Global AI Agent Market Strategic Research Report
By Type: Public Cloud SaaS, Private/On-premise Deployment, Edge/Endpoint Deployment
By Application: General Intelligent Agent, Office and Collaboration, Software Development, Customer Service, Sales and Marketing, Data Analysis and BI, IT Operation and Cybersecurity, E-commerce and Retail, Finance, Manufacturing, Healthcare, Education, Law, Others
Regional Forecast: Asia Pacific, Latin America, MEA, Europe, North America
Key Players: Microsoft, Google, ServiceNow, Anthropic, SAP, Amazon Web Services (AWS), IBM, OpenAI, Oracle, Salesforce, Aisera, SoundHound, Fujitsu, Cognition, UiPath, Naver, LangChain, Kakao, PKSHA Technology, Voiceflow, Teneo.ai, Mistral AI, AirOps, Sema4.ai, Gumloop, Stack AI, Relay.app, CrewAI, Alibaba, Baidu, ByteDance, Tencent, iFlytek, Huawei, China Mobile, China Telecom, JD, Beijing Kingsoft Office Software, Knowledge Atlas Technology, MiniMax
Overview
Scope of the Report
The global AI Agent market size is predicted to grow from US$ 10,874 million in 2025 to US$ 434,318 million in 2032; it is expected to grow at a CAGR of 58.0% from 2026 to 2032.
An AI Agent is evolving from a conversational interface into a software-based execution unit capable of planning, coordinating and completing business tasks. Its core functionality includes goal interpretation, task decomposition, knowledge retrieval, tool use, memory management, environment interaction, result verification and human escalation. This scope differentiates AI Agents from foundation models, conventional chatbots and basic generative AI assistants that primarily create content or answer questions. A production-grade AI Agent may connect with three to twenty enterprise systems, execute five to fifty steps in a complex workflow and operate over timeframes ranging from seconds for routine actions to hours for research, software engineering or cross-system processes. Commercial deployment also requires identity management, least-privilege access, audit logs, execution budgets, exception handling and approval controls. The value chain spans foundation models and computing infrastructure, Agent frameworks and runtime platforms, data and knowledge systems, enterprise connectors, vertical applications, implementation and managed services. Revenue is generated through software subscriptions, usage-based fees, runtime consumption, enterprise licences, private deployment and professional services.
The competitive landscape combines large enterprise platforms, model-native companies and specialist Agent vendors. Microsoft generated approximately USD 1.84 billion in AI Agent revenue in 2025, equal to 17.44% of the global market. Google, ServiceNow, Anthropic and Alibaba accounted for 7.03%, 6.48%, 5.91% and 4.61%, respectively, taking the combined share of the five largest vendors to 41.46%. Microsoft benefits from the integration of Agent creation, Microsoft 365, enterprise identity, application connectors and Azure infrastructure. Google combines workspace access, cloud data services and an open developer ecosystem, while ServiceNow embeds AI Agents directly into IT service management, customer operations and employee workflows. Anthropic follows a model-native route centred on software development, computer use and complex reasoning tasks. Alibaba combines cloud infrastructure, DingTalk, commerce and enterprise services. SAP, Amazon Web Services, IBM, Baidu and OpenAI form the next group of leading participants, with differentiated positions in ERP, Agent runtime infrastructure, enterprise orchestration, search and knowledge services, and general-purpose task execution.
Regional demand reflects differences in software ecosystems, industrial structures and enterprise procurement behaviour. North America generated USD 4.28 billion in 2025, accounting for 40.50% of the global market, supported by a dense concentration of foundation model companies, hyperscale cloud platforms, enterprise software vendors and specialist start-ups. Asia-Pacific reached USD 3.64 billion and a 34.46% share, with China, Japan and South Korea advancing through cloud services, super-app ecosystems, manufacturing, telecommunications and local digital platforms. Europe represented 21.15% of global revenue, or USD 2.23 billion, with stronger emphasis on ERP, industrial operations, financial services, public-sector workflows and sovereign deployment. Latin America and the Middle East and Africa remain smaller markets, but financial services, customer operations, government digitalisation, energy and smart-city projects provide a long runway for adoption.
