기업 AI 지식 운영 : 시장 점유율 분석, 업계 동향과 통계, 성장 예측(2026-2031년)

According to Mordor Intelligence, the enterprise AI knowledge operations market size is projected to expand from USD 13.81 billion in 2025 and USD 16.14 billion in 2026 to USD 34.44 billion by 2031, registering a CAGR of 16.37% between 2026 and 2031.

Global Enterprise AI Knowledge Operations Market Trends and Insights

Enterprise Knowledge Fragmentation Across SaaS Stacks

Every added SaaS application can create another knowledge silo within an organization. Employees often need information from project trackers, document repositories, customer systems, internal messaging tools, and shared workspaces in the same task. A request that crosses these systems can otherwise require repeated searches, manual comparison, or help from colleagues who know where information is stored. This fragmentation increases the value of the enterprise AI knowledge operations market because it requires a shared retrieval layer rather than separate search tools. Glean stated that its platform supported more than 275 app connectors, reflecting the importance vendors place on broad enterprise coverage. A centrally indexed system can improve access to information as organizations add tools, users, and content over time. Separate agents for each application can recreate the fragmentation they were intended to solve.

Permission-Aware Semantic Search and Grounded Answers

Semantic retrieval interprets the meaning of a request instead of relying only on keyword matches. Enterprises also require the retrieval process to enforce access rights before information reaches a user or agent. This requirement is raising the standard for the enterprise AI knowledge operations market, particularly in regulated settings where the consequences of disclosure can be material. Amazon Bedrock Managed Knowledge Base became generally available in June 2026 with document-level access control and real-time access-control-list checks. Grounding responses in authorized, version-controlled material helps organizations assess the basis for an answer and identify the underlying source. It also makes permission enforcement central to platform design rather than a separate control applied after retrieval.

Hallucination Risk and Limited Trust in AI-Generated Answers

Hallucinations can produce plausible answers that are not supported by current or verified information. This risk makes enterprises cautious when knowledge tools are used in financial, legal, clinical, or operational processes where unsupported advice can affect a decision. The enterprise AI knowledge operations market must therefore address whether users can verify each answer, identify its source, and recognize uncertainty. Citation-based retrieval and confidence thresholds can help systems avoid presenting uncertain content as an established fact. Knowledge systems are increasingly assessed on traceability and auditability, not only on the number of results returned or the fluency of the response. These requirements can slow adoption where a platform cannot show how its answer was produced and whether the user was authorized to receive the source.

Other drivers and restraints analyzed in the detailed report include:

1. Copilot-Led Knowledge Workflows
2. Retrieval of Tribal Knowledge for Distributed Teams
3. Legacy Repository and Identity-System Integration Complexity

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

Segment Analysis

Software platforms held 72.83% of enterprise AI knowledge operations market revenue in 2025. Enterprises favour centralized, configurable retrieval systems that can serve several use cases through one governance layer, rather than requiring separate administration for every application. Each connected application can improve the usefulness of a shared index for more users and workflows because the system can bring relevant organizational context together. Atlassian reported that Rovo indexed more than 50 connected SaaS applications. The enterprise AI knowledge operations industry relies on this shared-index model because separate tools can duplicate administration, create inconsistent results, and leave users uncertain about which system contains the latest information.

Services are projected to expand at a 16.78% CAGR through 2031 within the enterprise AI knowledge operations market. Implementation work remains important because companies must connect legacy repositories, synchronize permissions across systems, and define practical ownership for ongoing content maintenance. Managed operations also support content refresh, index administration, governance review, and user support after the original deployment is complete. These needs make services a recurring part of many vendor relationships instead of a one-time technical setup. Vendors with partner delivery capacity can support broader deployments than those relying only on their internal consulting teams, particularly when customers operate across several business units or regions.

Cloud represented 56.28% of revenue in 2025 and is projected to expand at a 17.25% CAGR through 2031. Cloud platforms avoid customer-managed provisioning and can provide continuing updates to retrieval models, source connectors, and security features without major internal upgrade projects. Amazon Bedrock Managed Knowledge Base reached general availability in June 2026 with connectors for Amazon S3, SharePoint, Confluence, Google Drive, OneDrive, and web content. These capabilities can lower the initial deployment burden for the enterprise AI knowledge operations market, especially for organizations that want to connect common information sources quickly. They also support agentic retrieval and document-level access control within a managed service.

