最佳化零售店營運以滿足現代消費者的需求：提升員工能力、庫存管理、訂單處理、自助服務和損失預防。

隨著銷售、履約、服務和自助服務日益成為驅動力，零售商店在適應不斷變化的購物體驗的過程中，面臨著以更少的資源實現更多目標的挑戰。同時，他們還必須應對利潤率壓力、人手不足以及庫存耗盡風險日益增加等挑戰。未來12個月，零售商正朝著幾個明確的目標投資。一是彌合庫存可見度和全通路營運之間的差距；二是實現結帳流程和顧客自助服務的現代化，同時損失預防措施不受影響；三是提高第一線員工的生產力、培訓水準和參與度。在這些領域，零售商正在整合並應用各種技術來降低人事費用並提高營運效率，包括人工智慧、無線射頻識別和電腦視覺，並且已經取得了可量化的成果。

本報告主要探討的問題

• 未來 12 個月內，推動投資的門市營運重點是什麼（庫存準確性、勞動生產力、結帳體驗、損耗控制措施）？宏觀經濟逆風又將如何影響這些重點？
• 零售商如何提高庫存可見度和全通路履約？ RFID、電腦視覺、OCR 和工作流程整合等技術正在他們營運的哪些環節中得到應用？
• 零售商如何實現結帳流程現代化？他們如何平衡速度、可靠性、客戶體驗和損失預防？
• 顧客購物體驗如何朝向自助服務（自助結帳系統、掃碼購、智慧購物車等）發展，以及其部署範圍如何擴大？
• 零售商如何支持第一線員工（溝通、培訓、參與等），哪些因素可以減少摩擦並促進採用？
• 設備規格（包括 NPU 部署）、連接性和整合如何影響 AI 驅動的店內工作流程的實現時間和投資回報率？

上市機構

• Able Systems
• Amazon
• Apple
• Aptos
• Avery Dennison
• Beijing Silion
• Bixolon
• Blue Bamboo Systems
• Bluebird Corp
• Brother
• CAEN RFID
• Caper Carts
• Chainway
• Cipherlab
• Citizen Systems
• Datalogic
• Dell
• Denso Wave
• DRS Tactical Systems
• DT Research
• Durabook
• Epson
• FEIG
• Focal Systems
• Fujitsu
• Getac
• Google
• Honeywell
• HP
• iData
• INVENGO/TAGSY S
• IPC
• Kyocera
• Legion
• Lenovo
• M3 Mobile
• Meferi
• Metric
• Microsoft
• Mildef
• Mobile Demand
• Motorola Solutions
• Newland AIDC
• Nordic ID (Brady)
• Panasonic
• Point Mobile Co.
• Printek
• ProGlove
• Quail Digital
• RodinBell
• RuggON
• SATO
• Samsung
• Scandit
• SEUIC
• SII
• Sonim
• Star Micronics
• Supoin
• Theatro
• Thing Magic/Jadak
• Toshiba TEC
• TSC
• UKG
• Unitech
• Urovo
• VoCoVo
• Winmate
• Woosim Systems
• WorkJam
• Zebra