China has become a significant component of the global market. The thirteen leading Chinese vendors generated approximately USD 2.14 billion in AI Agent revenue in 2025, representing 20.29% of the global total. Alibaba, Baidu, ByteDance, Tencent and iFlytek were the leading domestic participants. The Chinese market is differentiated by the integration of AI Agents with cloud platforms, content ecosystems, e-commerce, workplace software, telecommunications networks and industry delivery capabilities. Alibaba and Baidu combine cloud and enterprise development platforms with commerce or search entry points; ByteDance and Tencent use content, communication and developer ecosystems; iFlytek, Huawei and telecom operators concentrate on education, healthcare, government, manufacturing and network operations. This structure gives Chinese vendors strong access to high-frequency use cases and large domestic distribution channels.
Application demand is broadening from general interaction to core operational workflows. Office and collaboration represented 14.27% of 2025 revenue, followed by software development at 13.80%, customer service at 12.97% and general-purpose Agents at 12.29%. Together, these four applications accounted for 53.33% of the market. Sales and marketing represented 9.18%, while data analytics and BI, IT operations and cybersecurity, and e-commerce and retail accounted for 7.33%, 6.77% and 6.75%, respectively. Finance, manufacturing, healthcare, education and legal services currently have smaller revenue shares, but their requirements for specialised data, regulatory controls and complex workflows create higher barriers to entry. E-commerce and retail are expected to record a 63.74% CAGR during 2026–2032, while customer service, healthcare and office collaboration are also expected to grow faster than the overall market.
The latest stage of industry development is centred on long-horizon execution, multi-Agent coordination, open communication standards and controlled runtime environments. Agent platforms increasingly combine web search, file handling, code execution, enterprise connectors, trajectory monitoring, evaluation and security policies within a unified engineering environment. Multi-Agent systems assign separate planning, execution, review and specialist roles to complex workflows, while open protocols allow Agents built on different models and platforms to communicate. Long-term memory, identity, policy controls and auditability are becoming prerequisites for deployment in finance, healthcare, IT and industrial systems. The competitive focus is shifting from the number of Agents created to task completion rates, human intervention levels and cost per successful task. OpenAI has continued to expand long-horizon execution and sandbox capabilities, Google has advanced cross-platform Agent communication and enterprise orchestration, and enterprise software leaders are embedding Agents directly into established workflows.
This report presents a comprehensive overview of the global AI Agent market, covering market size and forecast, segmentation by product type and application, competitive landscape, leading players and regional and country-level outlook.
Segment by Deployment
- Public Cloud SaaS
- Private/On-premise Deployment
- Edge/Endpoint Deployment
Segment by Autonomy Level
- L0-L1 Low Autonomy
- L2 Tool Invocation
- L3 Multi-step Autonomy
- L4 Multi-agent/Continuous Autonomy
Segment by Interaction Pattern
- Conversational
- Embedded Copilot
- Event-driven
- Others
Segment by players, this report covers
- Microsoft
- ServiceNow
- Anthropic
- SAP
- Amazon Web Services (AWS)
- IBM
- OpenAI
- Oracle
- Salesforce
- Aisera
- SoundHound
- Fujitsu
- Cognition
- UiPath
- Naver
- LangChain
- Kakao
- PKSHA Technology
- Voiceflow
- Teneo.ai
- Mistral AI
- AirOps
- Sema4.ai
- Gumloop
- Stack AI
- Relay.app
- CrewAI
- Alibaba
- Baidu
- ByteDance
- Tencent
- iFlytek
- Huawei
- China Mobile
- China Telecom
- JD
- Beijing Kingsoft Office Software
- Knowledge Atlas Technology
- MiniMax
- Marketingforce
Segment by Application
- General Intelligent Agent
- Office and Collaboration
- Software Development
- Customer Service
- Sales and Marketing
- Data Analysis and BI
- IT Operation and Cybersecurity
- E-commerce and Retail
- Finance
- Manufacturing
- Healthcare
- Education
- Law
- Others
Who Can Use This Report?
