Causal AI Market

Report Code TC 8644
Published in Dec, 2024, By MarketsandMarkets™
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Causal AI Market by Offering (Causal AI Platforms, Causal Discovery, Causal Inference, Causal Modelling, Root Cause Analysis), Application (Financial Management, Sales & Customer Management, Operations & Supply Chain Management) - Global Forecast to 2030

 

Overview

The causal AI market is estimated to account for USD 56.2 million in 2024, expanding at a CAGR of 41.8% during the forecast period to accrue USD 456.8 million by 2030. The key driver is the increasing focus on explainability & trust in the AI systems. Unlike traditional machine learning models, which are “black boxes,” causal AI helps to uncover cause-and-effect relationships like 'why' something happens and how this outcome can be manipulated. This is important in heavily regulated industries like healthcare, where causal inference can help improve treatment strategies, and in finance, it can augment decisions around fraud detection. AI regulations such as GDPR also foster its deployment because causal models help attain transparency and accountability. Another factor that drives market growth is the rise of personalized marketing, where causal insights help businesses develop customer engagement strategies based on individual user preferences. Causal AI in predictive tools is gaining popularity among businesses for managing complex systems like supply chains, providing forecasts of outcomes and proposing practical improvements.

Causal AI refers to AI models that can recognize cause-and-effect connections within data in order to predict and influence results. Unlike traditional AI, which can only recognize and analyze correlations in data, causal AI offers more in-depth explainability and reduced bias by using causal inference to pinpoint root causes in all datasets, thus better modeling hypothetical situations accurately. Causal AI employs methods such as causal graphs and simulation to assess data and identify the root causes of events or behaviors. It can utilize this data to forecast outcomes and recommend steps.

Causal AI Market

Attractive Opportunities in the Causal AI Market

ASIA PACIFIC

The demand for Causal AI in Asia Pacific is driven by growth in healthcare, finance, and smart city projects. Areas like public policy making and precision medicine require robust causal models to predict outcomes of interventions. This drives the adoption of Causal AI for high-stakes applications in the region.

Vendors offering real-time causal AI tools and scalable solutions will lead the market. Those addressing data quality challenges and enabling seamless integration with workflows will gain a competitive edge.

The integration of causal AI with LLMs is expanding its applications. This fusion powers advanced use cases like policy recommendations, adaptive learning systems, and risk simulations in dynamic environments.

Causal AI is reshaping decision-making by enabling organizations to uncover true cause-and-effect relationships. It is critical in industries like healthcare, finance, and supply chain, where precision and risk mitigation are key.

The growing need for explainable AI is driving demand for causal AI in regulated sectors. Industries like healthcare and finance require transparent, actionable insights to meet ethical and compliance standards.

Impact of AI on Causal AI Market

ENHANCED DATA AVAILABILITY FOR CAUSAL ANALYSIS

Generative AI can produce synthetic datasets, enabling causal AI models to operate in environments where data collection is limited or constrained by privacy concerns.

STRESS TESTING OF CAUSAL MODELS

Generative AI allows the simulation of diverse hypothetical environments, enabling causal AI models to be tested under various conditions.

SUPPORT FOR COMPLEX MULTIVARIABLE ANALYSIS

Generative AI can simulate interactions between multiple factors, helping causal AI understand the interplay between multiple causes and their effects

ACCELERATED MODEL DEVELOPMENT

By automating the generation of training data, generative AI reduces the time and effort needed to prepare datasets for causal AI applications

BIAS REDUCTION FOR FAIRER OUTCOMES

Generative AI supports causal AI by generating data that balances out demographic disparities, ensuring causal inferences remain fair.

IDENTIFYING HIDDEN RELATIONSHIPS

Generative AI can simulate and model subtle or hidden interactions between variables, giving causal AI deeper insights into complex systems

Causal AI Market Impact

Global Causal AI Market Dynamics

Driver: Increasing demand for personalized solutions in marketing and customer engagement

The increasing demand for customized marketing and customer interaction is a significant factor in the growth of causal AI. Traditional AI models often rely on correlations, leading to standard methods that may not adequately address individual customer needs. These generic approaches can be tackled by causal AI through enhanced causal relationships, which enable the creation of customized marketing strategies and individualized customer interactions, resulting in increased involvement and contentment. Customization has proven to be quite significant in business performance. As per estimates, companies who are highly skilled at customization generate 40% more revenue from these efforts compared to companies who are just average. Additionally, 71% of consumers anticipate personalized interactions from companies, and 76% feel aggravated when this expectation is not met. Through the utilization of causal AI, companies can better meet these demands, enhancing customer connections and promoting expansion.

