查看購物車
  • Simplified Chinese
  • English
  • Japanese
  • Korean
封面
市場調查報告書
商品編碼
1797991

2032 年可解釋人工智慧市場預測：按組件、部署、應用、最終用戶和地區進行的全球分析

Explainable AI Market Forecasts to 2032 - Global Analysis By Component (Solution and Services), Deployment, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，全球可解釋人工智慧市場預計在 2025 年將達到 85 億美元，到 2032 年將達到 228 億美元，預測期內的複合年成長率為 15%。

可解釋人工智慧 (XAI) 是指能夠向人類使用者提供透明、可理解和可解釋結果的人工智慧系統。與「黑箱」模型不同，XAI 允許使用者理解 AI 決策的製定過程，從而建立信任並實現課責。這在可解釋性至關重要的領域尤其重要，例如醫療保健、金融和法律。透過使演算法更易於訪問，使洞察更具可操作性，XAI 彌合了複雜的機器學習輸出與現實世界人類決策之間的差距。

對人工智慧透明度和課責的需求日益成長

對人工智慧系統透明度和課責日益成長的需求，是推動可解釋人工智慧市場發展的關鍵驅動力。隨著金融、醫療保健和法律等受監管行業的人工智慧應用日益普及，相關人員正在尋求演算法決策的清晰度。倫理擔憂、管治壓力以及《歐盟人工智慧法案》等法律規範，正推動企業採用可解釋模型。這種日益成長的建立用戶信任和確保合規性的需求，正在加速全球市場對可解釋工具和框架的投資。

模型可解釋性的技術複雜性

阻礙可解釋人工智慧市場發展的關鍵因素是解釋複雜機器學習模型的技術複雜性。深度學習演算法雖然高度準確，但通常如同“黑盒子”，其提供的人類可讀性有限。開發既能保持模型性能，又能提供可理解解釋的技術仍然充滿挑戰。這種複雜性增加了實施時間和成本，需要專業知識，也為希望將可解釋人工智慧 (XAI) 整合到現有人工智慧工作流程和決策支援系統中的中小企業帶來了障礙。

XAI即服務平台的成長

可解釋人工智慧即服務 (XAIaaS) 平台的興起，為模型可解釋性提供了即插即用的工具，創造了巨大的市場機會。人工智慧提供者提供的雲端基礎的解決方案簡化了整合，使企業無需大量內部專業知識即可實現可解釋性。這些平台支援即時監控、合規性報告和模型審核。隨著各行各業對符合道德規範的人工智慧的需求日益成長，這些可擴展、經濟高效的服務越來越受到企業、新興企業和政府機構的青睞，他們致力於提高自動化系統的透明度和課責。

透明度可能會暴露專有演算法

可解釋人工智慧市場面臨的最大威脅之一是專有演算法和智慧財產權的潛在洩漏。企業可能不願意採用完全透明的模型，擔心這會洩漏其競爭優勢或敏感的業務邏輯。這種在可解釋性和保密性之間的權衡，可能會限制依賴獨特專有人工智慧演算法的行業的應用。此外，攻擊者可能會利用洩漏的模型邏輯來操縱輸出，這引發了人們對系統漏洞及其被利用風險的擔憂。

COVID-19的影響：

新冠疫情加速了醫療、金融和物流等多個產業的數位轉型，包括人工智慧的應用。相關人員要求影響公共衛生、資源配置和財務結果的自動化決策保持透明。從疾病診斷到供應鏈管理，可解釋人工智慧 (XAI) 在提升人們對人工智慧主導建議的信任方面發揮了關鍵作用。這場疫情凸顯了可解釋人工智慧在高風險情境中的重要性，並增強了人們對可解釋人工智慧領域的長期興趣和投資。

預計解決方案部門將成為預測期內最大的部門

由於企業對提供模型洞察和可解釋性的高階軟體工具的需求不斷成長，預計解決方案細分市場將在預測期內佔據最大市場佔有率。這包括與模型無關的工具、視覺化儀表板以及可與現有AI工作流程無縫整合的API。企業正在投資可解釋性解決方案，以確保合規性、增強客戶信任度並提高決策品質。隨著對道德AI和管治的日益重視，提供強大的解決方案已成為企業AI策略的重要組成部分。