This report is written for decision-makers who need a clear, data-backed view of the global AI Agent market:
- Manufacturers, suppliers and solution providers benchmarking their position and planning product, capacity and go-to-market strategy
- Distributors, channel partners and end users in General Intelligent Agent, Office and Collaboration, Software Development evaluating demand and sourcing options
- Investors, financial analysts and consultants assessing growth opportunities, competitive dynamics and M&A potential
- Government agencies, industry associations and research institutions tracking industry developments and policy impact
Market snapshot
Global AI Agent Market Strategic Research Report snapshot, 2025–2032
© MarketResearchReports.comDisclaimer: The actual data may vary in the final report which undergoes verification check post order confirmation.Segments covered in this report
Table of contents
01Executive Summary
02Industry Overview & Forecast
- 2.1.1 Market Definition and Scope
- 2.1.2 Market Size and Growth Forecast
- 2.1.3 Volume Analysis
- 2.1.4 Segment Outlook by Type
- 2.1.5 Segment Outlook by Application
- 2.1.6 Regional Outlook
- 2.1.7 Structural Developments Shaping the Forecast
- 2.1.8 Forecast Risks and Sensitivities
03Market Segmentation by Type
- 3.1 Market Segmentation by Type
- 3.1.1 Market by Type Overview
- 3.1.2 Public Cloud SaaS
- 3.1.3 Private/On-premise Deployment
- 3.1.4 Edge/Endpoint Deployment
- 3.1.5 Volume Analysis
04Market Segmentation by Application
- 4.1 Market Segmentation by Application
- 4.1.1 Market by Application Overview
- 4.1.2 General Intelligent Agent
- 4.1.3 Office and Collaboration
- 4.1.4 Software Development
- 4.1.5 Customer Service
- 4.1.6 Sales and Marketing
- 4.1.7 Data Analysis and BI
- 4.1.8 IT Operation and Cybersecurity
- 4.1.9 E-commerce and Retail
- 4.1.10 Finance
- 4.1.11 Manufacturing
- 4.1.12 Healthcare
- 4.1.13 Education
- 4.1.14 Law
- 4.1.15 Others
- 4.1.16 Volume Analysis
05Regional Market Forecast
- Asia Pacific
- North America
- Europe
- Middle East & Africa
- Latin America
06Country-Level Market Forecast
- 6.1 Asia Pacific
- 6.1.1 China
- 6.1.2 Japan
- 6.1.3 Korea
- 6.1.4 Southeast Asia
- 6.1.5 India
- 6.1.6 Australia
- 6.1.7 Rest of Asia Pacific
- 6.2 North America
- 6.2.1 United States
- 6.2.2 Canada
- 6.2.3 Mexico
- 6.2.4 Rest of North America
- 6.3 Europe
- 6.3.1 Germany
- 6.3.2 France
- 6.3.3 UK
- 6.3.4 Italy
- 6.3.5 Russia
- 6.3.6 Rest of Europe
- 6.4 Middle East & Africa
- 6.4.1 Egypt
- 6.4.2 South Africa
- 6.4.3 Israel
- 6.4.4 Turkey
- 6.4.5 GCC Countries
- 6.4.6 Rest of Middle East & Africa
- 6.5 Latin America
- 6.5.1 Brazil
- 6.5.2 Rest of Latin America
07Growth Drivers & Inhibitors
- 7.1 Growth Drivers & Inhibitors
- 7.1.1 Section Overview
- 7.1.2 Growth Drivers
- 7.1.3 Growth Inhibitors
- 7.1.4 Driver and Inhibitor Impact Assessment
- 7.1.5 Analyst Perspective
08Key Company Profiles
- 8.1 Microsoft
- 8.1.1 Company Overview
- 8.1.2 Key Products & Segments
- 8.1.3 Financial Performance (2023–2025)
- 8.1.4 Business Strategy
- 8.1.5 SWOT Analysis
- 8.1.6 Strategic Implications (2026–2032)
- 8.2 Google
- 8.2.1 Company Overview
- 8.2.2 Key Products & Segments
- 8.2.3 Financial Performance (2023–2025)
- 8.2.4 Business Strategy
