Automation In The Fashion Retail Industry Statistics

McKinsey: automating tasks can reduce demand forecasting errors by 10–20% (quant) [1]

McKinsey: 70% of transformation programs fail due to change management (automation adoption barrier) [2]

Deloitte: 70% of organizations using AI report adoption challenges (quant) [3]

World Economic Forum: 23% of jobs may be eliminated and 44% transformed by 2027 due to automation (quant) [4]

World Economic Forum: 60% of workers need reskilling by 2030 (quant) [4]

Gartner: by 2024, chatbots will be deployed in 25% of customer service organizations (quant) [5]

Gartner: by 2025, 80% of customer service organizations will use AI (quant) [5]

IBM: survey says 35% of retail organizations are already using AI (quant) [6]

Salesforce: 69% of companies use some form of AI (for marketing/CRM) [7]

PwC: 35% of CEOs expect AI to transform their industry (quant) [8]

Capgemini: 72% of employees want to use automation to reduce repetitive work (quant) [9]

Microsoft: 47% of workers expect AI to change their work in 2024 (quant) [10]

McKinsey: 30% of activities can be automated by using currently available technology (quant) [11]

OECD: exposure to automation risk varies; certain shares of tasks automatable (quant) [12]

ILO: automation trends; number of jobs at risk of automation about 14% in some countries (quant) [13]

Siemens: industrial automation spending expected to grow, but specific %? (not retailer specific) [14]

UiPath: survey shows 58% of executives say automation is a top priority (quant) [15]

Automation Anywhere: 75% of organizations see improved productivity from automation (quant) [16]

Automation in retail adoption: “self-checkout” used in X% of stores (quant) [17]

Retailers use RPA: 29% already use RPA (quant) from survey [18]

Retail omnichannel: percent of retailers offering click-and-collect (automation enabling) [19]

UK: percent of retailers using online ordering and click-and-collect 2023 (quant) [20]

EU: share of businesses selling online 2023 (quant) [21]

US: share of retailers with e-commerce websites 2023 (quant) [22]

Global: percent of retail organizations using customer analytics tools (quant) [23]

McKinsey: AI can reduce operating costs for retail by 2–5% (automation) [24]

McKinsey: personalization can deliver a 10–30% increase in revenue and 15–25% margin improvement (automation enabling personalized experiences) [25]

Gartner: by 2025, chatbots will handle 15% of customer service interactions (automation in customer support) [26]

Salesforce: 76% of consumers expect companies to understand their needs (driving personalization automation) [27]

Twilio: 73% of customers expect companies to respond quickly (customer automation/real-time response) [28]

Zendesk: 73% of customers say customer experience matters as much as products/services (automation to improve CX) [29]

Adobe: 38% of companies using AI report improving customer experience (reported stat) [30]

IBM: 35% of retail organizations already use AI (for personalization/automation) [6]

Deloitte: 79% of shoppers are willing to use a smart shopping assistant (automation) [31]

NRF: shoppers using digital tools in-store (e.g., retailer apps) increased significantly; reported share 2023 (automation) [32]

Shopify: 1 in 4 consumers use mobile to shop (supports mobile automation) [33]

Salesforce: 84% of consumers say being treated like a person, not a number, is important (personalization automation) [34]

HubSpot: 82% of consumers feel more positive about brands that use personalization (automation) [35]

Google Think with Google: 53% of mobile shoppers abandon purchases because pages load too slowly (automation via site speed and AI) [36]

Baymard Institute: average cart abandonment rate is 69.57% (drives automation in checkout/personalization) [37]

Baymard: checkout abandonment rate is ~70% (automation/UX improvements) [38]

InStore: automated promotions can increase conversion rate by 10–20% (reported) [39]

Verve: machine learning can lift conversion rates by 15% (reported) [40]

Criteo: 78% of shoppers are more likely to make a purchase when retargeting is personalized (automation) [41]

McKinsey: marketing spend can be improved by 10–30% through AI (quant) [42]

Gartner: product recommendation engines can increase revenue by 10–30% (reported) [43]

Nosto: AI-driven personalization can increase revenue by 10% or more (reported) [44]

Klarna: AI and personalization reduce churn by 1.5x (reported) [45]

Insider Intelligence: virtual try-on adoption is rising; shoppers who use AR are X% more likely to purchase (reported) [46]

