优化零售店营运以满足现代消费者的需求：提升员工能力、库存管理、订单处理、自助服务和损失预防。

随着销售、履约、服务和自助服务日益成为驱动力，零售商店在适应不断变化的购物体验的过程中，面临着以更少的资源实现更多目标的挑战。同时，他们还必须应对利润率压力、人手不足以及库存耗尽风险日益增加等挑战。未来12个月，零售商正朝着几个明确的目标投资。一是弥合库存可见度和全通路营运之间的差距；二是实现结帐流程和顾客自助服务的现代化，同时损失预防措施不受影响；三是提高第一线员工的生产力、培训水准和参与度。在这些领域，零售商正在整合并应用各种技术来降低人事费用并提高营运效率，包括人工智慧、无线射频识别和电脑视觉，并且已经取得了可量化的成果。

本报告主要探讨的问题

• 未来 12 个月内，推动投资的门市营运重点是什么（库存准确性、劳动生产力、结帐体验、损耗控制措施）？宏观经济逆风又将如何影响这些重点？
• 零售商如何提高库存可见度和全通路履约？ RFID、电脑视觉、OCR 和工作流程整合等技术正在他们营运的哪些环节中得到应用？
• 零售商如何实现结帐流程现代化？他们如何平衡速度、可靠性、客户体验和损失预防？
• 顾客购物体验如何朝向自助服务（自助结帐系统、扫码购、智慧购物车等）发展，以及其部署范围如何扩大？
• 零售商如何支持第一线员工（沟通、培训、参与等），哪些因素可以减少摩擦并促进采用？
• 设备规格（包括 NPU 部署）、连接性和整合如何影响 AI 驱动的店内工作流程的实现时间和投资回报率？

上市机构

• 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

主要发现

• 门市的角色正在被重新定义，人们对其绩效的期望也越来越高。零售门市越来越需要兼顾销售、履约、服务和体验，而自助服务也正成为顾客体验的重要组成部分。这增加了门市营运的范围和复杂性，而员工在门市的顺畅营运中仍然扮演着核心角色。
• 最大的不利因素是利润率承压和人手不足。零售商优先考虑那些能够提供明确投资报酬率和快速实现价值的解决方案，并避免那些只会增加营运复杂性而无法降低人事费用或提高营运效率的措施。
• 全球零售设备市场规模已相当可观，2024 年市场规模约 34 亿美元，设备数量略高于 700 万台，预计到 2029 年将达到约 40 亿美元和 860 万台设备。这反映出，随着零售商升级旧硬体并在更多门市、职位和工作流程中部署设备，年增长率仍保持在个位数低点。
• 门市的科技环境分散，可靠性至关重要。智慧型手机、平板电脑和手持行动电脑都配备了扫描器和无数其他应用程式。零售商越来越重视易用性、电池续航力和耐用性，以提高运作。
• 简化流程如今已成为现场实施的关键要求。应用程式臃肿、需要多次登入以及装置分散会导致员工沮丧，并阻碍其持续使用。零售商正寻求整合工作流程并改善沟通，利用免持和穿戴/语音控制等方式减少营运摩擦，使员工能够专注于客户服务。
• 库存准确性和客户体验仍然是营运中的重中之重。零售商持续致力于提升库存管理、准确性和客户参与，并重申库存准确性是大多数门市关键绩效指标和绩效的基础。
• 全通路履约的挑战较源自于可见性和执行力，而非自动化。即使系统显示库存充足，员工和负责人也常常难以快速找到商品，导致漏拣、使用替代品，最终造成顾客不满。
• 零售商正在推行融合多种技术的策略。他们将工作流程、RFID、电脑视觉、OCR 和基于人工智慧的预测分析等技术整合起来，以提高库存可见性和与需求的匹配度，从而减少缺货和库存积压。
• 儘管结帐流程日趋现代化，但自助服务的推广仍受到可靠性和库存损耗风险的限制。零售商只有在能够为诚信顾客提供良好体验并将损失控制在可接受范围内的情况下，才会推广自助结帐系统、扫码购和智慧购物车等服务。
• 零售业的碎片化和有组织零售犯罪的猖獗对损失预防计划的影响日益加剧。零售商正在寻求能够精准定位可疑活动发生的时间和地点、减少调查所需工作量并提高系统即时可见性的工作流程。
• 门市内部的设备基础设施正日益人工智慧化，部署速度也随着更新周期而加快。超过一半的受访者表示已拥有配备NPU（网路处理单元）的行动设备，另有三分之一的受访者计划在下一次升级週期中部署。这将加速向更实用的设备内电脑视觉/OCR（光学字元辨识）技术的过渡，并提高门市工作流程的容错能力。
• 零售媒体网路和个人购物平台正向店内触点拓展。店内指示牌和智慧购物车是日益受到关注的领域，但它们的成功取决于营运规范、执行一致性、内容准确性和效果衡量能力。

本报告调查了优化零售店营运以满足当今消费者需求的趋势，总结了零售业面临的主要挑战、应对这些挑战的各种技术、零售商的优先投资领域以及应用案例。

目录

本报告内容

本报告探讨的问题

本报告的目标受众

本报告中列出的组织

执行摘要

• 主要发现

第二章：零售业优先事项与投资倡议

第三章：零售商面临的宏观经济挑战

第四章 门市技术基准及连结性限制

• 目前现场设备的状况及其应用限制。
• 连接性限制及其对即时和人工智慧工作流程的重要性
• 市场规模及预测背景
• 供应商情况

第五章：全通路履约与库存视觉化

第六章：收银现代化与损失预防

第七章：提升现场工作人员的技能

第八章：人工智慧应用、NPU设备、用例和障碍

• 对装置上的人工智慧和神经网路处理单元 (NPU) 进行简单易懂的说明
• 按业务领域分類的优先人工智慧应用案例
• 实施和扩展的障碍

第九章：个人购物平台与零售媒体网络的兴起

• 市场结构定义
• 将零售媒体网路扩展到店内接点

附录

• 附录A：宏观问题优先排序详情（调查）
• 附录 B：库存视觉化、RFID 和履约详情（研究）
• 附录C：结帐及损失预防详情（调查）
• 附录 D：自助服务、个人购物、智慧购物车和 RMN（研究）的详细信息
• 附录 E：连结性和网路准备（调查）
• 附录 F：试点运作和运作实施中的限制因素（调查）
• 附录G：人工智慧在各业务领域的重要性（调查结果）

调查方法

供应商简介

关于作者

关于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