- 8.2.5 SWOT Analysis
- 8.2.6 Strategic Implications (2026–2032)
- 8.3 ServiceNow
- 8.3.1 Company Overview
- 8.3.2 Key Products & Segments
- 8.3.3 Financial Performance (2023–2025)
- 8.3.4 Business Strategy
- 8.3.5 SWOT Analysis
- 8.3.6 Strategic Implications (2026–2032)
- 8.4 Anthropic
- 8.4.1 Company Overview
- 8.4.2 Key Products & Segments
- 8.4.3 Financial Performance (2023–2025)
- 8.4.4 Business Strategy
- 8.4.5 SWOT Analysis
- 8.4.6 Strategic Implications (2026–2032)
- 8.5 SAP
- 8.5.1 Company Overview
- 8.5.2 Key Products & Segments
- 8.5.3 Financial Performance (2023–2025)
- 8.5.4 Business Strategy
- 8.5.5 SWOT Analysis
- 8.5.6 Strategic Implications (2026–2032)
- 8.6 Amazon Web Services (AWS)
- 8.6.1 Company Overview
- 8.6.2 Key Products & Segments
- 8.6.3 Financial Performance (2023–2025)
- 8.6.4 Business Strategy
- 8.6.5 SWOT Analysis
- 8.6.6 Strategic Implications (2026–2032)
- 8.7 IBM
- 8.7.1 Company Overview
- 8.7.2 Key Products & Segments
- 8.7.3 Financial Performance (2023–2025)
- 8.7.4 Business Strategy
- 8.7.5 SWOT Analysis
- 8.7.6 Strategic Implications (2026–2032)
- 8.8 OpenAI
- 8.8.1 Company Overview
- 8.8.2 Key Products & Segments
- 8.8.3 Financial Performance (2023–2025)
- 8.8.4 Business Strategy
- 8.8.5 SWOT Analysis
- 8.8.6 Strategic Implications (2026–2032)
- 8.9 Oracle
- 8.9.1 Company Overview
- 8.9.2 Key Products & Segments
- 8.9.3 Financial Performance (2023–2025)
- 8.9.4 Business Strategy
- 8.9.5 SWOT Analysis
- 8.9.6 Strategic Implications (2026–2032)
- 8.10 Salesforce
- 8.10.1 Company Overview
- 8.10.2 Key Products & Segments
- 8.10.3 Financial Performance (2023–2025)
- 8.10.4 Business Strategy
- 8.10.5 SWOT Analysis
- 8.10.6 Strategic Implications (2026–2032)
- 8.11 Aisera
- 8.11.1 Company Overview
- 8.11.2 Key Products & Segments
- 8.11.3 Financial Performance (2023–2025)
- 8.11.4 Business Strategy
- 8.11.5 SWOT Analysis
- 8.11.6 Strategic Implications (2026–2032)
- 8.12 SoundHound
- 8.12.1 Company Overview
- 8.12.2 Key Products & Segments
- 8.12.3 Financial Performance (2023–2025)
- 8.12.4 Business Strategy
- 8.12.5 SWOT Analysis
- 8.12.6 Strategic Implications (2026–2032)
- 8.13 Fujitsu
- 8.13.1 Company Overview
- 8.13.2 Key Products & Segments
- 8.13.3 Financial Performance (2023–2025)
- 8.13.4 Business Strategy
- 8.13.5 SWOT Analysis
- 8.13.6 Strategic Implications (2026–2032)
- 8.14 Cognition
- 8.14.1 Company Overview
- 8.14.2 Key Products & Segments
- 8.14.3 Financial Performance (2023–2025)
- 8.14.4 Business Strategy
- 8.14.5 SWOT Analysis
- 8.14.6 Strategic Implications (2026–2032)
- 8.15 UiPath
- 8.15.1 Company Overview
- 8.15.2 Key Products & Segments
- 8.15.3 Financial Performance (2023–2025)
- 8.15.4 Business Strategy
- 8.15.5 SWOT Analysis
- 8.15.6 Strategic Implications (2026–2032)
- 8.16 Naver
- 8.16.1 Company Overview
- 8.16.2 Key Products & Segments
- 8.16.3 Financial Performance (2023–2025)
- 8.16.4 Business Strategy
- 8.16.5 SWOT Analysis
- 8.16.6 Strategic Implications (2026–2032)
- 8.17 LangChain
- 8.17.1 Company Overview
- 8.17.2 Key Products & Segments
- 8.17.3 Financial Performance (2023–2025)
- 8.17.4 Business Strategy
- 8.17.5 SWOT Analysis
- 8.17.6 Strategic Implications (2026–2032)
- 8.18 Kakao
- 8.18.1 Company Overview
- 8.18.2 Key Products & Segments