Restraint: Over-reliance of causal AI models on high-quality, unbiased data causes issues with fragmented datasets

One major limitation in the causal AI industry is the strong reliance on high-quality, unbiased data for successful deployment. Causal AI models require precise and thorough datasets to establish valid cause-and-effect relationships, unlike conventional machine learning models that can still make functional predictions with noisy or incomplete datasets. Flawed data, whether it is inconsistent, incomplete, or biased, can result in unreliable decision-making due to incorrect insights. In healthcare, incomplete patient records can lead to incorrect conclusions about the effectiveness of treatments, which may harm patient outcomes. This reliance presents a difficulty for companies in sectors with scattered or uneven data gathering, like manufacturing or public policy. Moreover, preparing and organizing this data for causal analysis typically demands substantial resources, specialized knowledge, and time, which can discourage usage. Therefore, although the promise of causal AI is great, its dependence on grounded data continues to be a major hindrance, restricting its usefulness and availability in specific industries.

 

Opportunity: Integration of causal AI models in supply chain systems for critical decision-making

An important opportunity in the causal AI industry is its ability to completely transform dynamic systems, specifically in sectors such as supply chain management. Businesses are now more interested in causal AI, as it provides the capability to understand and analyze cause-and-effect relationships in intricate operations, moving beyond simple correlations. As global supply chains become increasingly complex and vulnerable to interruptions, such as those stemming from political conflicts or climate issues, a rise in the need for explainable AI solutions is expected. Having causal AI inference allows companies to predict possible disruptions and also model the consequences of different choices instantly, enabling proactive tactics instead of reactive responses. Moreover, with an increasing number of companies implementing digital transformation plans, incorporating causal AI into supply chain management systems can help improve operational effectiveness, cut expenses, and strengthen resilience. These use cases highlight the significant growth opportunities for causal AI, especially in sectors where accuracy and flexibility are essential for achieving goals.

Challenge: Steep learning curve and specialized expertise required for implementing causal AI

A major challenge in the causal AI industry is the considerable expertise needed to successfully deploy and maintain such systems. Contrary to traditional AI's emphasis on recognizing patterns in data, causal AI is dedicated to understanding cause-and-effect connections, requiring expertise in causal inference and statistical modeling. This intricacy results in a shortage of skills, making it challenging for organizations to locate or enhance the required talent to oversee these advanced tools. Moreover, the incorporation of causal AI into current systems may demand considerable resources, including time, funding, and expertise, to ensure alignment with the organization's objectives. For smaller businesses or those in industries less experienced with AI adoption, this challenge can act as a deterrent, slowing overall market penetration. While intuitive platforms and thorough training programs are reducing the obstacle, the challenging learning curve continues to be a major barrier to broad adoption in different industries.

Global Causal AI Market Ecosystem Analysis

The causal AI ecosystem comprises key players offering platforms, tools, APIs, and services to enable organizations to leverage cause-and-effect insights. Major platform providers like causaLens, Causaly, and Aitia focus on comprehensive solutions. Tool providers, including Google and Microsoft, specialize in data-driven causal inference. API developers like DataRobot deliver integration-ready toolkits, while service providers such as IBM and Veldt offer customized implementation and advisory services. This ecosystem facilitates diverse applications across industries.

Top Companies in Causal AI Market

Source: Secondary Research, Interviews with Experts, and MarketsandMarkets Analysis

 

By offering, causal AI platforms slated to account for highest market share in 2024

Causal AI platforms provide a complete set of tools, including data ingestion, processing, advanced analytics, and visualization, enabling users to easily recognize and respond to cause-and-effect connections in their data. Platforms, in contrast to standalone tools or APIs, are created to be both user-friendly and scalable, serving businesses in different sectors, regardless of their level of technical knowledge. This wide range of applications makes them very appealing to businesses seeking all-encompassing solutions that can be tailored to their specific needs. As sectors such as healthcare, finance, and supply chain management depend more on data-driven approaches, the need for comprehensive, user-friendly platforms is growing. The feature of causal AI platforms that helps integrate with workflows and provides measurable value makes them a crucial facilitator for businesses seeking a competitive advantage with causal AI. Their dominance in the causal AI market is fueled by their versatility and broad utility.

By application, marketing & pricing management segment poised to register highest growth rate over forecast period

Marketing and pricing management is becoming increasingly popular as an application of causal AI because it can identify the exact factors behind customer behavior and buying choices. In a competitive environment where personalized interactions and flexible pricing tactics are crucial for success, causal AI provides companies with a means to go beyond just correlation-driven insights. An example is when causal AI helps marketers decide whether offering a discount increases overall revenue or simply shifts demand temporarily. By identifying true cause-and-effect relationships, marketing tactics that genuinely influence customer engagement can be determined. In the same way, businesses can use it to model different pricing tactics and forecast how they will affect various customer groups immediately. As customer demands for customization increase, research findings show that businesses achieving success in personalization experience a substantial boost in revenue. This highlights the need for causality in pricing strategies.

