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2118260

機器客戶平台：市場佔有率分析、產業趨勢與統計、成長預測（2026-2031）

Machine Customer Platform - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2026 - 2031)
出版日期: | 出版商: Mordor Intelligence | 英文 181 Pages | 商品交期: 2-3個工作天內

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簡介目錄

據 Mordor Intelligence 稱，2025 年機器客戶平台市場價值 4.2 億美元，預計到 2031 年將達到 16.3 億美元，而 2026 年為 5.1 億美元，預測期（2026-2031 年）的複合年成長率為 26.16%。

機器客戶平台-市場-IMG1

本報告按平台（機器平台、客戶平台、電商平台等）、部署模式（雲端部署、混合部署、本地部署）、企業規模（大型企業、中小企業）、應用領域（IT與電信、銀行、金融服務和保險、汽車與運輸、醫療保健與生命科學等）以及地區進行細分。市場預測以美元計價。

全球機器客戶平台市場趨勢與洞察

擴大人工智慧驅動的採購和補貨方式的應用

人工智慧驅動的購買流程正從產品發現轉向產品選擇、下單和重複購買。根據 Shopify 預測，到 2025 年，其平台上的人工智慧驅動訂單將成長 15 倍，而人工智慧目錄的轉換率將是基於抓取資料的建議的兩倍。這些結果凸顯了建立一個機器客戶平台市場的重要性，以便在代理商識別出合適的產品後管理交易。這些結果也強調了市場為何需要可靠的產品記錄和清晰的權限設定。連網設備可以檢測庫存短缺和維護需求，並啟動已通過核准的補貨流程。這使得代理商能夠在使用者和組織設定的約束範圍內開展業務，從而建立持續的商業關係。

擴展機器可讀產品和服務數據

機器可讀的目錄資料正成為自動化商務的實際需求。 Mirakl 在 2026 年 4 月指出，只有不到 1% 的產品頁面能夠被大規模語言模型讀取、比較並用於交易。現有的大部分目錄都是為關鍵字搜尋和視覺瀏覽而建構的，而非針對精確的產品或商業術語。 OpenAI 的產品資訊流規格要求必須包含最新的價格、庫存和退貨政策欄位。目錄管理正逐漸從促銷職能轉變為商業營運職能。擁有完整產品記錄的經銷商在透過代理商獲取需求方面更具優勢。

在非人類購買者的身份、同意和責任方面存在差距。

商業規則通常假定購買決策和接受行為均由人做出。因此，當代理人在指定授權範圍內選擇商品、批准替代品或處理付款時，就會產生不確定性。 CERRE 的一項研究發現，歐洲消費者法缺乏針對代理人造成的缺陷的責任明確框架。未解決的問題包括同意、授權委託以及對錯誤結果的責任。 Visa 的可信任代理協議和 Experian 的代理信任旨在將授權代理人與經過驗證的使用者或組織聯繫起來。對非人類購買者的法律處理仍將是實現完全自主購買的一大限制因素。

細分市場分析

到2025年，機器客戶商務平台將佔據34.82%的市場。該領域涵蓋產品發現、購物車創建、支付和訂單管理。由於這些功能與收入和購買行為直接相關，企業通常會從這些環節開始採用人工智慧。該領域也支援分階段部署，讓企業在添加多代理流程之前先實現商業自動化。 Shopify的商務功能展示如何將產品目錄存取和交易流程與人工智慧管道結合。

代理識別和信任平台預計將在2026年至2031年間以27.34%的複合年成長率成長。這些平台用於確定人工智慧代理是否被授權代表特定個人或公司行事。隨著代理的角色從單純的建議轉向支付、合約和採購等實際操作，這種需求將變得更加迫切。 Experian於2026年4月推出了代理信任（Agent Trust）服務，而Visa則於2026年7月在其歐洲銀行網路中推廣了可信任代理協議（Trusted Agent Protocol）。隨後，編配、分析和管治平台將支援多階段操作、監控、策略執行和文件記錄。

到 2025 年，雲端部署將佔機器客戶平台市場的 68.14%。雲端服務支援快速模型更新、強大的運算能力和便利的協定整合。這些特性在早期實驗階段尤其重要，因為團隊需要快速調整工作流程。對於不希望管理整個技術堆疊的公司而言，這種模式可以減輕營運負擔。在資料管理法規允許外部處理的情況下，雲端仍然是首選。