- 8.18.3 Financial Performance (2023–2025)
- 8.18.4 Business Strategy
- 8.18.5 SWOT Analysis
- 8.18.6 Strategic Implications (2026–2032)
- 8.19 PKSHA Technology
- 8.19.1 Company Overview
- 8.19.2 Key Products & Segments
- 8.19.3 Financial Performance (2023–2025)
- 8.19.4 Business Strategy
- 8.19.5 SWOT Analysis
- 8.19.6 Strategic Implications (2026–2032)
- 8.20 Voiceflow
- 8.20.1 Company Overview
- 8.20.2 Key Products & Segments
- 8.20.3 Financial Performance (2023–2025)
- 8.20.4 Business Strategy
- 8.20.5 SWOT Analysis
- 8.20.6 Strategic Implications (2026–2032)
- 8.21 Teneo.ai
- 8.21.1 Company Overview
- 8.21.2 Key Products & Segments
- 8.21.3 Financial Performance (2023–2025)
- 8.21.4 Business Strategy
- 8.21.5 SWOT Analysis
- 8.21.6 Strategic Implications (2026–2032)
- 8.22 Mistral AI
- 8.22.1 Company Overview
- 8.22.2 Key Products & Segments
- 8.22.3 Financial Performance (2023–2025)
- 8.22.4 Business Strategy
- 8.22.5 SWOT Analysis
- 8.22.6 Strategic Implications (2026–2032)
- 8.23 AirOps
- 8.23.1 Company Overview
- 8.23.2 Key Products & Segments
- 8.23.3 Financial Performance (2023–2025)
- 8.23.4 Business Strategy
- 8.23.5 SWOT Analysis
- 8.23.6 Strategic Implications (2026–2032)
- 8.24 Sema4.ai
- 8.24.1 Company Overview
- 8.24.2 Key Products & Segments
- 8.24.3 Financial Performance (2023–2025)
- 8.24.4 Business Strategy
- 8.24.5 SWOT Analysis
- 8.24.6 Strategic Implications (2026–2032)
- 8.25 Gumloop
- 8.25.1 Company Overview
- 8.25.2 Key Products & Segments
- 8.25.3 Financial Performance (2023–2025)
- 8.25.4 Business Strategy
- 8.25.5 SWOT Analysis
- 8.25.6 Strategic Implications (2026–2032)
- 8.26 Stack AI
- 8.26.1 Company Overview
- 8.26.2 Key Products & Segments
- 8.26.3 Financial Performance (2023–2025)
- 8.26.4 Business Strategy
- 8.26.5 SWOT Analysis
- 8.26.6 Strategic Implications (2026–2032)
- 8.27 Relay.app
- 8.27.1 Company Overview
- 8.27.2 Key Products & Segments
- 8.27.3 Financial Performance (2023–2025)
- 8.27.4 Business Strategy
- 8.27.5 SWOT Analysis
- 8.27.6 Strategic Implications (2026–2032)
- 8.28 CrewAI
- 8.28.1 Company Overview
- 8.28.2 Key Products & Segments
- 8.28.3 Financial Performance (2023–2025)
- 8.28.4 Business Strategy
- 8.28.5 SWOT Analysis
- 8.28.6 Strategic Implications (2026–2032)
- 8.29 Alibaba
- 8.29.1 Company Overview
- 8.29.2 Key Products & Segments
- 8.29.3 Financial Performance (2023–2025)
- 8.29.4 Business Strategy
- 8.29.5 SWOT Analysis
- 8.29.6 Strategic Implications (2026–2032)
- 8.30 Baidu
- 8.30.1 Company Overview
- 8.30.2 Key Products & Segments
- 8.30.3 Financial Performance (2023–2025)
- 8.30.4 Business Strategy
- 8.30.5 SWOT Analysis
- 8.30.6 Strategic Implications (2026–2032)
- 8.31 ByteDance
- 8.31.1 Company Overview
- 8.31.2 Key Products & Segments
- 8.31.3 Financial Performance (2023–2025)
- 8.31.4 Business Strategy
- 8.31.5 SWOT Analysis
- 8.31.6 Strategic Implications (2026–2032)
- 8.32 Tencent
- 8.32.1 Company Overview
- 8.32.2 Key Products & Segments
- 8.32.3 Financial Performance (2023–2025)
- 8.32.4 Business Strategy
- 8.32.5 SWOT Analysis
- 8.32.6 Strategic Implications (2026–2032)
- 8.33 iFlytek
- 8.33.1 Company Overview
- 8.33.2 Key Products & Segments
- 8.33.3 Financial Performance (2023–2025)
- 8.33.4 Business Strategy
- 8.33.5 SWOT Analysis