North America to emerge as largest region by market share in 2024

North America dominates the causal AI market owing to its robust technological ecosystem, the early embrace of advanced AI solutions, and the existence of important industry pioneers. The area is home to many top causal AI providers, innovative research institutions, and companies keen on incorporating AI-based decision-making into their processes. Sectors like healthcare, finance, and retail are creating a need for advanced tools to solve difficult problems, such as enhancing patient results, improving fraud detection, and optimizing customer experiences. Laws like HIPAA and rising AI transparency guidelines are encouraging organizations in North America to choose causal AI solutions for their transparency and accountability features. Successful venture capital environments and government-supported innovation initiatives have provided substantial investment in AI research and development. North America's technological preparedness, industry needs, and financial backing have positioned it as the leading and most developed market for causal AI, as businesses depend more on these tools to obtain valuable insights and stay ahead of the competition.

HIGHEST CAGR MARKET IN 2030
INDIA FASTEST GROWING MARKET IN THE REGION
Causal AI Market Size and Share

Recent Developments of Causal AI Market

  • In October 2024, causaLens launched new enhancements in the AI agent’s platform. These enhancements facilitate improved decision-making by combining causal AI and large language models, enabling users to interpret complex data with accuracy and recommend optimal actions. This innovation provides businesses with faster, explainable insights into causal relationships in data for improved, data-driven strategies.
  • In September 2024, Google Cloud and causaLens collaborated to integrate causaLens’ causal AI technology with Google Cloud’s generative AI and cloud capabilities. This partnership enables large language models (LLMs) to handle complex quantitative data with enhanced causal reasoning, supporting businesses in making data-driven, explainable decisionsl.
  • In September 2024, Taskade enhanced its AI Causal Inference GPT Agent with the addition of Public AI Agents for easy sharing and deployment, one-click video calls, and automated tables with customizable fields for task management. These features aim to improve collaboration and efficiency, allowing users to seamlessly connect and automate workflows within their projects.
  • In April 2024, IBM Instana introduced a new feature called Probable Root Cause as part of its Intelligent Incident Remediation capabilities. This feature uses causal AI to automatically analyze incidents by assessing call statistics and application topology, enabling faster identification of the root cause of issues.
  • In September 2024, Logility acquired Garvis to enhance its supply chain planning with AI-driven demand forecasting. The integration will combine generative AI and causal AI through DemandAI+, offering real-time, data-driven insights and reducing planning time. This acquisition aims to create a more agile and transparent supply chain system.
  • In March 2023, Causality Link partnered with Bayesia to integrate AI-driven insights into financial decision-making. By combining Bayesia's expertise in Bayesian networks with Causality Link's natural language processing, the partnership seeks to deliver real-time data-driven solutions for investors and researchers.

Key Market Players

List of Top Causal AI Market Companies

The Causal AI Market is dominated by a few major players that have a wide regional presence. The major players in the Causal AI Market are

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Scope of the Report

Report Attribute Details
Market size available for years 2019–2030
Base year considered 2023
Forecast period 2024–2030
Forecast units USD (Billion/Million)
Segments Covered Offering, Application, Vertical and Region
Regions covered North America, Europe, Asia Pacific, Middle East & Africa, and Latin America

 

Key Questions Addressed by the Report

How does causal AI differ from traditional AI models?
Causal AI differs from traditional AI in that it focuses on uncovering cause-and-effect relationships rather than just identifying patterns or correlations. While traditional AI predicts outcomes based on historical data, it often lacks the ability to explain why those outcomes occur. Causal AI, however, provides actionable insights by identifying the root causes behind events and simulating the impact of different interventions. This makes it especially valuable for decision-making in areas like healthcare, finance, and marketing, where understanding the "why" is essential.
What is the total CAGR expected to be recorded for the causal AI market during 2024–2030?
The causal AI market is expected to record a CAGR of 41.8% from 2024 to 2030.
What are the key drivers supporting the growth of the causal AI market?
The key factors driving the growth of the causal AI market include increasing demand for explainable AI in regulated industries, growing demand for robust counterfactual analysis, surge in demand for predictive maintenance and root cause analysis, and shift from predictive to causal AI-based prescriptive analytics.
Which are the top-3 verticals prevailing in the causal AI market?
The leading verticals in the causal AI market include BFSI, healthcare and life sciences, and retail & e-commerce.
Who are the key vendors in the causal AI market?
Major vendors offering causal AI solutions & services across the globe include IBM (US), Google (US), Microsoft (US), Dynatrace (US), Cognizant (US), Logility (US), DataRobot (US), causaLens (UK), Aitia (US), Taskade (US), Causely (US), Causaly (UK), Causality Link (US), Xplain Data (Germany), Parabole.AI (US), Datma (US), Incrmntal (Israel), Scalnyx (France), Geminos (US), Data Poem (US), CausaAI (Netherlands), Causa (UK), Lifesight (US), Actable AI (UK), biotx.ai (Germany), Howso (US), VELDT (Japan), and CML Insight (US).