混合部署預計將在 2026 年至 2031 年間以 26.91% 的複合年成長率成長。這種方法利用雲端管理的代理介面，同時將敏感的定價資訊、合規相關資訊或客戶記錄保存在本地系統中。這種架構解決了整個交易上下文可能經過第三方人工智慧層的擔憂。在公共雲端的使用受到有關健康數據、主權或國家安全法規限制的情況下，本地部署仍然發揮著至關重要的作用。 Salesforce 將 Agentforce Commerce 描述為一個可與商家自有資料基礎架構協同工作的可攜式層。

區域分析

2025年，北美將佔據機器客戶平台市場32.59%的佔有率。美國擁有大規模的供應商群體，並且是代理式商業系統的早期採用者。美國公司在商業、支付和代理檢驗協議的製定中發揮了核心作用。加州AB 316法案於2026年1月1日生效，該法案正日益關注人工智慧驅動的商業活動的問責制。此外，Shopify在2025年人工智慧驅動訂單量成長15倍，也顯示了消費者對電商平台的強勁需求。

預計亞太地區在2026年至2031年間將以27.28%的複合年成長率成長。該地區融合了中國的數位商務基礎設施、印度對數位服務的需求以及東南亞以行動優先的支付生態系統。美團於2025年下半年推出了小美AI助手，使用戶能夠理解意圖並盡可能減少螢幕互動即可完成交易。該地區的成長取決於可靠的支付方式和清晰的助理權限規則。

在歐洲，監管要求的增加促使人們對管治工具的需求日益成長，進而塑造著市場格局。根據歐盟人工智慧法案第9條的規定，高風險系統提交相關文件的截止日期為2026年8月。 CERRE指出，關於代理程式故障導致的消費者保護問題仍未解決。南美洲仍處於起步階段，而中東和非洲則透過醫療保健和公共服務領域的人工智慧採購活動迅速發展。部署水準取決於支付基礎設施、監管法規和結構化供應商資料的成熟度。

其他好處：

  • Excel格式的市場預測（ME）表
  • 3個月的分析師支持

目錄

第1章：引言

  • 研究假設和市場定義
  • 調查範圍

第2章：調查方法

第3章執行摘要

第4章 市場狀況

  • 市場概覽
  • 市場促進因素
    • 人工智慧在採購和補貨方面的應用越來越廣泛。
    • 擴展機器可讀產品和服務數據
    • 基於代理的商業協議標準化
    • 企業對自主B2B交易工作流程的需求
    • 連網設備和物聯網交易的增加是觸發因素。
    • 在決策層面引入主動式人工智慧，降低推理成本
  • 市場限制因素
    • 非人類買家在身分、同意和責任上的差距
    • 分銷商的產品目錄、定價和政策資料不完整。
    • 消除商家中介功能和第一方資料外洩風險。
    • 存在出錯、欺詐和不可逆轉購買的風險。
  • 宏觀經濟因素對市場的影響
  • 產業價值鏈分析
  • 科技趨勢
  • 監理情勢
  • 波特五力分析

第5章 市場規模與成長預測

  • 按平台
    • 機器客戶商務平台
    • 代理編配平台
    • 代理身份和信任平台
    • 分析與管治平台
  • 按部署模式
    • 雲
    • 混合
    • 現場
  • 按公司規模
    • 大公司
    • 小型企業
  • 透過使用
    • 資訊科技/通訊
    • BFSI
    • 汽車和交通運輸
    • 醫療保健和生命科學
    • 能源與公共產業
    • 工業製造
    • 旅遊與飯店
    • 其他
  • 按地區
    • 北美洲
      • 美國
      • 加拿大
      • 墨西哥
    • 南美洲
      • 巴西
      • 阿根廷
      • 其他南美國家
    • 歐洲
      • 德國
      • 英國
      • 法國
      • 俄羅斯
      • 西班牙
      • 其他歐洲國家
    • 亞太地區
      • 中國
      • 日本
      • 印度
      • 韓國
      • 東南亞
      • 其他亞太國家
    • 中東和非洲
      • 中東
        • 沙烏地阿拉伯
        • 阿拉伯聯合大公國
        • 其他中東國家
      • 非洲
        • 南非
        • 奈及利亞
        • 其他非洲國家

第6章 競爭情勢

  • 市場集中度
  • 策略趨勢
  • 市佔率分析
  • 公司簡介
    • commercetools GmbH
    • VTEX
    • Shopify Inc.
    • BigCommerce Holdings, Inc.
    • Elastic Path Software Inc.
    • Spryker Systems GmbH
    • Salesforce, Inc.
    • Kibo Software, Inc.
    • Intershop Communications AG
    • Sana Commerce BV
    • Shopware AG
    • Virto Commerce, Inc.
    • Oro, Inc.
    • Mirakl SAS
    • SCAYLE GmbH
    • Commerce Layer, Inc.
    • Fabric, Inc.
    • Constructor.io, Inc.
    • Algolia, Inc.
    • Bloomreach, Inc.