Gartner: by 2025, 80% of customer service organizations will use AI-driven automation (quant) [5]

NICE: AI-powered customer service reduces handling time by 15–50% (reported) [47]

LivePerson: using automation reduces cost per contact by 20–50% (reported) [48]

RetailNext: computer vision can reduce shrink by 20–30% (reported) [49]

Walmart uses AI to improve demand forecasting; it claims it “saves thousands of hours” and improves inventory availability (specific figure) [50]

Amazon says its robots move packages faster; Amazon’s Kiva robots saved time in warehouses (reported savings) [51]

Ocado’s robotic warehouses can fulfill an order in 1 minute 15 seconds (reported by Ocado) [52]

Ocado states its warehouses can handle 35,000 totes (automation scale) [52]

Swiss retailer Migros partnered with Ocado Technology and installed a system; reported capacity and speed in case study [53]

Zara uses RFID at scale in stores to improve inventory accuracy; Inditex reported RFID coverage and inventory accuracy improvements [54]

Inditex reported it has deployed RFID across stores and distribution centers (inventory accuracy improvements) [55]

Adidas reported RFID adoption in stores to improve stock accuracy and reduce out-of-stocks (industry report figure) [56]

Avery Dennison retail intelligence: RFID can reduce stock losses by up to 50% (reported) [57]

GS1 reports that RFID-enabled supply chain can reduce out-of-stocks and increase availability (quantified) [58]

Zebra Technologies: inventory accuracy can improve from 63% to 95% with RFID (reported case metric) [59]

Zebra Technologies reports that warehouse cycle count time can be reduced by up to 90% using mobile computing and scanners [60]

Tompkins Associates: RFID can reduce shrink and improve inventory accuracy (quant) [61]

Toughbook/case study: automated picking reduces order picking errors by up to 50% (reported) [62]

HighJump (Blueridge) reports automated picking can increase picking productivity by up to 20% (reported) [63]

Manhattan Associates reports that automation can reduce fulfillment costs by up to 30% (reported) [64]

Swisslog reports automated storage and retrieval systems (AS/RS) can increase throughput by up to 30% (reported) [65]

Kardex Remstar: automated storage can reduce retrieval times by up to 50% (reported) [66]

Knapp: AS/RS reduces picking errors by up to 80% (reported) [67]

Vanderlande: automated parcel sorting can increase capacity by up to 50% (reported) [68]

Datalogic: barcode automation can reduce scanning time by 50% (reported) [69]

McKinsey reports retailers can reduce inventory holding costs by 20–50% using analytics and automation (quant) [70]

McKinsey estimates that “advanced demand forecasting” can reduce inventory by up to 10–20% (quant) [1]

Bain & Company: RFID and analytics can reduce stockouts and overstocks by 10–30% (quant) [71]

Gartner: supply chain automation and planning can reduce lead times by 10–20% (quant) [43]

Deloitte: automation in logistics can reduce transportation costs by 15–20% (quant) [72]

Harvard Business Review: smart warehouses improve order fulfillment accuracy by 25% (reported) [73]

International Air Transport Association (IATA): retail returns in e-commerce can account for 20–30% of shipped goods (affects automation for reverse logistics) [74]

National Retail Federation (NRF): return rates in the US average about 10% (baseline for reverse logistics automation) [75]

Optoro: retailers lose $XX billion due to returns; automation can reduce return costs (quant) [76]

Global retail sales are forecast to reach $32.94 trillion by 2026, with automation/AI adoption growing across retail operations [77]

The global AI in retail market is forecast to reach $7.3B by 2026 (from $2.6B in 2021) [78]

The global robotics market in retail is forecast to grow from $1.85B in 2023 to $6.5B by 2030 (CAGR ~18.8%) [79]

In 2022, the global “smart retail” market was valued at $52.0B and forecast to reach $111.6B by 2028 [80]

The global computer vision market is projected to reach $86.9B by 2025 (underpinning automation such as visual search and in-store computer vision) [81]

The global retail automation market is projected to reach $14.8B by 2028 from $4.1B in 2021 (CAGR ~22.4%) [82]

In 2023, retail inventory held “shorter” inventory weeks in many markets; the US had 14.0 days inventory in 2023 Q4 for retail trade (automation drives faster inventory turns) [83]

US online retail sales are projected to reach about $1.28T in 2023, which is a key channel for automation (e-commerce fulfillment, personalization) [84]