預計在預測期內，內部部署部分將以最高的複合年成長率成長。

由於對安全、內部AI可解釋解決方案的需求不斷成長，預計本地部署領域將在預測期內實現最高成長率。國防、銀行和醫療保健等行業更傾向於本地部署，以維護資料主權、降低延遲並保護智慧財產權。本地部署模式還能對演算法和內部基礎架構進行更嚴格的控制，從而滿足合規性要求。日益成長的網路安全擔憂以及對高度客製化的偏好，正在推動企業（尤其是在大型企業中）對這一領域的興趣。

佔比最大的地區：

預計亞太地區將在預測期內佔據最大的市場佔有率，這得益於快速數位化、政府人工智慧計畫以及金融服務和醫療保健領域人工智慧的廣泛應用。中國、印度和日本等國家正積極投資透明的人工智慧生態系統，以確保負責任的部署。隨著人工智慧新興企業數量的增加、研發支出的增加以及法律規範的不斷加強，該地區將繼續在人工智慧應用和創新方面保持領先地位。

複合年成長率最高的地區：

由於北美地區擁有強大的技術基礎設施、較高的人工智慧採用率以及對人工智慧管治的嚴格監管要求，預計其在預測期內的複合年成長率最高。醫療保健、金融服務和保險業（BFSI）以及政府部門的企業正優先考慮人工智慧系統的透明度、可解釋性和道德的決策。領先科技公司的湧現以及對負責任的人工智慧研究和標準制定的不斷投資，使北美成為xAI市場快速持續成長的中心。

免費客製化服務

此報告的訂閱者可以使用以下免費自訂選項之一：

  • 公司簡介
    • 對最多三家其他市場公司進行全面分析
    • 主要企業的SWOT分析（最多3家公司）
  • 區域細分
    • 根據客戶興趣對主要國家進行的市場估計、預測和複合年成長率（註：基於可行性檢查）
  • 競爭基準化分析
    • 根據產品系列、地理分佈和策略聯盟對主要企業基準化分析

目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 研究途徑
  • 研究材料
    • 主要研究資料
    • 次級研究資訊來源
    • 先決條件

第3章市場走勢分析

  • 驅動程式
  • 抑制因素
  • 機會
  • 威脅
  • 應用分析
  • 最終用戶分析
  • 新興市場
  • COVID-19的影響

第4章 波特五力分析

  • 供應商的議價能力
  • 買方的議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭對手之間的競爭

5. 全球可解釋人工智慧市場（按組件分類）

  • 解決方案
  • 服務

6. 全球可解釋人工智慧市場（按部署）

  • 雲
  • 本地

7. 全球可解釋人工智慧市場（按應用）

  • 詐欺和異常檢測
  • 藥物研發與診斷
  • 預測性維護
  • 供應鏈管理
  • 身分和存取管理
  • 其他用途

8. 全球可解釋人工智慧市場（按最終用戶）

  • 衛生保健
  • BFSI
  • 航太和國防
  • 零售與電子商務
  • 公共部門和公共產業
  • 資訊科技/通訊
  • 車

9. 全球可解釋人工智慧市場（按地區）

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲國家
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第10章：主要發展

  • 協議、夥伴關係、合作和合資企業
  • 收購與合併
  • 新產品發布
  • 業務擴展
  • 其他關鍵策略

第11章 公司概況

  • Microsoft Corporation
  • Alphabet Inc.（Google LLC）
  • Amazon Web Services Inc.（Amazon.com Inc.）
  • NVIDIA Corporation
  • IBM Corporation
  • Intel Corporation
  • Mphasis Limited
  • Alteryx, Inc.
  • Palantir Technologies Inc.
  • Salesforce, Inc.
  • Oracle Corporation
  • Cisco Systems, Inc.
  • Meta Platforms, Inc.（Facebook）
  • Broadcom Inc.
  • Advanced Micro Devices（AMD）
  • SAP SE
  • Twilio Inc.
  • ServiceNow, Inc.
Product Code: SMRC30361