第7章 市場機會與未來展望

簡介目錄
Product Code: 101012

According to Mordor Intelligence, the machine customer platform market size was valued at USD 0.42 billion in 2025 and estimated to grow from USD 0.51 billion in 2026 to reach USD 1.63 billion by 2031, at a CAGR of 26.16% during the forecast period (2026-2031).

Machine Customer Platform - Market - IMG1

This report is Segmented by Platform (Machine Customer Commerce Platforms, and More), Deployment Model (Cloud, Hybrid, and On-Premises), Enterprise Size (Large Enterprises, and Small and Mid-Sized Enterprises), Application, (IT and Telecommunication, BFSI, Automotive and Transportation, Healthcare and Life Sciences, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Global Machine Customer Platform Market Trends and Insights

Rising Adoption of AI-Mediated Buying and Reordering

AI-assisted buying is moving from product discovery into product selection, order setup, and repeat purchasing. Shopify reported that AI-driven orders on its platform increased 15-fold during 2025, while AI catalog surfaces converted at twice the rate of recommendations based on scraped data. These results support the need for a Machine Customer Platform Market to manage transactions after an agent identifies a suitable product. They also show why the Machine Customer Platform Market needs dependable product records and clear authority settings. Connected devices can identify depletion or maintenance needs and initiate approved replenishment workflows. This enables an ongoing commercial relationship in which an agent acts within the limits set by its user or organization.

Expansion of Machine-Readable Product and Service Data

Machine-readable catalog data is becoming a practical requirement for automated commerce. Mirakl stated in April 2026 that fewer than 1% of product pages were ready for large language models to read, compare, and use in transactions. Many existing catalogs were built for keyword search and visual browsing rather than for exact product and commercial terms. The OpenAI product feed specification requires current pricing, inventory, and return policy fields. Catalog management is becoming a commercial operations function rather than a promotional task. Merchants with complete product records are better positioned to receive agent-mediated demand.

Identity, Consent, and Liability Gaps for Nonhuman Buyers

Commercial rules generally assume that a person makes or accepts a purchase. This creates uncertainty when an agent selects an item, approves a substitution, or submits payment within a pre-set authority. CERRE found that European consumer law does not provide a clear liability structure for agent-initiated failures. The unresolved issues include consent, delegated authority, and responsibility for an incorrect result. Visa's Trusted Agent Protocol and Experian Agent Trust seek to connect an authorized agent with a verified user or organization. Legal treatment of nonhuman buyers will remain a constraint on fully autonomous purchasing.

Other drivers and restraints analyzed in the detailed report include:

  1. Standardization of Agentic Commerce Protocols
  2. Enterprise Demand for Autonomous B2B Transaction Workflows
  3. Incomplete Catalog, Pricing, and Policy Data for Agents

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Machine Customer Commerce Platforms accounted for 34.82% of the Machine Customer Platform Market share in 2025. This segment covers product discovery, cart assembly, checkout, and order management. Enterprises commonly begin here because these functions have a direct connection to revenue and purchasing activity. The segment also supports a phased deployment, allowing firms to introduce commercial automation before adding multi-agent processes. Shopify's commerce capabilities show how catalog access and transaction flows can be exposed to AI channels.

Agent Identity and Trust Platforms are projected to grow at a 27.34% CAGR from 2026 to 2031. They determine whether an AI agent has authority to act on behalf of a named person or business. This need becomes more pressing when agents move from recommendations to payment, contract, and procurement actions. Experian introduced Agent Trust in April 2026, while Visa advanced Trusted Agent Protocol across European banking networks in July 2026. Orchestration, analytics, and governance platforms then support multi-step work, monitoring, policy enforcement, and documentation.

Cloud deployment held 68.14% of the Machine Customer Platform Market share in 2025. Cloud services support rapid model updates, elastic computing capacity, and easier protocol integration. These features are useful during early experiments when teams need to adjust workflows quickly. The model can lower the operational burden for firms that do not want to manage a full technical stack. It remains the leading choice where data controls permit external processing.

