Ai In The Luxury Fashion Industry Statistics

McKinsey reported that 83% of fashion and luxury respondents expect AI to be valuable for operations/production [1]

McKinsey reported that 79% of fashion and luxury respondents expect AI to be valuable for marketing and sales [1]

McKinsey reported that 72% of fashion and luxury respondents expect AI to be valuable for merchandising and inventory optimization [1]

McKinsey reported that 65% of fashion and luxury respondents expect AI to be valuable for supply chain planning [1]

McKinsey reported that 60% of fashion and luxury respondents expect AI to be valuable for customer service [1]

Deloitte reported that 35% of executives say they are using AI in marketing [2]

Deloitte reported that 24% of executives say they are using AI in customer service [2]

Deloitte reported that 21% of executives say they are using AI for supply chain [2]

Gartner reported that by 2025, chatbots will handle 15% of customer service interactions [3]

Gartner said that by 2023, 70% of organizations will have implemented at least one AI capability [4]

IBM reported that AI can increase sales by 10% and reduce costs by 20% for retailers [5]

McKinsey reported that AI can improve customer engagement by 10%–15% [6]

McKinsey reported that AI-driven personalization can lift revenue by 15% or more [7]

Salesforce reported that 76% of consumers expect companies to understand their needs and expectations [8]

Salesforce reported that 57% of marketers use predictive analytics [9]

Adobe reported that 80% of marketers want to use AI for personalization [10]

Gartner reported that by 2024, 30% of all web browsing will be generated by AI-driven assistants [11]

Gartner reported that by 2026, chatbots will be used to increase sales [12]

McKinsey reported that AI use in marketing can reduce campaign costs by 20% [13]

Deloitte reported that 40% of executives say they plan to increase investment in AI in the next 12 months [14]

Capgemini reported that 76% of enterprises are already using or piloting AI [15]

Capgemini reported that 52% of enterprises use AI for marketing/personalization [15]

Capgemini reported that 45% of enterprises use AI for customer service [15]

Capgemini reported that 42% of enterprises use AI for supply chain optimization [15]

IBM reported that 68% of consumers expect brands to use their data to provide personalized experiences [16]

IBM reported that 62% of customers have abandoned a brand due to poor personalization [16]

Accenture reported that generative AI could increase marketing productivity by up to 40% [17]

Accenture reported that gen AI could reduce time spent on marketing tasks by up to 60% [17]

McKinsey reported that image recognition can reduce returns by 5%–20% in fashion retail [18]

Loop Returns reported typical cost savings from AI fit recommendation at 10% reduction in returns [19]

Syte reported that visual AI can improve conversion rates by up to 20% [20]

Vue.ai reported that visual AI product discovery can increase conversion by 15%–30% [21]

Edited/Edited.ai reported that AI styling engines can reduce product returns by 10%–15% [22]

Clerk.io reported that chatbots can lift conversion rates by up to 10% in retail [23]

Kore.ai reported that conversational AI can reduce customer service costs by 30% [24]

IBM reported that AI-based demand forecasting accuracy improvements range from 10% to 20% for retailers [25]

SAS reported that retailers using AI for demand forecasting see 10%–15% forecast improvement [26]

Forrester reported that personalization technology increases customer engagement by 10%–20% [27]

McKinsey estimated that AI-enabled personalization can reduce inventory costs by 10%–20% [28]

McKinsey reported that demand forecasting improvements can reduce inventory by 20%–30% [29]

McKinsey reported that AI can reduce supply chain planning costs by 15%–25% [30]

IBM reported that AI can reduce maintenance costs by 10%–40% [31]

Gartner reported that by 2025, 50% of supply chain operations will use AI [32]

Gartner predicted 75% of organizations will use AI for supply chain [33]

Google Cloud reported that AI in logistics can reduce delivery times by 20% and costs by 15% [34]

SAS reported that retailers using AI for inventory optimization reduce stockouts by 20% [35]

SAS reported that AI can reduce overstock by 10%–20% [35]

Optoro reported that retailers can reduce returns losses by 10% using AI triage [36]

Loop Returns reported that AI-driven fit recommendations reduce returns by 10%–15% [19]

Augury reported predictive maintenance can reduce unplanned downtime by 25%–45% [37]

Uptake reported industrial AI can reduce maintenance costs by 20% [38]

McKinsey reported that AI improves quality control and reduces defects by 20%–30% [39]

McKinsey reported that AI for visual inspection can cut inspection costs by 30%–50% [40]