According to Stratistics MRC, the Global Explainable AI Market is accounted for $8.5 billion in 2025 and is expected to reach $22.8 billion by 2032 growing at a CAGR of 15% during the forecast period. Explainable AI (XAI) refers to artificial intelligence systems that provide transparent, understandable, and interpretable results to human users. Unlike "black-box" models, XAI allows users to understand how AI decisions are made, which builds trust and enables accountability. It is especially critical in high-stakes sectors like healthcare, finance, and law where interpretability is essential. By making algorithms more accessible and insights more actionable, XAI bridges the gap between complex machine learning outputs and real-world human decision-making.

Market Dynamics:

Driver:

Rising demand for AI transparency and accountability

The rising demand for transparency and accountability in AI systems is a key driver fueling the Explainable AI market. As AI adoption grows in regulated industries like finance, healthcare, and legal, stakeholders require clarity on algorithmic decision-making. Ethical concerns, governance pressures, and regulatory frameworks such as the EU AI Act are pushing enterprises to adopt interpretable models. This growing need to build user trust and ensure compliance is accelerating investments in explainability tools and frameworks across global markets.

Restraint:

Technical complexity in model interpretability

A major restraint hampering the Explainable AI market is the technical complexity involved in interpreting complex machine learning models. Deep learning algorithms, while highly accurate, often function as "black boxes" with limited human-readable insight. Developing methods that maintain model performance while offering understandable explanations remains challenging. This complexity increases implementation time, costs, and requires specialized expertise, creating barriers for small and medium-sized enterprises attempting to integrate XAI into existing AI workflows and decision support systems.

Opportunity:

Growth of XAI-as-a-Service platforms

The rise of Explainable AI-as-a-Service (XAIaaS) platforms presents a significant market opportunity, offering plug-and-play tools for model interpretability. Cloud-based solutions from AI providers simplify integration and allow businesses to implement explainability without extensive in-house expertise. These platforms enable real-time monitoring, compliance reporting, and model auditing. With increasing demand across industries for ethical AI, these scalable and cost-efficient services are gaining traction among enterprises, startups, and government institutions aiming to boost transparency and accountability in automated systems.

Threat:

Risk of exposing proprietary algorithms through transparency

One of the most critical threats to the Explainable AI market is the potential exposure of proprietary algorithms and intellectual property. Companies may hesitate to adopt full transparency models for fear of revealing competitive advantages or sensitive business logic. This trade-off between explainability and confidentiality can limit adoption in industries that rely on unique, proprietary AI algorithms. Additionally, adversaries could exploit revealed model logic to manipulate outputs, creating concerns over system vulnerability and exploitation risks.

Covid-19 Impact:

The COVID-19 pandemic accelerated digital transformation, including AI adoption, across multiple sectors-especially healthcare, finance, and logistics. In this surge, explainable AI gained traction as stakeholders demanded transparency in automated decisions affecting public health, resource allocation, and financial outcomes. XAI played a crucial role in enhancing trust in AI-driven recommendations, from diagnosing diseases to managing supply chains. The pandemic highlighted the importance of interpretable AI in high-stakes scenarios, reinforcing long-term interest and investment in the Explainable AI landscape.

The solution segment is expected to be the largest during the forecast period

The solution segment is expected to account for the largest market share during the forecast period, owing to rising enterprise demand for advanced software tools that provide model insights and interpretability. These include model-agnostic tools, visualization dashboards, and APIs that integrate seamlessly with existing AI workflows. Businesses are investing in explainability solutions to ensure regulatory compliance, enhance customer trust, and improve decision-making quality. As the emphasis on ethical AI and governance grows, robust solution offerings are becoming essential components of enterprise AI strategies.

The on-premise segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the on-premise segment is predicted to witness the highest growth rate, due to growing demand for secure, in-house AI interpretability solutions. Industries such as defense, banking, and healthcare prefer on-premise deployment to maintain data sovereignty, reduce latency, and protect intellectual property. On-premise models allow tighter control over algorithms and internal infrastructure, aligning with compliance mandates. With rising cybersecurity concerns and a preference for high customization, this segment is witnessing growing interest, especially among large-scale enterprises.