Hybrid deployment is projected to grow at a 26.91% CAGR from 2026 to 2031. It uses cloud-managed agent interfaces while retaining sensitive pricing, compliance, or customer records within local systems. The structure responds to the concern that the full transaction context could pass through third-party AI layers. On-premises deployment remains relevant where health data, sovereignty, or national security controls limit public cloud use. Salesforce described Agentforce Commerce as a portable layer that works with merchant-owned data infrastructure.

Complete Report Scope:

  • By Platform
    • Machine Customer Commerce Platforms
    • Agent Orchestration Platforms
    • Agent Identity and Trust Platforms
    • Analytics and Governance Platforms
  • By Deployment Model
    • Cloud
    • Hybrid
    • On-Premises
  • By Enterprise Size
    • Large Enterprises
    • Small and Mid-sized Enterprises
  • By Application
    • IT and Telecommunication
    • BFSI
    • Automotive and Transportation
    • Healthcare and Life Sciences
    • Energy and Utilities
    • Industrial Manufacturing
    • Travel and Hospitality
    • Other End Users
  • By Geography
    • North America
      • United States
      • Canada
      • Mexico
    • South America
      • Brazil
      • Argentina
      • Rest of South America
    • Europe
      • Germany
      • United Kingdom
      • France
      • Russia
      • Spain
      • Rest of Europe
    • Asia-Pacific
      • China
      • Japan
      • India
      • South Korea
      • Southeast Asia
      • Rest of Asia-Pacific
    • Middle East and Africa
      • Middle East
        • Saudi Arabia
        • United Arab Emirates
        • Rest of Middle East
      • Africa
        • South Africa
        • Nigeria
        • Rest of Africa

Geography Analysis

North America held 32.59% of the Machine Customer Platform Market share in 2025. The United States combines a substantial vendor base with early enterprise users of agent-based commercial systems. U.S.-based companies have played a central role in protocol development for commerce, payments, and agent verification. California's AB 316 took effect on January 1, 2026, increasing focus on responsibility for AI-initiated commercial actions. Shopify's 15-fold increase in AI-driven orders during 2025 also showed active demand on consumer-facing commerce surfaces.

Asia-Pacific is projected to grow at a 27.28% CAGR from 2026 to 2031. The region combines China's digital commerce infrastructure, India's demand for digital services, and Southeast Asia's mobile-first payment ecosystems. Meituan launched the Xiaomei AI agent in late 2025 to interpret user intent and complete transactions with minimal screen interaction. Regional growth will depend on trusted payment methods and clear rules for agent authority.

Europe is shaped by regulatory requirements that increase the need for governance tools. The EU AI Act's Article 9 documentation requirements for high-risk systems have an August 2026 deadline. CERRE has noted unresolved consumer protection questions regarding agent-initiated failures. South America is at an earlier stage, while the Middle East and Africa are building momentum through AI procurement activity in healthcare and public services. Adoption will vary with payment maturity, regulation, and structured supplier data.

  1. commercetools GmbH
  2. VTEX
  3. Shopify Inc.
  4. BigCommerce Holdings, Inc.
  5. Elastic Path Software Inc.
  6. Spryker Systems GmbH
  7. Salesforce, Inc.
  8. Kibo Software, Inc.
  9. Intershop Communications AG
  10. Sana Commerce B.V.
  11. Shopware AG
  12. Virto Commerce, Inc.
  13. Oro, Inc.
  14. Mirakl SAS
  15. SCAYLE GmbH
  16. Commerce Layer, Inc.
  17. Fabric, Inc.
  18. Constructor.io, Inc.
  19. Algolia, Inc.
  20. Bloomreach, Inc.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