- 8.33.6 Strategic Implications (2026–2032)
- 8.34 Huawei
- 8.34.1 Company Overview
- 8.34.2 Key Products & Segments
- 8.34.3 Financial Performance (2023–2025)
- 8.34.4 Business Strategy
- 8.34.5 SWOT Analysis
- 8.34.6 Strategic Implications (2026–2032)
- 8.35 China Mobile
- 8.35.1 Company Overview
- 8.35.2 Key Products & Segments
- 8.35.3 Financial Performance (2023–2025)
- 8.35.4 Business Strategy
- 8.35.5 SWOT Analysis
- 8.35.6 Strategic Implications (2026–2032)
- 8.36 China Telecom
- 8.36.1 Company Overview
- 8.36.2 Key Products & Segments
- 8.36.3 Financial Performance (2023–2025)
- 8.36.4 Business Strategy
- 8.36.5 SWOT Analysis
- 8.36.6 Strategic Implications (2026–2032)
- 8.37 JD
- 8.37.1 Company Overview
- 8.37.2 Key Products & Segments
- 8.37.3 Financial Performance (2023–2025)
- 8.37.4 Business Strategy
- 8.37.5 SWOT Analysis
- 8.37.6 Strategic Implications (2026–2032)
- 8.38 Beijing Kingsoft Office Software
- 8.38.1 Company Overview
- 8.38.2 Key Products & Segments
- 8.38.3 Financial Performance (2023–2025)
- 8.38.4 Business Strategy
- 8.38.5 SWOT Analysis
- 8.38.6 Strategic Implications (2026–2032)
- 8.39 Knowledge Atlas Technology
- 8.39.1 Company Overview
- 8.39.2 Key Products & Segments
- 8.39.3 Financial Performance (2023–2025)
- 8.39.4 Business Strategy
- 8.39.5 SWOT Analysis
- 8.39.6 Strategic Implications (2026–2032)
- 8.40 MiniMax
- 8.40.1 Company Overview
- 8.40.2 Key Products & Segments
- 8.40.3 Financial Performance (2023–2025)
- 8.40.4 Business Strategy
- 8.40.5 SWOT Analysis
- 8.40.6 Strategic Implications (2026–2032)
09Competitive Landscape
- 9.1 Competitive Landscape Overview
- 9.2 Competitive Intensity Assessment
- 9.3 Key Player Strategies & Positioning
- 9.4 Competitive Dynamics & Strategic Outlook
- 9.4.1 Emerging Competitive Threats
- 9.4.2 Consolidation vs. Fragmentation Outlook
- 9.4.3 Competitive Response Matrix
- 9.4.4 Strategic Recommendations, 2026–2032
10Porter's Five Forces Analysis
- 10.1 Threat of New Entrants
- 10.2 Bargaining Power of Buyers
- 10.3 Bargaining Power of Suppliers
- 10.4 Threat of Substitutes
- 10.5 Competitive Rivalry
11PESTLE Analysis
- 11.1 Political
- 11.2 Economic
- 11.3 Social and Demographic
- 11.4 Technological
- 11.5 Legal and Regulatory
- 11.6 Environmental
- 11.7 Strategic Implications of the PESTLE Assessment
12SWOT Analysis
13Future Trends & Outlook
- 13.1 Future Trends & Outlook
- 13.1.1 Trend Summary and Commercial Maturity Assessment
- 13.1.2 Technology and Innovation Trends
- 13.1.3 Long-Term Market Outlook
- 13.1.4 Investment & M&A Activity Outlook
- 13.1.5 Overall Outlook Assessment
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Company profiles built from public financial disclosures, product launches, M&A activity, job postings (as capability proxies), and supply chain mapping. Market share estimates triangulated across revenue, capacity, and shipment data.
CAGR projections use time-series regression on 5-10 years of historical data, adjusted for identified demand drivers (technology adoption curves, regulatory catalysts, demographic shifts) and demand inhibitors (cost barriers, substitution risk). Scenario modeling covers base, optimistic, and conservative cases.
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