Region with largest share:

During the forecast period, the Asia Pacific region is expected to hold the largest market share, driven by rapid digitalization, government AI initiatives, and the proliferation of AI in financial services and healthcare. Countries like China, India, and Japan are actively investing in transparent AI ecosystems to ensure responsible deployment. With a large number of AI startups, increasing R&D spending, and expanding regulatory oversight, the region continues to be a leader in XAI adoption and innovation.

Region with highest CAGR:

Over the forecast period, the North America region is anticipated to exhibit the highest CAGR attributed to robust technological infrastructure, high AI adoption rates, and stringent regulatory demands for AI governance. Enterprises across healthcare, BFSI, and government sectors are prioritizing transparency, interpretability, and ethical decision-making in their AI systems. The presence of leading tech firms, coupled with growing investment in responsible AI research and standard-setting, positions North America as a hub for rapid and sustained XAI market growth.

Key players in the market

Some of the key players in Explainable AI Market include Microsoft Corporation, Alphabet Inc. (Google LLC), Amazon Web Services Inc. (Amazon.com Inc.), NVIDIA Corporation, IBM Corporation, Intel Corporation, Mphasis Limited, Alteryx, Inc., Palantir Technologies Inc., Salesforce, Inc., Oracle Corporation, Cisco Systems, Inc., Meta Platforms, Inc. (Facebook), Broadcom Inc., Advanced Micro Devices (AMD), SAP SE, Twilio Inc. and ServiceNow, Inc.

Key Developments:

In June 2025, Microsoft enhanced its open-source InterpretML toolkit, adding advanced features for model interpretability and bias detection across AI workflows. This update helps enterprises comply with emerging AI regulations and build user trust by providing transparent AI decision explanations in sectors like healthcare, finance, and government.

In May 2025, Google launched a comprehensive Explainable AI Hub in Google Cloud, offering integrated tools for model transparency, fairness assessment, and causal analysis. The platform supports regulated industries requiring explainability, such as insurance and healthcare, enhancing AI adoption with compliance assistance and improved risk management.

In April 2025, AWS updated its SageMaker Clarify service expanded its capabilities for detecting bias and providing global and local explanations for AI models. These features help developers examine model fairness and interpret complex predictions, strengthening AI governance across retail, finance, and logistics applications.

Components Covered:

  • Solution
  • Services

Deployments Covered:

  • Cloud
  • On-Premise

Applications Covered:

  • Fraud & Anomaly Detection
  • Drug Discovery & Diagnostics
  • Predictive Maintenance
  • Supply Chain Management
  • Identity & Access Management
  • Other Applications

End Users Covered:

  • Healthcare
  • BFSI
  • Aerospace & Defense
  • Retail and Ecommerce
  • Public Sector & Utilities
  • IT & Telecommunication
  • Automotive

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Application Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Explainable AI Market, By Component

  • 5.1 Introduction
  • 5.2 Solution
  • 5.3 Services

6 Global Explainable AI Market, By Deployment

  • 6.1 Introduction
  • 6.2 Cloud
  • 6.3 On-Premise

7 Global Explainable AI Market, By Application

  • 7.1 Introduction
  • 7.2 Fraud & Anomaly Detection
  • 7.3 Drug Discovery & Diagnostics
  • 7.4 Predictive Maintenance
  • 7.5 Supply Chain Management
  • 7.6 Identity & Access Management
  • 7.7 Other Applications

8 Global Explainable AI Market, By End User

  • 8.1 Introduction
  • 8.2 Healthcare
  • 8.3 BFSI
  • 8.4 Aerospace & Defense
  • 8.5 Retail and Ecommerce
  • 8.6 Public Sector & Utilities
  • 8.7 IT & Telecommunication
  • 8.8 Automotive