  • 4.1 Market Overview
  • 4.2 Market Drivers
    • 4.2.1 Rising Adoption of AI-Mediated Buying and Reordering
    • 4.2.2 Expansion of Machine-Readable Product and Service Data
    • 4.2.3 Standardization of Agentic Commerce Protocols
    • 4.2.4 Enterprise Demand for Autonomous B2B Transaction Workflows
    • 4.2.5 Rising Connected-Device and IoT Transaction Triggers
    • 4.2.6 Decision-Grade Agentic AI and Lower Inference Costs
  • 4.3 Market Restraints
    • 4.3.1 Identity, Consent, and Liability Gaps for Nonhuman Buyers
    • 4.3.2 Incomplete Catalog, Pricing, and Policy Data for Agents
    • 4.3.3 Merchant Disintermediation and First-Party Data Leakage Risk
    • 4.3.4 Error, Fraud, and Irreversible Purchase Risk
  • 4.4 Impact of Macroeconomic Factors on the Market
  • 4.5 Industry Value-Chain Analysis
  • 4.6 Technology Outlook
  • 4.7 Regulatory Landscape
  • 4.8 Porter's Five Forces Analysis
    • 4.8.1 Threat of New Entrants
    • 4.8.2 Bargaining Power of Suppliers
    • 4.8.3 Bargaining Power of Buyers
    • 4.8.4 Threat of Substitutes
    • 4.8.5 Intensity of Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

  • 5.1 By Platform
    • 5.1.1 Machine Customer Commerce Platforms
    • 5.1.2 Agent Orchestration Platforms
    • 5.1.3 Agent Identity and Trust Platforms
    • 5.1.4 Analytics and Governance Platforms
  • 5.2 By Deployment Model
    • 5.2.1 Cloud
    • 5.2.2 Hybrid
    • 5.2.3 On-Premises
  • 5.3 By Enterprise Size
    • 5.3.1 Large Enterprises
    • 5.3.2 Small and Mid-sized Enterprises
  • 5.4 By Application
    • 5.4.1 IT and Telecommunication
    • 5.4.2 BFSI
    • 5.4.3 Automotive and Transportation
    • 5.4.4 Healthcare and Life Sciences
    • 5.4.5 Energy and Utilities
    • 5.4.6 Industrial Manufacturing
    • 5.4.7 Travel and Hospitality
    • 5.4.8 Other End Users
  • 5.5 By Geography
    • 5.5.1 North America
      • 5.5.1.1 United States
      • 5.5.1.2 Canada
      • 5.5.1.3 Mexico
    • 5.5.2 South America
      • 5.5.2.1 Brazil
      • 5.5.2.2 Argentina
      • 5.5.2.3 Rest of South America
    • 5.5.3 Europe
      • 5.5.3.1 Germany
      • 5.5.3.2 United Kingdom
      • 5.5.3.3 France
      • 5.5.3.4 Russia
      • 5.5.3.5 Spain
      • 5.5.3.6 Rest of Europe
    • 5.5.4 Asia-Pacific
      • 5.5.4.1 China
      • 5.5.4.2 Japan
      • 5.5.4.3 India
      • 5.5.4.4 South Korea
      • 5.5.4.5 Southeast Asia
      • 5.5.4.6 Rest of Asia-Pacific
    • 5.5.5 Middle East and Africa
      • 5.5.5.1 Middle East
        • 5.5.5.1.1 Saudi Arabia
        • 5.5.5.1.2 United Arab Emirates
        • 5.5.5.1.3 Rest of Middle East
      • 5.5.5.2 Africa
        • 5.5.5.2.1 South Africa
        • 5.5.5.2.2 Nigeria
        • 5.5.5.2.3 Rest of Africa

6 COMPETITIVE LANDSCAPE

  • 6.1 Market Concentration
  • 6.2 Strategic Moves
  • 6.3 Market Share Analysis
  • 6.4 Company Profiles (includes Global Level Overview, Market Level Overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share, Products and Services, Recent Developments)
    • 6.4.1 commercetools GmbH
    • 6.4.2 VTEX
    • 6.4.3 Shopify Inc.
    • 6.4.4 BigCommerce Holdings, Inc.
    • 6.4.5 Elastic Path Software Inc.
    • 6.4.6 Spryker Systems GmbH
    • 6.4.7 Salesforce, Inc.
    • 6.4.8 Kibo Software, Inc.
    • 6.4.9 Intershop Communications AG
    • 6.4.10 Sana Commerce B.V.
    • 6.4.11 Shopware AG
    • 6.4.12 Virto Commerce, Inc.
    • 6.4.13 Oro, Inc.
    • 6.4.14 Mirakl SAS
    • 6.4.15 SCAYLE GmbH
    • 6.4.16 Commerce Layer, Inc.
    • 6.4.17 Fabric, Inc.
    • 6.4.18 Constructor.io, Inc.
    • 6.4.19 Algolia, Inc.
    • 6.4.20 Bloomreach, Inc.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

  • 7.1 White-Space and Unmet-Need Assessment