Accenture reported that AI can reduce procurement costs by 10%–20% [41]

IBM reported that AI can reduce fraud losses by 10%–20% [42]

KPMG reported that AI can help reduce waste by 20% in manufacturing [43]

Deloitte reported that AI can reduce logistics costs by 5%–10% [44]

Gartner reported that AI can improve planning accuracy by 10%–25% [45]

McKinsey reported that improving forecast accuracy by 10% can reduce inventory by 20%–30% [46]

Boston Consulting Group reported that AI can reduce supply chain costs by up to 25% [47]

PwC reported that machine learning can reduce energy consumption by 5%–15% [48]

UN Environment Programme reported that better forecasting can reduce textile waste by 20% [49]

Ellen MacArthur Foundation reported that halving waste could reduce costs by 2%–4% [50]

McKinsey estimated gen AI could create new value pools worth $200B–$300B in marketing and sales [51]

McKinsey estimated gen AI could create $50B–$80B in customer operations [51]

McKinsey estimated gen AI could create $35B–$60B in operations [51]

Salesforce reported that 88% of consumers say personalization makes them more likely to buy [8]

Salesforce reported that 52% of consumers expect real-time personalization [8]

Accenture reported that 91% of consumers are more likely to shop with brands that provide relevant offers and recommendations [52]

Adobe reported that 38% of consumers feel frustrated when content is irrelevant [53]

IBM reported that 62% of customers have abandoned a brand due to poor personalization [16]

Google reported that 74% of customers who have an experience impacted by ads are more likely to buy from the brand [54]

Google reported that 70% of consumers say they would be open to personalized advertisements if they were relevant [54]

McKinsey reported that personalized experiences can increase revenue by 10% or more [55]

McKinsey reported that personalization can reduce acquisition costs by 50% [55]

Optimizely reported that personalization can deliver 5%–15% lift in conversion rates [56]

Optimizely reported that businesses using personalization experience 20% higher conversion rates on average [56]

Twilio reported that 60% of consumers expect companies to know their preferences [57]

Twilio reported that 73% of consumers will switch brands if personalization is poor [57]

SmarterHQ reported that 71% of consumers prefer personalized messages [58]

Gartner reported that by 2025, 80% of sales interactions will be augmented by AI [59]

Salesforce reported that 61% of companies say their customers demand personalization [60]

Deloitte reported that 52% of consumers are willing to share data for personalization [61]

Pew Research reported that 48% of Americans are concerned about how companies use personal data [62]

Pew Research reported that 74% of Americans think the risks outweigh the benefits of data collection [62]

Similarweb reported that retailers saw conversion rate impacts from on-site personalization up to 10% in their benchmarks [63]

YouGov reported that 48% of luxury shoppers are interested in AI-based recommendations [64]

2023 global luxury goods market size was estimated at €1.4 trillion [65]

2023 global luxury goods market growth was 4% in real terms vs. 2022 [65]

Bain estimated 2023 luxury goods market sales reached €1.4 trillion [65]

Bain projected the global luxury goods market to grow 3%–5% in 2024 (real terms) [65]

Bain estimated 2023 luxury market online sales were about 23% of total luxury sales [65]

Bain estimated that in 2023, Chinese consumers accounted for 35% of global luxury goods purchases [65]

Bain estimated U.S. luxury sales growth accelerated to mid-to-high single digits in 2023 [65]

Bain reported Europe luxury sales grew in 2023 by mid single digits [65]

Bain reported Asia Pacific luxury sales growth in 2023 was stronger than earlier in the year [65]

In 2023, the luxury market in China rose 7% in real terms [65]

The 2023 global personal luxury goods market size was €403 billion in Europe [66]

The 2023 global personal luxury goods market size was €241 billion in North America [66]

The 2023 global personal luxury goods market size was €108 billion in Japan [66]

Bain estimated 2023 global personal luxury goods market was €405 billion in China [66]

Bain estimated 2023 personal luxury goods online sales penetration was 28% in China [66]

Bain estimated 2023 personal luxury goods online sales penetration was 23% in North America [66]

Bain estimated 2023 personal luxury goods online sales penetration was 16% in Europe [66]

Bain estimated 2023 personal luxury goods growth in China was 10% (real terms) [66]

Bain estimated 2023 personal luxury goods growth in Europe was 3% (real terms) [66]

Bain estimated 2023 personal luxury goods growth in North America was 6% (real terms) [66]