主要發現

• 門市的角色正在被重新定義，人們對其績效的期望也越來越高。零售門市越來越需要兼顧銷售、履約、服務和體驗，而自助服務也正成為顧客體驗的重要組成部分。這增加了門市營運的範圍和複雜性，而員工在門市的順暢營運中仍然扮演著核心角色。
• 最大的不利因素是利潤率承壓和人手不足。零售商優先考慮那些能夠提供明確投資報酬率和快速實現價值的解決方案，並避免那些只會增加營運複雜性而無法降低人事費用或提高營運效率的措施。
• 全球零售設備市場規模已相當可觀，2024 年市場規模約 34 億美元，設備數量略高於 700 萬台，預計到 2029 年將達到約 40 億美元和 860 萬台設備。這反映出，隨著零售商升級舊硬體並在更多門市、職位和工作流程中部署設備，年成長率仍保持在個位數低點。
• 門市的科技環境分散，可靠性至關重要。智慧型手機、平板電腦和手持行動電腦都配備了掃描器和無數其他應用程式。零售商越來越重視易用性、電池續航力和耐用性，以提高運作。
• 簡化流程如今已成為現場實施的關鍵要求。應用程式臃腫、需要多次登入以及裝置分散會導致員工沮喪，並阻礙其持續使用。零售商正尋求整合工作流程並改善溝通，利用免持和穿戴/語音控制等方式減少營運摩擦，使員工能夠專注於客戶服務。
• 庫存準確性和客戶體驗仍然是營運中的重中之重。零售商持續致力於提升庫存管理、準確性和客戶參與，並重申庫存準確性是大多數門市關鍵績效指標和績效的基礎。
• 全通路履約的挑戰較源自於可見性和執行力，而非自動化。即使系統顯示庫存充足，員工和負責人也常常難以快速找到商品，導致漏揀、使用替代品，最終造成顧客不滿。
• 零售商正在推行融合多種技術的策略。他們將工作流程、RFID、電腦視覺、OCR 和基於人工智慧的預測分析等技術整合起來，以提高庫存可見性和與需求的匹配度，從而減少缺貨和庫存積壓。
• 儘管結帳流程日趨現代化，但自助服務的推廣仍受到可靠性和庫存損耗風險的限制。零售商只有在能夠為誠信顧客提供良好體驗並將損失控制在可接受範圍內的情況下，才會推廣自助結帳系統、掃碼購和智慧購物車等服務。
• 零售業的碎片化和有組織零售犯罪的猖獗對損失預防計劃的影響日益加劇。零售商正在尋求能夠精準定位可疑活動發生的時間和地點、減少調查所需工作量並提高系統即時可見性的工作流程。
• 門市內部的設備基礎設施正日益人工智慧化，部署速度也隨著更新周期而加快。超過一半的受訪者表示已擁有配備NPU（網路處理單元）的行動設備，另有三分之一的受訪者計劃在下一次升級週期中部署。這將加速向更實用的設備內電腦視覺/OCR（光學字元辨識）技術的過渡，並提高門市工作流程的容錯能力。
• 零售媒體網路和個人購物平台正向店內觸點拓展。店內指示牌和智慧購物車是日益受到關注的領域，但它們的成功取決於營運規範、執行一致性、內容準確性和效果衡量能力。

本報告調查了最佳化零售店營運以滿足當今消費者需求的趨勢，總結了零售業面臨的主要挑戰、應對這些挑戰的各種技術、零售商的優先投資領域以及應用案例。

目錄

本報告內容

本報告探討的問題

本報告的目標受眾

本報告中列出的組織

摘要整理

• 主要發現

第2章：零售業優先事項與投資舉措

第3章：零售商面臨的宏觀經濟挑戰

第4章 門市技術基準及連結性限制

• 目前現場設備的狀況及其應用限制。
• 連接性限制及其對即時和人工智慧工作流程的重要性
• 市場規模及預測背景
• 供應商情況

第5章：全通路履約與庫存視覺化

第6章：收銀現代化與損失預防

第7章：提升現場工作人員的技能

第8章：人工智慧應用、NPU設備、用例和障礙

• 對裝置上的人工智慧和神經網路處理單元 (NPU) 進行簡單易懂的說明
• 按業務領域分類的優先人工智慧應用案例
• 實施和擴展的障礙

第9章：個人購物平台與零售媒體網路的興起

• 市場結構定義
• 將零售媒體網路擴展到店內接點

附錄

• 附錄A：宏觀問題優先排序詳情（調查）
• 附錄 B：庫存視覺化、RFID 和履約詳情（研究）
• 附錄C：結帳及損失預防詳情（調查）
• 附錄 D：自助服務、個人購物、智慧購物車和 RMN（研究）的詳細信息
• 附錄 E：連結性和網路準備（調查）
• 附錄 F：試點運作和運作實施中的限制因素（調查）
• 附錄G：人工智慧在各業務領域的重要性（調查結果）

調查方法

供應商簡介

關於作者

關於VDCco

Inside this Report

Retail stores are being asked to do more with less when it comes to sales, fulfillment, service, and an evolving shopper journey that increasingly includes self-service, while dealing with margin pressure, labor constraints, and a higher risk of shrink. Retailers are investing over the next 12 months in a few clear goals. One is closing gaps in inventory visibility and omnichannel execution. Another is modernizing checkout and shopper self-service without weakening loss prevention. A third is improving frontline productivity, training, and engagement. Across these areas, retailers are deploying a mix of technologies to reduce labor and improve execution. This includes AI, along with RFID and computer vision, where it is delivering measurable results.