 

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Table of Contents

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TITLE
PAGE NO
INTRODUCTION
32
RESEARCH METHODOLOGY
39
EXECUTIVE SUMMARY
51
PREMIUM INSIGHTS
58
MARKET OVERVIEW AND INDUSTRY TRENDS
61
  • 5.1 INTRODUCTION
  • 5.2 MARKET DYNAMICS
    DRIVERS
    - Increasing demand for explainable AI in regulated industries
    - Growing demand for robust counterfactual analysis
    - Surge in demand for predictive maintenance and root cause analysis
    - Shift from predictive to causal AI-based prescriptive analytics
    RESTRAINTS
    - Lack of standardized tools and frameworks for causal inference
    - High computational costs for causal modeling
    OPPORTUNITIES
    - Causal AI in precision healthcare and drug discovery
    - Scalable causal inference APIs for real-time applications
    - Integrating causal AI with IoT for real-time decision making
    CHALLENGES
    - Complexity of causal model development and interpretability
    - Data quality and availability for causal inference
  • 5.3 EVOLUTION OF CAUSAL AI
  • 5.4 SUPPLY CHAIN ANALYSIS
  • 5.5 ECOSYSTEM ANALYSIS
    CAUSAL AI PLATFORM PROVIDERS
    CAUSAL AI TOOL PROVIDERS
    CAUSAL AI TOOLKITS AND APIS PROVIDERS
    CAUSAL AI SERVICE PROVIDERS
  • 5.6 INVESTMENT LANDSCAPE AND FUNDING SCENARIO
  • 5.7 IMPACT OF GENERATIVE AI IN CAUSAL AI MARKET
    ENHANCED DATA AVAILABILITY FOR CAUSAL ANALYSIS
    STRESS TESTING OF CAUSAL MODELS
    SUPPORT FOR COMPLEX MULTIVARIABLE ANALYSIS
    ACCELERATED MODEL DEVELOPMENT
    BIAS REDUCTION FOR FAIRER OUTCOMES
    DYNAMIC SIMULATIONS FOR CAUSAL TESTING
  • 5.8 PRICING ANALYSIS
    PRICING DATA, BY OFFERING
    PRICING DATA, BY APPLICATION
  • 5.9 CASE STUDY ANALYSIS
    CASE STUDY 1: DYNATRACE BOOSTS BMO'S DIGITAL EFFICIENCY WITH CAUSAL AI-POWERED INSIGHTS AND AUTOMATION
    CASE STUDY 2: FINGERSOFT ACHIEVES DATA-DRIVEN MARKETING OPTIMIZATION WITH INCRMNTAL’S CAUSAL AI INSIGHTS
    CASE STUDY 3: ACCELERATING FAULT DETECTION WITH CAUSAL AI FOR ENHANCED PRODUCT RELIABILITY IN MANUFACTURING
    CASE STUDY 4: LEVERAGING CAUSAL AI FOR ENHANCED ROOT CAUSE ANALYSIS IN TRUMPF’S EQUIPMENT MAINTENANCE
    CASE STUDY 5: CAUSA TECH ENHANCED OPERATIONAL EFFICIENCY FOR LEADING MANUFACTURING FIRM, STRENGTHENING SUPPLY CHAIN RESILIENCE
    CASE STUDY 6: LIFESIGHT ADDRESSING KEY CHALLENGES IN MARKETING, ENHANCING EFFICIENCY AND SALES FOR DTC BEAUTY BRAND
  • 5.10 TECHNOLOGY ANALYSIS
    KEY TECHNOLOGIES
    - Causal inference algorithms
    - Explainable AI (XAI)
    - Structural equation modeling (SEM)
    - Bayesian networks
    - Causal graphs
    COMPLEMENTARY TECHNOLOGIES
    - Machine learning
    - Reinforcement learning
    - Data engineering
    - Knowledge graphs
    ADJACENT TECHNOLOGIES
    - Predictive analytics
    - Decision intelligence
    - Synthetic data generation
    - Natural language processing (NLP)
  • 5.11 REGULATORY LANDSCAPE
    REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
    REGULATIONS: CAUSAL AI
    - North America
    - Europe
    - Asia Pacific
    - Middle East & Africa
    - Latin America
  • 5.12 PATENT ANALYSIS
    METHODOLOGY
    PATENTS FILED, BY DOCUMENT TYPE