On-premises and hybrid options remain strategically relevant despite the cloud's larger share. Data sovereignty rules can require retrieval and storage to remain within defined infrastructure boundaries, even when organizations want access to cloud-based model capabilities. This condition creates a parallel opportunity for vendors that can support cloud and local deployment models without creating separate governance processes. Financial services, defense-adjacent organizations, and markets with local data mandates may place greater emphasis on hybrid deployment to keep sensitive data under defined controls. The enterprise AI knowledge operations industry can therefore favour providers that address governance requirements without limiting deployment choice or slowing access to updated tools.

Complete Report Scope:

• By Offering
  • Software Platforms
  • Services
• By Deployment Mode
  • Cloud
  • On-Premises
  • Hybrid
• By Application
  • Enterprise Search and Knowledge Discovery
  • Employee Copilots and Productivity Assistance
  • Customer Support and Self-Service
  • Document Management and Content Retrieval
  • Training, Learning, and Employee Onboarding
  • Legal, Risk, and Compliance Management
  • Market Intelligence and Competitive Analysis
  • Research and Development Knowledge Operations
  • Field-Service and Technical Operations
• By Industry Vertical
  • Information Technology and Telecommunications
  • Banking, Financial Services, and Insurance
  • Healthcare and Life Sciences
  • Manufacturing
  • Retail and E-Commerce
  • Government and Public Sector
  • Others Industry Vertical
• By Geography
  • North America
    • United States
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Europe
    • Germany
    • United Kingdom
    • France
    • Italy
    • Spain
    • Russia
    • Rest of Europe
  • Asia-Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Rest of Asia-Pacific
  • Middle East
    • Saudi Arabia
    • United Arab Emirates
    • Turkey
    • Rest of Middle East
  • Africa
    • South Africa
    • Egypt
    • Rest of Africa

Geography Analysis

North America accounted for 44.12% of the enterprise AI knowledge operations market in 2025. The region benefits from concentrated enterprise software spending and the presence of major platform vendors, while knowledge platforms are closely integrated with Microsoft, Google, and Salesforce environments across many organizations. Microsoft stated in March 2026 that 90% of the Fortune 500 used Microsoft 365 Copilot. The United States drives most regional demand, while Canada supports bilingual retrieval needs in English and French for government and enterprise settings.

Asia-Pacific is projected to expand at a 17.36% CAGR through 2031. India has strong enterprise AI adoption, while China is developing locally adapted retrieval platforms designed for its data governance environment and domestic technology ecosystem. Japan is advancing more carefully, with internal knowledge management serving as an early use case for enterprise AI where organizations want controlled adoption. The enterprise AI knowledge operations market has room to develop differently across these markets because governance practices, language requirements, and deployment readiness vary. South Korea and Australia are at intermediate stages, with governance receiving attention before large-scale rollout across sensitive organizational information.

Europe ranked third by share in 2025, led by Germany and the United Kingdom. Manufacturing, insurance, and financial-services organizations have deployed AI-assisted knowledge systems, and German research programs have provided models for small and medium enterprises. The EU AI Act and GDPR encourage demand for local and hybrid architectures that can support data residency requirements while maintaining useful AI-assisted retrieval. Middle Eastern adoption is linked to public-sector, energy, and financial-services digital programs in Saudi Arabia and the UAE. South America and Africa remain earlier-stage regions where enterprise digitalization is building the required data foundation, creating a longer-term opportunity as internal information becomes more structured and accessible.