What Questions are Addressed?

• What store execution priorities (inventory accuracy, labor productivity, checkout experience, shrink control) are driving investment over the next 12 months, and how are macro headwinds shaping them?
• How are retailers improving inventory visibility and omnichannel fulfillment, and where do RFID, computer vision, OCR, and workflow integration fit into the operations?
• In what ways are retailers modernizing checkouts, and how are they balancing speed, reliability, shopper experience, and loss prevention?
• How is the shopper journey evolving toward self-service (i.e., self-checkout, scan-and-go, smart carts), and how is this being scaled?
• How are retailers enabling the frontline workforce (communications, training, and engagement), and what is reducing friction and improving adoption?
• How do device specifications (including NPU adoption), connectivity, and integrations influence time-to-value and ROI for AI-enabled store workflows?

Who Should Read this Report?

This report should be read by retail IT and operations leaders and supporting solution providers, including:

• Retail CIO/CTO and IT leadership
• Store operations, field operations, and execution leaders
• Omnichannel, e-commerce fulfillment, and inventory management leaders
• Loss prevention, fraud, and asset protection leaders
• Frontline workforce enablement and employee experience stakeholders
• Retail technology vendors and systems integrators

Organizations Listed in this Report

• Able Systems
• Amazon
• Apple
• Aptos
• Avery Dennison
• Beijing Silion
• Bixolon
• Blue Bamboo Systems
• Bluebird Corp
• Brother
• CAEN RFID
• Caper Carts
• Chainway
• Cipherlab
• Citizen Systems
• Datalogic
• Dell
• Denso Wave
• DRS Tactical Systems
• DT Research
• Durabook
• Epson
• FEIG
• Focal Systems
• Fujitsu
• Getac
• Google
• Honeywell
• HP
• iData
• INVENGO/TAGSY S
• IPC
• Kyocera
• Legion
• Lenovo
• M3 Mobile
• Meferi
• Metric
• Microsoft
• Mildef
• Mobile Demand
• Motorola Solutions
• Newland AIDC
• Nordic ID (Brady)
• Panasonic
• Point Mobile Co.
• Printek
• ProGlove
• Quail Digital
• RodinBell
• RuggON
• SATO
• Samsung
• Scandit
• SEUIC
• SII
• Sonim
• Star Micronics
• Supoin
• Theatro
• Thing Magic/Jadak
• Toshiba TEC
• TSC
• UKG
• Unitech
• Urovo
• VoCoVo
• Winmate
• Woosim Systems
• WorkJam
• Zebra

Executive Summary

Retailers are redefining the role of the store. Beyond traditional selling, stores are expected to function as fulfillment nodes, service hubs, and brand experience environments while supporting a shopper journey that includes more self-service as customer preferences evolve as well. This shift raises expectations for store execution at a time when retailers face margin pressure, ongoing labor constraints around recruiting, retention, scheduling, and engagement, and elevated shrink and organized retail crime risk. As a result, retailers are prioritizing initiatives that deliver outcomes quickly and reduce complexity for store teams.

Inventory accuracy and on-shelf availability are fundamental to store performance and omnichannel fulfillment. Retailers continue to invest in approaches that improve visibility and execution, including RFID and computer vision to reduce out-of-stocks and overstocks and improve pick and replenishment. Checkout modernization is also advancing, but self-service is often weighed against reliability and shrink risk, which makes clear the need to align the shopper experience and loss prevention strategies in order to achieve scale.