    INNOVATION AND PATENT APPLICATIONS
  • 5.13 KEY CONFERENCES AND EVENTS (2024–2025)
  • 5.14 PORTER’S FIVE FORCES ANALYSIS
    THREAT OF NEW ENTRANTS
    THREAT OF SUBSTITUTES
    BARGAINING POWER OF SUPPLIERS
    BARGAINING POWER OF BUYERS
    INTENSITY OF COMPETITIVE RIVALRY
  • 5.15 KEY STAKEHOLDERS & BUYING CRITERIA
    KEY STAKEHOLDERS IN BUYING PROCESS
    BUYING CRITERIA
  • 5.16 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
CAUSAL AI MARKET, BY OFFERING
114
  • 6.1 INTRODUCTION
    OFFERING: CAUSAL AI MARKET DRIVERS
  • 6.2 SOFTWARE
    RISING DEMAND FOR DATA-DRIVEN DECISIONS DRIVES GROWTH IN INDUSTRY-SPECIFIC CAUSAL AI SOFTWARE
    CAUSAL AI PLATFORMS
    CAUSAL AI SOLUTIONS
    - Causal discovery
    - Causal modeling
    - Decision intelligence
    - Root-cause analysis
    - Causal AI APIs
    - Software development kits
  • 6.3 SERVICES
    CAUSAL AI SERVICES ENABLE BUSINESSES TO PREDICT IMPACT OF POTENTIAL CHANGES AND MAKE PROACTIVE ADJUSTMENTS
    - Consulting services
    - Deployment & integration services
    - Training, support & maintenance services
CAUSAL AI MARKET, BY APPLICATION
131
  • 7.1 INTRODUCTION
    APPLICATION: CAUSAL AI MARKET DRIVERS
  • 7.2 FINANCIAL MANAGEMENT
    CAUSAL AI IMPROVES REGULATORY COMPLIANCE AND FOSTERS AGILE FINANCIAL MANAGEMENT IN ORGANIZATIONS
    FACTOR INVESTING
    PORTFOLIO SIMULATION
    INVESTMENT ANALYSIS
    OTHER FINANCIAL MANAGEMENT APPLICATIONS
  • 7.3 SALES & CUSTOMER MANAGEMENT
    CAUSAL AI HELPS ORGANIZATIONS IDENTIFY KEY DRIVERS OF CUSTOMER ACTIONS BY ANALYZING CAUSAL RELATIONSHIPS BETWEEN FACTORS
    CHURN PREDICTION & PREVENTION
    CUSTOMER SEGMENTATION
    CUSTOMER LIFETIME VALUE (CLV) PREDICTION
    CUSTOMER EXPERIENCE OPTIMIZATION
    PERSONALIZED RECOMMENDATIONS
    OTHER SALES & CUSTOMER MANAGEMENT APPLICATIONS
  • 7.4 OPERATIONS & SUPPLY CHAIN MANAGEMENT
    CAUSAL AI ENABLES BUSINESSES OPTIMIZE PROCESSES, PREDICT DISRUPTIONS, AND MAKE DATA-DRIVEN DECISIONS TO ENHANCE EFFICIENCY
    BOTTLENECK REMEDIATION
    PREDICTIVE MAINTENANCE
    REAL-TIME FAILURE RESPONSE
    INVENTORY MANAGEMENT
    OTHER OPERATIONS & SUPPLY CHAIN MANAGEMENT APPLICATIONS
  • 7.5 MARKETING & PRICING MANAGEMENT
    CAUSAL AI HELPS BUSINESSES MAKE DATA-DRIVEN DECISIONS TO BOOST PROFITABILITY AND GAIN COMPETITIVE EDGE IN RAPIDLY CHANGING MARKET
    MARKETING CHANNEL OPTIMIZATION
    PRICE ELASTICITY MODELING
    PROMOTIONAL IMPACT ANALYSIS
    COMPETITIVE PRICING ANALYSIS
    OTHER MARKETING & PRICING MANAGEMENT APPLICATIONS
  • 7.6 OTHER APPLICATIONS
CAUSAL AI MARKET, BY VERTICAL
161
  • 8.1 INTRODUCTION
    VERTICAL: CAUSAL AI MARKET DRIVERS
  • 8.2 BFSI
    CAUSAL AI RESHAPE BFSI PRACTICES, SETTING NEW STANDARDS FOR CUSTOMER-CENTRIC SERVICE DELIVERY IN FINANCIAL ECOSYSTEMS
    BFSI: USE CASES
  • 8.3 HEALTHCARE & LIFE SCIENCES
    CAUSAL AI GUIDES POLICIES OR PUBLIC HEALTH INTERVENTIONS, LEADING TO EFFECTIVE HEALTH PROGRAMS
    HEALTHCARE & LIFE SCIENCES: USE CASES
  • 8.4 RETAIL & E-COMMERCE
    BUSINESSES USING CAUSAL AI FOR ANALYZING FINANCIAL IMPACT, PROVIDING DATA-BACKED INSIGHTS ON DECISIONS
    RETAIL & E-COMMERCE: USE CASES
  • 8.5 MANUFACTURING