1. Microsoft Corporation
2. ServiceNow, Inc.
3. Salesforce, Inc.
4. Google LLC
5. Atlassian Corporation Plc
6. Glean Technologies, Inc.
7. International Business Machines Corporation
8. Amazon Web Services, Inc.
9. Oracle Corporation
10. SAP SE
11. Elastic N.V.
12. Coveo Solutions Inc.
13. Open Text Corporation
14. Lucidworks, Inc.
15. Sinequa SAS
16. Algolia SAS
17. Guru Technologies, Inc.
18. Notion Labs, Inc.
19. Moveworks, Inc.
20. Kore.ai, Inc.
21. Vectara, Inc.
22. KMS Lighthouse
23. Knowmax AI Private Limited
24. Shelf, Inc.
25. Livepro, 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 Enterprise Knowledge Fragmentation Across SaaS Stacks
  • 4.2.2 Permission-Aware Semantic Search and Grounded Answers
  • 4.2.3 Copilot-Led Knowledge Workflows
  • 4.2.4 Retrieval of Tribal Knowledge for Distributed Teams
  • 4.2.5 Multilingual Knowledge Retrieval for Cross-Border Operations
  • 4.2.6 Agent-Ready Knowledge Graphs for Permissioned Autonomous Workflows
• 4.3 Market Restraints
  • 4.3.1 Hallucination Risk and Limited Trust in AI-Generated Answers
  • 4.3.2 Legacy Repository and Identity-System Integration Complexity
  • 4.3.3 Data Residency and Cross-Border Knowledge Replication Constraints
  • 4.3.4 Stale Permissions and Unowned Enterprise Content
• 4.4 Industry Value-Chain Analysis
• 4.5 Regulatory Landscape
• 4.6 Technological Outlook
• 4.7 Porter's Five Forces Analysis
  • 4.7.1 Bargaining Power of Suppliers
  • 4.7.2 Bargaining Power of Buyers
  • 4.7.3 Threat of New Entrants
  • 4.7.4 Threat of Substitutes
  • 4.7.5 Intensity of Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By Offering
  • 5.1.1 Software Platforms
  • 5.1.2 Services
• 5.2 By Deployment Mode
  • 5.2.1 Cloud
  • 5.2.2 On-Premises
  • 5.2.3 Hybrid
• 5.3 By Application
  • 5.3.1 Enterprise Search and Knowledge Discovery
  • 5.3.2 Employee Copilots and Productivity Assistance
  • 5.3.3 Customer Support and Self-Service
  • 5.3.4 Document Management and Content Retrieval
  • 5.3.5 Training, Learning, and Employee Onboarding
  • 5.3.6 Legal, Risk, and Compliance Management
  • 5.3.7 Market Intelligence and Competitive Analysis
  • 5.3.8 Research and Development Knowledge Operations
  • 5.3.9 Field-Service and Technical Operations
• 5.4 By Industry Vertical
  • 5.4.1 Information Technology and Telecommunications
  • 5.4.2 Banking, Financial Services, and Insurance
  • 5.4.3 Healthcare and Life Sciences
  • 5.4.4 Manufacturing
  • 5.4.5 Retail and E-Commerce
  • 5.4.6 Government and Public Sector
  • 5.4.7 Others Industry Vertical
• 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 Italy
    • 5.5.3.5 Spain
    • 5.5.3.6 Russia
    • 5.5.3.7 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 Australia
    • 5.5.4.6 Rest of Asia-Pacific
  • 5.5.5 Middle East
    • 5.5.5.1 Saudi Arabia
    • 5.5.5.2 United Arab Emirates
    • 5.5.5.3 Turkey
    • 5.5.5.4 Rest of Middle East
  • 5.5.6 Africa
    • 5.5.6.1 South Africa
    • 5.5.6.2 Egypt
    • 5.5.6.3 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 Microsoft Corporation
  • 6.4.2 ServiceNow, Inc.
  • 6.4.3 Salesforce, Inc.
  • 6.4.4 Google LLC
  • 6.4.5 Atlassian Corporation Plc
  • 6.4.6 Glean Technologies, Inc.
  • 6.4.7 International Business Machines Corporation
  • 6.4.8 Amazon Web Services, Inc.
  • 6.4.9 Oracle Corporation
  • 6.4.10 SAP SE
  • 6.4.11 Elastic N.V.
  • 6.4.12 Coveo Solutions Inc.
  • 6.4.13 Open Text Corporation
  • 6.4.14 Lucidworks, Inc.
  • 6.4.15 Sinequa SAS
  • 6.4.16 Algolia SAS
  • 6.4.17 Guru Technologies, Inc.
  • 6.4.18 Notion Labs, Inc.
  • 6.4.19 Moveworks, Inc.
  • 6.4.20 Kore.ai, Inc.
  • 6.4.21 Vectara, Inc.
  • 6.4.22 KMS Lighthouse
  • 6.4.23 Knowmax AI Private Limited
  • 6.4.24 Shelf, Inc.
  • 6.4.25 Livepro, Inc.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-Space and Unmet-Need Assessment