish it could be more trustworthy, so we could automate internal processes and even let it run part of our customer service on its own.” C-Suite Executive, Watches & Jewellery

AI-RELATED TALENT REMAINS ANOTHER CRITICAL CHALLENGE TO ADOPTION

Beyond data, talent remains the most significant barrier to AI adoption, but the challenge for luxury is unique. The core issue is not a simple lack of technical expertise, but a critical shortage of hybrid talent. Luxury organisations are struggling to find leaders who can bridge the gap between information technology and the nuanced, qualitative world of brand equity. The industry doesn’t just need AI specialists; it needs “translators” who can strategically apply AI to enhance the creative process or scale high-touch clienteling, all without diluting the brand’s soul. AI Fluency will most likely become a hot topic in the next year, as brands begin to realise the importance of getting up to speed with AI whilst maintaining these crucial human elements to remain competitive.

This skills gap is compounded by deep-seated cultural friction. “Change management resistance” in luxury is not just procedural; it’s philosophical. It represents the inherent tension between a data-driven future and a culture built on heritage and human craftsmanship.

Furthermore, the “lack of employee time to upskill” is symptomatic of an industry that runs on the relentless pace of collections, events and immediate client demands. This creates a critical bottleneck: organisations lack the internal expertise, face cultural resistance from teams who fear AI’s impact on their craft, and are too operationally focused to invest the time in strategic learning.

“The most significant challenge will be to properly train and educate the team on [AI] usage.” Senior Executive, Beauty & Cosmetics

60% OF EXECUTIVES USE GEN AI FOR THE CREATION OF MARKETING CONTENT

GenAI has moved from a theoretical risk to a practical engine for high-volume content production. The highest adoption rates are for marketing content and visual design. This shift allows organisations to solve a critical industry bottleneck: feeding the insatiable demand for digital content without compromising their standards or inflating costs. Crucially, this proliferation is being accelerated by emerging regulatory clarity in key markets. The EU AI Act, alongside US measures like the California AI Transparency Act (SB 942) and U.S. Copyright Office guidance, now provide the necessary legal guardrails. By defining clear “rules of the road” for digital provenance and IP rights, these frameworks remove corporate hesitation, giving risk-averse brands the confidence to transition GenAI from experimental pilots into a standardised, scalable business practice.

“The future belongs to those who can combine the precision of algorithms with the poetry of emotion, transforming technology into an invisible ally that elevates creativity, storytelling, and human connection.” C-Suite Executive, Multi-luxury industry

66% OF LUXURY EXECUTIVES SEE CONSUMER INSIGHTS AS AI’S TOP OPPORTUNITY

In today’s omnichannel world, the historical one-on-one boutique relationship has become fragmented across digital touchpoints, social media and global retail. AI offers the only scalable way to solve this, sifting through massive, unstructured data sets – from social sentiment to purchase history – to build a unified client view. This allows brands to move beyond simple segmentation and power predictive personalisation, effectively scaling intimacy.

This is especially critical in high-value, long-cycle sectors like watchmaking. AI can analyse nuanced, long-term signals, such as waitlist requests, auction results and collector forum discussions, to identify nascent trends and map a client’s entire journey, from their first inquiry to their “grail” purchase.

Top three AI opportunities cited by Watches & Jewellery executives:

• Consumer insights & analytics 73%
• Social media management 52%
• Competitive intelligence 42%

“I think AI is, like anything, a business facilitator. We have an incredible amount of transactional data for our customers over the last 20 years. Consolidating this data then empowering our teams to utilise AI tools to mine it is, in my view, the biggest opportunity that we’re going to go after first.” Fran Millar, CEO, Rapha

“The one business challenge I wish AI could solve for me is achieving true personalisation at scale without losing authenticity. While data-driven insights can identify patterns and preferences, crafting experiences that genuinely resonate with each individual customer emotionally and contextually remains difficult. AI could help by unifying fragmented data sources, predicting nuanced behaviour, and generating adaptive content that reflects brand values as well as user intent.” C-Suite Executive, Multi-luxury industry

The data reveals an industry in flux – some racing ahead, others paralysed by pilot fatigue. But the bigger questions remain unanswered: How do luxury brands balance AI-driven personalisation with the exclusivity that defines them? Where does automation enhance craft and where does it dilute it? And as organisations layer tool upon tool, how do they prevent data fragmentation from undermining the very insights AI promises to deliver? These aren’t abstract concerns – they’re the make-or-break decisions that will separate leaders from laggards in the years ahead.

// For more insights, visit us at digitalluxurygroup.com