9 Global Explainable AI Market, By Geography

  • 9.1 Introduction
  • 9.2 North America
    • 9.2.1 US
    • 9.2.2 Canada
    • 9.2.3 Mexico
  • 9.3 Europe
    • 9.3.1 Germany
    • 9.3.2 UK
    • 9.3.3 Italy
    • 9.3.4 France
    • 9.3.5 Spain
    • 9.3.6 Rest of Europe
  • 9.4 Asia Pacific
    • 9.4.1 Japan
    • 9.4.2 China
    • 9.4.3 India
    • 9.4.4 Australia
    • 9.4.5 New Zealand
    • 9.4.6 South Korea
    • 9.4.7 Rest of Asia Pacific
  • 9.5 South America
    • 9.5.1 Argentina
    • 9.5.2 Brazil
    • 9.5.3 Chile
    • 9.5.4 Rest of South America
  • 9.6 Middle East & Africa
    • 9.6.1 Saudi Arabia
    • 9.6.2 UAE
    • 9.6.3 Qatar
    • 9.6.4 South Africa
    • 9.6.5 Rest of Middle East & Africa

10 Key Developments

  • 10.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 10.2 Acquisitions & Mergers
  • 10.3 New Product Launch
  • 10.4 Expansions
  • 10.5 Other Key Strategies

11 Company Profiling

  • 11.1 Microsoft Corporation
  • 11.2 Alphabet Inc. (Google LLC)
  • 11.3 Amazon Web Services Inc. (Amazon.com Inc.)
  • 11.4 NVIDIA Corporation
  • 11.5 IBM Corporation
  • 11.6 Intel Corporation
  • 11.7 Mphasis Limited
  • 11.8 Alteryx, Inc.
  • 11.9 Palantir Technologies Inc.
  • 11.10 Salesforce, Inc.
  • 11.11 Oracle Corporation
  • 11.12 Cisco Systems, Inc.
  • 11.13 Meta Platforms, Inc. (Facebook)
  • 11.14 Broadcom Inc.
  • 11.15 Advanced Micro Devices (AMD)
  • 11.16 SAP SE
  • 11.17 Twilio Inc.
  • 11.18 ServiceNow, Inc.

List of Tables

  • Table 1 Global Explainable AI Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Explainable AI Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global Explainable AI Market Outlook, By Solution (2024-2032) ($MN)
  • Table 4 Global Explainable AI Market Outlook, By Services (2024-2032) ($MN)
  • Table 5 Global Explainable AI Market Outlook, By Deployment (2024-2032) ($MN)
  • Table 6 Global Explainable AI Market Outlook, By Cloud (2024-2032) ($MN)
  • Table 7 Global Explainable AI Market Outlook, By On-Premise (2024-2032) ($MN)
  • Table 8 Global Explainable AI Market Outlook, By Application (2024-2032) ($MN)
  • Table 9 Global Explainable AI Market Outlook, By Fraud & Anomaly Detection (2024-2032) ($MN)
  • Table 10 Global Explainable AI Market Outlook, By Drug Discovery & Diagnostics (2024-2032) ($MN)
  • Table 11 Global Explainable AI Market Outlook, By Predictive Maintenance (2024-2032) ($MN)
  • Table 12 Global Explainable AI Market Outlook, By Supply Chain Management (2024-2032) ($MN)
  • Table 13 Global Explainable AI Market Outlook, By Identity & Access Management (2024-2032) ($MN)
  • Table 14 Global Explainable AI Market Outlook, By Other Applications (2024-2032) ($MN)
  • Table 15 Global Explainable AI Market Outlook, By End User (2024-2032) ($MN)
  • Table 16 Global Explainable AI Market Outlook, By Healthcare (2024-2032) ($MN)
  • Table 17 Global Explainable AI Market Outlook, By BFSI (2024-2032) ($MN)
  • Table 18 Global Explainable AI Market Outlook, By Aerospace & Defense (2024-2032) ($MN)
  • Table 19 Global Explainable AI Market Outlook, By Retail and Ecommerce (2024-2032) ($MN)
  • Table 20 Global Explainable AI Market Outlook, By Public Sector & Utilities (2024-2032) ($MN)
  • Table 21 Global Explainable AI Market Outlook, By IT & Telecommunication (2024-2032) ($MN)
  • Table 22 Global Explainable AI Market Outlook, By Automotive (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.