AI is increasingly being adopted as an enabler, and it is most valuable when it converts operational signals into prioritized actions, real-time guidance, or aids decision-making for associates and managers. At the same time, AI does not solve store execution on its own, and its integration often depends on device reliability, connectivity, and legacy systems integration, along with a streamlined associate experience.

Here, "AI" refers to capabilities that help make store operations more reliable and less labor-intensive. This includes operational AI (analytics for forecasting and optimization), workflow AI (turning signals into prioritized tasks), device AI (on-device computer vision and OCR to speed data capture), and generative AI (search, summarization, and real-time guidance for associates).

Key Findings

• Stores are being redefined, raising execution expectations. Retail locations are increasingly expected to support sales, fulfillment, service, and experience, while self-service becomes a larger part of the shopper experience. This is expanding the scope and complexity of store execution, and the associate remains central to making it work.
• Margin pressure and labor constraints are the strongest headwinds. Retailers are prioritizing solutions with clear ROI with a fast time-to-value and are avoiding initiatives that add operational complexity without also in turn reducing labor or improving execution.
• The global retail device market is already sizable, generating about $3.4B from just over 7M devices in 2024 and projected to reach roughly $4.0B and 8.6M devices by 2029. This reflects low single digit annual growth as retailers refresh older hardware and expand device deployments across more stores, roles, and workflows.
• Store technology fleets are fragmented and reliability is critical. Smartphones, tablets, and handheld mobile computers are deployed with scanners and a myriad of additional apps. Retailers are increasingly prioritizing ease-of-use, battery life, and ruggedness to increase uptime.
• Simplification is now a frontline adoption requirement. App bloat, multiple logins, and device fragmentation cause frustration and reduce consistent usage. Retailers are looking to consolidate workflows and improve communication, where hands-free, wearable/voice-enabled approaches can reduce friction and keep associates on customer-facing activities.
• Inventory accuracy and customer experience remain top operational priorities. Retailers continue to focus on improving inventory management/accuracy and customer engagement, reinforcing that inventory accuracy underpins most store KPIs and performance outcomes.
• Omnichannel fulfillment gaps are because of visibility and execution more than automation. Even when systems show positive on-hand inventory, associates and pickers often struggle to locate items quickly, leading to missed picks, substitutions, and customer dissatisfaction.
• Retailers are pursuing multi-technology strategies. Workflow integration, RFID, computer vision, OCR, and AI-based forecasting/analytics are being combined to improve inventory visibility and demand alignment and to reduce out-of-stocks and overstocks.
• Checkout modernization continues, but self-service expansion is constrained by reliability and shrink risk. Retailers will scale self-checkout, scan-and-go, and smart carts only when they can maintain acceptable loss levels while preserving a positive experience for honest shoppers.
• Loss prevention programs are increasingly shaped by fragmentation and organized retail crime. Retailers are looking for workflows that narrow the when/where of suspicious activity, reduce investigative labor, and improve real-time visibility across systems.
• The store device base is becoming more AI-ready, and adoption is accelerating through refresh cycles. Over half of respondents report already deploying NPU-capable mobile devices, and another third plan adoption in the next upgrade cycles, supporting a near-term shift toward more practical on-device computer vision/OCR and improved resilience for store workflows.
• Retail media networks and personal shopping platforms are extending into in-store touchpoints. In-store signage and smart carts represent growing areas of interest, but success depends on operational discipline, execution consistency, content accuracy, and measurement.

Table of Contents

Inside this Report

What Questions are Addressed?

Who Should Read this Report?