    CAUSAL AI ENABLES DEEPER INSIGHTS INTO CAUSE-AND-EFFECT RELATIONSHIPS IN PRODUCTION PROCESSES, REVOLUTIONIZING MANUFACTURING
    MANUFACTURING: USE CASES
  • 8.6 TRANSPORTATION & LOGISTICS
    CAUSAL AI ENHANCING INVENTORY MANAGEMENT, ROUTE PLANNING, AND OVERALL OPERATIONAL EFFICIENCY, REDUCING DOWNTIME AND COSTS
    TRANSPORTATION & LOGISTICS: USE CASES
  • 8.7 MEDIA & ENTERTAINMENT
    CAUSAL AI PROVIDES DEEPER INSIGHTS INTO CONTENT CREATION AND AUDIENCE ENGAGEMENT
    MEDIA & ENTERTAINMENT: USE CASES
  • 8.8 TELECOMMUNICATIONS
    TELECOM COMPANIES UTILIZING CAUSAL AI TO IDENTIFY SPECIFIC FACTORS CONTRIBUTING TO CUSTOMER DISSATISFACTION
    TELECOMMUNICATIONS: USE CASES
  • 8.9 ENERGY & UTILITIES
    CAUSAL AI OPTIMIZES ENERGY PRODUCTION, ALLOWING MORE EFFICIENT SCHEDULING AND OPERATION OF PLANTS
    ENERGY & UTILITIES: USE CASES
  • 8.10 OTHER VERTICALS
CAUSAL AI MARKET, BY REGION
179
  • 9.1 INTRODUCTION
  • 9.2 NORTH AMERICA
    NORTH AMERICA: CAUSAL AI MARKET DRIVERS
    NORTH AMERICA: MACROECONOMIC OUTLOOK
    US
    - Need for advanced analytics that determine cause-and-effect relationships to drive market
    CANADA
    - Use of causal AI to enhance everything from supply chain operations to personalized marketing strategies to drive market
  • 9.3 EUROPE
    EUROPE: CAUSAL AI MARKET DRIVERS
    EUROPE: MACROECONOMIC OUTLOOK
    UK
    - Advancements in machine learning, data analytics, and artificial intelligence technologies to drive market
    GERMANY
    - Investment in AI research through initiatives to drive market
    FRANCE
    - French AI startups attracting significant investment to scale their AI-driven platforms to drive market
    REST OF EUROPE
  • 9.4 ASIA PACIFIC
    ASIA PACIFIC: CAUSAL AI MARKET DRIVERS
    ASIA PACIFIC: MACROECONOMIC OUTLOOK
    CHINA
    - China’s strong commitment to becoming world leader in AI to drive market
    INDIA
    - Advancements in causal AI by Indian tech firms and academia, supported by collaborations and government initiatives, to drive market
    JAPAN
    - Industries leveraging causal AI to optimize operations and create more adaptive systems to drive market
    SOUTH KOREA
    - Partnerships with global AI firms to create more advanced causal inference algorithms to drive market
    ASEAN
    - Integration of causal AI into diverse sectors to drive market
    REST OF ASIA PACIFIC
  • 9.5 MIDDLE EAST & AFRICA
    MIDDLE EAST & AFRICA: CAUSAL AI MARKET DRIVERS
    MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK
    SAUDI ARABIA
    - Leveraging causal models to enhance predictive capabilities, optimize resource allocation, and improve operational efficiencies to drive market
    UAE
    - Prioritization of AI across development strategies to drive market
    SOUTH AFRICA
    - Startups using causal AI to improve financial inclusion to drive market
    REST OF MIDDLE EAST
  • 9.6 LATIN AMERICA
    LATIN AMERICA: CAUSAL AI MARKET DRIVERS
    LATIN AMERICA: MACROECONOMIC OUTLOOK
    BRAZIL
    - Growing demand for advanced analytics and decision-making tools across sectors to drive market
    MEXICO
    - Causal AI to play pivotal role in reshaping technological landscape and business strategies