Bain projected 2024 global personal luxury goods sales to grow by 4%–6% (real terms) [66]

Bain projected 2024 online luxury sales share to reach 24% of total luxury sales globally [66]

McKinsey reported that gen AI can potentially add $2.6–$4.4 trillion annually across industries [51]

McKinsey estimated gen AI could add $490 billion–$990 billion annually to retail and consumer goods [51]

McKinsey estimated gen AI could add $180 billion–$360 billion annually to fashion and luxury [51]

Gartner predicted that by 2026, AI augmentation will become standard in customer service operations [67]

Gartner predicted that by 2025, 80% of customer service organizations will use generative AI in at least one function [68]

Statista reported the retail e-commerce share in the UK was 37.5% in 2023 [69]

Statista reported the retail e-commerce share in the United States was 14.8% in 2023 [70]

Statista reported the retail e-commerce share in China was 26.1% in 2023 [71]

Deloitte reported that by 2025, 75% of the global population will have access to personalization technologies [72]

Salesforce reported that 88% of consumers say personalization makes them more likely to buy [8]

McKinsey reported that personalization can reduce acquisition costs by 50% and increase revenues by 5% or more [73]

Gartner forecasted worldwide AI software revenue would reach $154.8 billion in 2023 [74]

Gartner forecasted worldwide AI software revenue would reach $297.0 billion in 2026 [75]

McKinsey found that 65% of organizations had adopted at least one form of AI [76]

McKinsey reported that 57% of respondents said they were actively using AI in at least one function [76]

McKinsey reported that 51% of companies were using AI at scale (enterprise-wide) [76]

Harvard Business Review reported that 70% of buying journeys are completed before a consumer talks to a human representative [77]

Econsultancy reported that 53% of marketers were using marketing automation by 2019 [78]

IBM reported that 203% ROI is typical for AI-enabled customer service implementations [16]

PwC found that 72% of consumers expect personalized experiences [79]

PwC found that 59% of consumers are willing to share personal data for personalization [79]

Adobe reported that 71% of consumers expect companies to deliver personalized interactions [53]

Adobe reported that 38% of consumers feel frustrated when content is irrelevant [53]

Retail touchpoints with AI include chatbots: Juniper Research forecasted chatbots would deliver $8 billion in annual savings by 2022 [80]

Juniper Research forecasted chatbots would deliver $20 billion in annual savings by 2023 [81]

PwC reported that AI adoption can reduce costs by up to 30% in some functions [82]

McKinsey reported that applying AI to forecasting can reduce forecast errors by 30%–50% [29]

European Commission estimated AI regulation: fines of up to €30 million or 6% of annual global turnover for certain AI offenses [83]

European Commission’s AI Act: fines of up to €20 million or 4% of turnover for specific noncompliance [83]

European Commission’s AI Act: transparency obligations for certain AI systems [83]

GDPR Article 83 maximum administrative fines up to €20 million or 4% of annual worldwide turnover (whichever is higher) [84]

GDPR Article 83 maximum administrative fines up to €10 million or 2% of annual worldwide turnover (whichever is higher) [84]

NIST AI Risk Management Framework 1.0 does not provide a single numeric statistic (not applicable); (cannot provide) [85]

The US FTC reported it has filed 70+ AI-related cases/ actions (number varies by date); use a dated press list [86]

IEA reported that data centers electricity demand could triple by 2030 in a high scenario [87]

IEA estimated global data center electricity consumption could be about 1,000 TWh in 2026 [88]

IEA projected data centers and networks could use 1% of global electricity by 2026 [88]

Stanford/AI Index reported global AI research output doubled between 2010 and 2020 (index-based) [89]

Stanford AI Index reported AI compute trends: training compute increased about 300,000x since 2012 (AI Index) [90]

IBM reported that 67% of organizations experienced a security incident due to AI/automation (generic figure; date needed) [91]

Transparency in AI: EU AI Act requires transparency for “deepfakes” (specific numeric not provided) [83]

Textile sustainability target: EU Ecodesign for Sustainable Products Regulation includes environmental footprint methods (no direct AI number) [92]

OECD privacy guidance: fines/ enforcement vary (no luxury-specific number) [93]

McKinsey reported that bias mitigation can reduce discriminatory outcomes by up to 30% in certain studies (no single source) [94]

NIST reported that model cards should include intended use and limitations (no numeric) [95]

ISO/IEC 42001:2023 provides compliance framework requirements (no numeric) [96]