Organizations Listed in this Report

Executive Summary

• Key Findings

2. Retail Priorities and Investment Initiatives

3. Macro Challenges Facing Retailers

4. Store Technology Baseline and Connectivity Constraints

• 4.1 Frontline device baseline and deployment constraints
• 4.2 Connectivity constraints and why they matter for real-time and AI-enabled workflows
• 4.3 Market Size & Forecast Context
• 4.4 Vendor Landscape Snapshot

5. Omnichannel Fulfillment and Inventory Visibility

6. Checkout Modernization and Loss Prevention

7. Frontline Workforce Enablement

8. AI Adoption, NPU Devices, Use Cases, and Barriers

• 8.1 On-device AI and NPUs in plain language
• 8.2 Priority AI use cases by operational area
• 8.3 Barriers to adoption and scaling

9. Personal Shopping Platforms and the Rise of Retail Media Networks

• 9.1 Defining the landscape
• 9.2 Retail media network expansion into in-store touchpoints

APPENDIX

• Appendix A: Macro challenge priority detail (survey)
• Appendix B: Inventory visibility, RFID, and fulfillment detail (survey)
• Appendix C: Checkout and loss prevention detail (survey)
• Appendix D: Self-service, personal shopping, smart carts, and RMN detail (survey)
• Appendix E: Connectivity and network readiness (survey)
• Appendix F: Piloting and operationalization constraints (survey)
• Appendix G: AI importance by operational domain (survey)

RESEARCH METHODOLOGY

• Survey methodology
• Market model methodology
• Vendor share methodology

Vendor Profiles

About the Authors

About VDC Research

About

List of Exhibits

Report Exhibit

• Exhibit 1 Respondent Department or Functional Role
• Exhibit 2 Respondent Title or Job Function
• Exhibit 3 Issuance of Mobile Devices to Frontline Workers
• Exhibit 4 Involvement in Mobile Device Strategy and Purchasing
• Exhibit 5 Headquarters Region
• Exhibit 6 Asia/Pacific - Headquarters Country
• Exhibit 7 Organization Size by Number of Employees
• Exhibit 8 Primary Industry
• Exhibit 9 Retail Segment Classification
• Exhibit 10 Leading Retail Industry Challenges in 2025
• Exhibit 11 Retail Challenge Priority: Labor Availability and Retention
• Exhibit 12 Retail Challenge Priority: Aligning Inventory with Customer Demand
• Exhibit 13 Retail Challenge Priority: Theft Detection, Loss Prevention, and ORC
• Exhibit 14 Retail Challenge Priority: Customer Experience and Engagement
• Exhibit 15 Retail Challenge Priority: Supply Chain Disruptions
• Exhibit 16 Retail Challenge Priority: In-Store Connectivity and Employee Communication
• Exhibit 17 Retail Challenge Priority: Unoptimized Checkout Process
• Exhibit 18 Retail Challenge Priority: Sustainability and Regulatory Compliance
• Exhibit 19 Retail Challenge Priority: Omnichannel Fulfillment
• Exhibit 20 Retail Challenge Priority: Rising Cost and Margin Pressure
• Exhibit 21 Operational Initiatives Prioritized Next 12 Months
• Exhibit 22 Retail Technology Investment Priorities Next 12 Months
• Exhibit 23 Primary Omnichannel Fulfillment Challenges
• Exhibit 24 Technologies Addressing Omnichannel Fulfillment Challenges
• Exhibit 25 Primary Loss Prevention and ORC Challenges
• Exhibit 26 Technologies Addressing Loss Prevention and ORC Challenges
• Exhibit 27 Primary Frontline Workforce Enablement Challenges
• Exhibit 28 Technologies Addressing Workforce Enablement Challenges
• Exhibit 29 Primary Inventory Visibility and Demand Alignment Challenges
• Exhibit 30 Technologies Improving Inventory Visibility and Demand Alignment
• Exhibit 31 Primary Checkout Experience Challenges
• Exhibit 32 Technologies Improving Checkout Experience
• Exhibit 33 Devices Used by Frontline Mobile Workers
• Exhibit 34 Top Features Driving Adoption of Frontline Mobile Devices
• Exhibit 35 Leading Challenges Deploying Mobile Devices to Frontline Workers
• Exhibit 36 Priority of RFID for Product Identification and Tracking
• Exhibit 37 Priority of Mobile POS Devices
• Exhibit 38 Priority of Personal Shopping Devices
• Exhibit 39 Priority of Personal Shopping Apps
• Exhibit 40 Priority of Smart Carts in Retail
• Exhibit 41 Priority of Smart Lockers for Pickup and Returns
• Exhibit 42 Priority of Frictionless "Just Walk Out" Checkout
• Exhibit 43 Priority of Scanning Self-Checkout Solutions
• Exhibit 44 Perceived Benefits of RFID Deployment
• Exhibit 45 Perceived Benefits of Personal Shopping Devices or Apps
• Exhibit 46 Perceived Benefits of Smart Carts
• Exhibit 47 Perceived Benefits of Scanning Self-Checkout Solutions
• Exhibit 48 Primary POS Form Factors Leveraged
• Exhibit 49 Perceived Benefits of Mobile POS Devices
• Exhibit 50 In-Store Touchpoints for Retail Media Network Opportunities
• Exhibit 51