    REST OF LATIN AMERICA
    COMPETITIVE LANDSCAPE
  • 9.1 OVERVIEW
  • 9.2 KEY PLAYER STRATEGIES/RIGHT TO WIN
  • 9.3 REVENUE ANALYSIS
  • 9.4 MARKET SHARE ANALYSIS
    MARKET SHARE OF KEY PLAYERS OFFERING CAUSAL AI
    - Market Ranking Analysis
  • 9.5 PRODUCT COMPARATIVE ANALYSIS
    DECISIONOS PLATFORM (CAUSALENS)
    CAUSAL REASONING PLATFORM (CAUSELY)
    LIFESIGHT PLATFORM (LIFESIGHT)
    CAUSALITY ENGINE, COGNIZANT CAUSALITY SERVICE (COGNIZANT)
    DYNATRACE PLATFORM (DYNATRACE)
  • 9.6 COMPANY VALUATION AND FINANCIAL METRICS
  • 9.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023
    STARS
    EMERGING LEADERS
    PERVASIVE PLAYERS
    PARTICIPANTS
    COMPANY FOOTPRINT: KEY PLAYERS, 2023
    - Company footprint
    - Regional footprint
    - Offering footprint
    - Application footprint
    - Vertical footprint
  • 9.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2023
    PROGRESSIVE COMPANIES
    RESPONSIVE COMPANIES
    DYNAMIC COMPANIES
    STARTING BLOCKS
    COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2023
    - Detailed list of key startups/SMEs
    - Competitive benchmarking of key startups/SMEs
  • 9.9 COMPETITIVE SCENARIO AND TRENDS
    PRODUCT LAUNCHES AND ENHANCEMENTS
    DEALS
COMPANY PROFILES
270
  • 10.1 INTRODUCTION
  • 10.2 KEY PLAYERS
    GOOGLE
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    - MnM view
    IBM
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    - MnM view
    MICROSOFT
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    - MnM view
    DYNATRACE
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    - MnM view
    COGNIZANT
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    - MnM View
    LOGILITY
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    DATAROBOT
    - Business overview
    - Products/Solutions/Services offered
    CAUSALENS
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    DATA POEM
    LIFESIGHT
    AITIA
    CAUSALY
  • 10.3 STARTUPS/SMES
    CAUSALITY LINK
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    TASKADE
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    CAUSELY
    XPLAIN DATA
    PARABOLE.AI
    DATMA
    INCRMNTAL
    SCALNYX
    GEMINOS
    CAUSAI
    CAUSA
    ACTABLE AI
    BIOTX.AI
    HOWSO
    VELDT
    CML INSIGHT
ADJACENT AND RELATED MARKETS
309
  • 11.1 INTRODUCTION
  • 11.2 ARTIFICIAL INTELLIGENCE (AI) MARKET – GLOBAL FORECAST TO 2030
    MARKET DEFINITION
    MARKET OVERVIEW
    - Artificial intelligence market, by offering
    - Artificial intelligence market, by business function
    - Artificial intelligence market, by technology
    - Artificial intelligence market, by vertical
    - Artificial intelligence market, by region
  • 11.3 AI GOVERNANCE MARKET– GLOBAL FORECAST TO 2030
    MARKET DEFINITION
    MARKET OVERVIEW
    - AI governance market, by product type
    - AI governance market, by functionality
    - AI governance market, by end user
    - AI governance market, by region
APPENDIX
322
  • 12.1 DISCUSSION GUIDE
  • 12.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL
  • 12.3 CUSTOMIZATION OPTIONS
  • 12.4 RELATED REPORTS
  • 12.5 AUTHOR DETAILS
LIST OF TABLES
 