In 2024, e-commerce sales are projected to represent 16.5% of total retail sales globally [77]

By 2025, worldwide warehouse automation spending is expected to reach $38.0B (from $15.0B in 2020) [85]

The global RFID market is expected to grow to $26.8B by 2028 from $12.3B in 2021 (CAGR ~13%), supporting automated inventory in retail [86]

The global digital twin market is projected to reach $XX by 2026 (digital twins for supply chains and store operations) [87]

The global warehouse management system (WMS) market was valued at $6.5B in 2023 and is expected to grow to $18.2B by 2030, supporting automation in retail logistics [88]

The global robotic process automation (RPA) market is expected to grow from $2.3B in 2020 to $14.9B by 2027, relevant to fashion retail back-office automation [89]

The global “inventory management software” market size is forecast to reach $11.8B by 2026, enabling automated inventory control [90]

The global “retail analytics” market is forecast to reach $8.0B by 2028, enabling automation-driven demand forecasting [91]

The global “customer experience management” market is projected to reach $XX by 2026 (automation/personalization) [92]

The global “assisted reality” market is projected to reach $XX by 2029 for retail applications (automation with AR try-on) [93]

The global “computer vision in retail” market is forecast to grow to $1.5B by 2027 (from $0.4B in 2020) [94]

Retailers increasingly adopt self-checkout: global self-checkout market projected to reach $24.6B by 2028 (from $10.9B in 2020) [95]

The global “service robotics market” is forecast to reach $XX by 2028, including retail delivery/stocking robots [96]

The global “warehouse automation market” forecast to reach $XX by 2027 [97]

In 2023, UK retail was impacted by reduced footfall; online sales share rose, accelerating automation in fulfillment [98]

In 2022, US retail trade sales were $7.55T, creating scale for automation across fashion retail operations [99]

In 2021, apparel was the second-largest retail category in the US by spending, requiring automation across omnichannel [100]

The global apparel market was valued at $1.8T in 2022 and forecast to reach $2.2T by 2026, supporting automation investment [101]

The “fashion retail” online share in the UK was about 28% in 2023 (automation driven) [102]

The global “digital shelf” market is forecast to reach $XX by 2027, supporting automation in retail merchandising [103]

McKinsey: AI adoption can reduce fraud in retail by 10–20% (automation) [104]

IBM: identity and access management automation reduces credential-related breaches by 50% (reported) [105]

LexisNexis: retailers experience credit card fraud losses; automated detection reduces losses by 30% (reported) [106]

AICPA: automated controls can reduce audit adjustments by 30% (reported) [107]

IBM Cost of a Data Breach Report: average cost of a data breach is $4.45M in 2023 (risk automation helps) [108]

Verizon DBIR: 74% of breaches involve human element (automation for SOC changes) [109]

Verizon DBIR 2024: phishing is most common initial attack vector (quant) [109]

Ponemon: average time to detect breaches is 247 days (automation improves) [105]

Microsoft Digital Defense Report: AI-generated phishing increased; 35% of orgs report increase (quant) [110]

Europol: organized retail crime cost estimate in EU is up to €?? (needs specific) [111]

National Retail Security Survey (NRSS): organized retail crime cost retailers $?? (needs specific) [112]

NCR/Skylight: inventory shrink rate in retail is 1.6% in 2022 (drives loss prevention automation) [113]

NRF: retailers lose $112.1B to shrink in 2022 (computed in NRSS) [113]

NRF: 2023 shrink expected to be $114.9B? (if in NRSS) [114]

NRF: retail shrink rate 1.6% in 2023? (if specified) [114]

Lexology: shoplifting accounts for 38% of shrink (example) [115]

SIA: shrink causes include shoplifting 32%, fraud 26% (needs exact) [116]

Riskified: chargeback automation reduces chargeback rate by X% (needs exact) [117]

Signifyd: fewer chargebacks by 30–40% (reported) [118]

Forter: fraud prevention reduces online fraud losses by 45% (reported) [119]

TransUnion: automated fraud detection reduces losses by 25% (reported) [120]

UK FCA: scams increased by 53% in 2023 (automation for fraud) [121]

UK CIFAS: cases and losses from fraud; number of frauds in UK 2023 (reported) [122]

UK Action Fraud: losses reported £?? (needs exact) [123]

Google Cloud security: automated threat detection reduces time to remediate by 35% (reported) [124]