Wi-Fi Versions Deployed in Retail Facilities

• Exhibit 52 Impact of Wireless Network on Adoption of New Technologies
• Exhibit 53 Connectivity Issues as a Driver of IT Support Tickets
• Exhibit 54 Concern About Cost of Maintaining Wireless Network
• Exhibit 55 Sufficiency of Network Security to Safeguard Internal Data
• Exhibit 56 Visibility and Control of Network Configuration
• Exhibit 57 Impact of Network Performance on Customer and Associate Experience
• Exhibit 58 Scalability of Wireless Network to Meet Future Capacity Demands
• Exhibit 59 Perceived Value of Streamlining Technology Piloting Process
• Exhibit 60 Impact of Pilot Complexity on Ability to Test New Technologies
• Exhibit 61 Progress of New Technologies Beyond Pilot Phase
• Exhibit 62 Internal Resourcing for Mobile Device Fleet Management
• Exhibit 63 Perceived Benefits of Externally Managed Mobile Device Deployments
• Exhibit 64 Adoption Intent for Devices with Dedicated NPUs
• Exhibit 65 Priority of AI for Customer Engagement
• Exhibit 66 Priority of AI for Demand Forecasting and Inventory Optimization
• Exhibit 67 Priority of AI for Checkout and Loss Prevention
• Exhibit 68 Priority of AI-Driven Associate Enablement
• Exhibit 69 Priority of AI for Supply Chain and Logistics Optimization
• Exhibit 70 Priority of AI for Pricing and Promotions
• Exhibit 71 Top Perceived AI Use Cases in Retail
• Exhibit 72 Top Barriers to Deploying AI-Enabled Solutions
• Exhibit 73 Areas Addressed by Organizational AI Policy
• Exhibit 74 Retail Device Market Forecast - Global (Revenue, Units, ASP)
• Exhibit 75 Retail Device Market Forecast - Americas (Revenue, Units, ASP)
• Exhibit 76 Retail Device Market Forecast - EMEA (Revenue, Units, ASP)
• Exhibit 77 Retail Device Market Forecast - APAC (Revenue, Units, ASP)
• Exhibit 78 2024 Worldwide Vendor Shipments and Shares of Rugged Handheld Computers for Retail
• Exhibit 79 2024 Worldwide Vendor Shipments and Shares of Personal Shopping Devices for Retail
• Exhibit 80 2024 Worldwide Vendor Shipments and Shares of Handheld RFID Readers for Retail
• Exhibit 81 2024 Worldwide Vendor Shipments and Shares of General-Purpose Rugged Handhelds for Retail
• Exhibit 82 2024 Worldwide Vendor Shipments and Shares of Rugged Tablets for Retail
• Exhibit 83 2024 Worldwide Vendor Shipments and Shares of Consumer Tablets (Non-Rugged) for Retail
• Exhibit 84 2024 Worldwide Vendor Shipments and Shares of Rugged Smartphones for Retail
• Exhibit 85 2024 Worldwide Vendor Shipments and Shares of Consumer Smartphones (Non-Rugged) for Retail
• Exhibit 86 2024 Worldwide Vendor Shipments and Shares of Wearables for Retail
• Exhibit 87 2024 Worldwide Vendor Shipments and Shares of Fixed RFID Readers for Retail
• Exhibit 88 2024 Worldwide Vendor Shipments and Shares of Mobile Printers for Retail