  • TABLE 1 CAUSAL AI MARKET DETAILED SEGMENTATION
  • TABLE 2 UNITED STATES DOLLAR EXCHANGE RATE, 2019–2023
  • TABLE 3 PRIMARY INTERVIEWS
  • TABLE 4 FACTOR ANALYSIS
  • TABLE 5 GLOBAL CAUSAL AI MARKET SIZE AND GROWTH RATE, 2019–2023 (USD THOUSAND, Y-O-Y %)
  • TABLE 6 GLOBAL MARKET SIZE AND GROWTH RATE, 2024–2030 (USD THOUSAND, Y-O-Y %)
  • TABLE 7 MARKET: ECOSYSTEM
  • TABLE 8 PRICING DATA OF CAUSAL AI, BY OFFERING
  • TABLE 9 PRICING DATA OF CAUSAL AI, BY APPLICATION
  • TABLE 10 NORTH AMERICA: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • TABLE 11 EUROPE: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • TABLE 12 ASIA PACIFIC: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • TABLE 13 MIDDLE EAST & AFRICA: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • TABLE 14 LATIN AMERICA: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • TABLE 15 PATENTS FILED, 2015–2024
  • TABLE 16 LIST OF FEW PATENTS IN MARKET, 2022–2024
  • TABLE 17 CAUSAL AI MARKET: DETAILED LIST OF CONFERENCES & EVENTS, 2024–2025
  • TABLE 18 PORTERS’ FIVE FORCES’ IMPACT ON MARKET
  • TABLE 19 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE END USERS
  • TABLE 20 KEY BUYING CRITERIA FOR TOP THREE END USERS
  • TABLE 21 MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 22 MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 23 SOFTWARE: MARKET, BY TYPE, 2019–2023 (USD THOUSAND)
  • TABLE 24 SOFTWARE: MARKET, BY TYPE, 2024–2030 (USD THOUSAND)
  • TABLE 25 CAUSAL AI PLATFORMS: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 26 CAUSAL AI PLATFORMS: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 27 CAUSAL AI SOLUTIONS: MARKET, BY TYPE, 2019–2023 (USD THOUSAND)
  • TABLE 28 CAUSAL AI SOLUTIONS: MARKET, BY TYPE, 2024–2030 (USD THOUSAND)
  • TABLE 29 CAUSAL DISCOVERY: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 30 CAUSAL DISCOVERY: CAUSAL AI MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 31 CAUSAL MODELING: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 32 CAUSAL MODELING: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 33 DECISION INTELLIGENCE: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 34 DECISION INTELLIGENCE: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 35 ROOT-CAUSE ANALYSIS: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 36 ROOT-CAUSE ANALYSIS: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 37 CAUSAL AI APIS: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 38 CAUSAL AI APIS: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 39 SOFTWARE DEVELOPMENT KITS: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 40 SOFTWARE DEVELOPMENT KITS: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 41 SERVICES: MARKET, BY TYPE, 2019–2023 (USD THOUSAND)
  • TABLE 42 SERVICES: MARKET, BY TYPE, 2024–2030 (USD THOUSAND)
  • TABLE 43 CONSULTING SERVICES: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 44 CONSULTING SERVICES: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 45 DEPLOYMENT & INTEGRATION SERVICES: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 46 DEPLOYMENT & INTEGRATION SERVICES: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 47 TRAINING, SUPPORT & MAINTENANCE SERVICES: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 48 TRAINING, SUPPORT & MAINTENANCE SERVICES: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 49 CAUSAL AI MARKET, BY APPLICATION, 2019–2023 (USD THOUSAND)
  • TABLE 50 MARKET, BY APPLICATION, 2024–2030 (USD THOUSAND)
  • TABLE 51 FINANCIAL MANAGEMENT: MARKET, BY TYPE, 2019–2023 (USD THOUSAND)
  • TABLE 52 FINANCIAL MANAGEMENT: MARKET, BY TYPE, 2024–2030 (USD THOUSAND)
  • TABLE 53 FACTOR INVESTING: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 54 FACTOR INVESTING: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 55 PORTFOLIO SIMULATION: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 56 PORTFOLIO SIMULATION: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 57 INVESTMENT ANALYSIS: CAUSAL AI MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 58 INVESTMENT ANALYSIS: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 59 OTHER FINANCIAL MANAGEMENT APPLICATIONS: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 60 OTHER FINANCIAL MANAGEMENT APPLICATIONS: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 61 SALES & CUSTOMER MANAGEMENT: MARKET, BY TYPE, 2019–2023 (USD THOUSAND)
  • TABLE 62 SALES & CUSTOMER MANAGEMENT: MARKET, BY TYPE, 2024–2030 (USD THOUSAND)
  • TABLE 63 CHURN PREDICTION & PREVENTION: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 64 CHURN PREDICTION & PREVENTION: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 65 CUSTOMER SEGMENTATION: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 66 CUSTOMER SEGMENTATION: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 67 CUSTOMER LIFETIME VALUE (CLV) PREDICTION: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 68 CUSTOMER LIFETIME VALUE (CLV) PREDICTION: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 69 CUSTOMER EXPERIENCE OPTIMIZATION: CAUSAL AI MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 70 CUSTOMER EXPERIENCE OPTIMIZATION: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 71 PERSONALIZED RECOMMENDATIONS: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 72 PERSONALIZED RECOMMENDATIONS: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 73 OTHER SALES & CUSTOMER MANAGEMENT APPLICATIONS: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 74 OTHER SALES & CUSTOMER MANAGEMENT APPLICATIONS: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 75 OPERATIONS & SUPPLY CHAIN MANAGEMENT: MARKET, BY TYPE, 2019–2023 (USD THOUSAND)
  • TABLE 76 OPERATIONS & SUPPLY CHAIN MANAGEMENT: MARKET, BY TYPE, 2024–2030 (USD THOUSAND)
  • TABLE 77 BOTTLENECK REMEDIATION: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 78 BOTTLENECK REMEDIATION: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 79 PREDICTIVE MAINTENANCE: CAUSAL AI MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 80 PREDICTIVE MAINTENANCE: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 81 REAL-TIME FAILURE RESPONSE: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 82 REAL-TIME FAILURE RESPONSE: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 83 INVENTORY MANAGEMENT: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 84 INVENTORY MANAGEMENT: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 85 OTHER OPERATIONS & SUPPLY CHAIN MANAGEMENT APPLICATIONS: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 86 OTHER OPERATIONS & SUPPLY CHAIN MANAGEMENT APPLICATIONS: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 87 MARKETING & PRICING MANAGEMENT: MARKET, BY TYPE, 2019–2023 (USD THOUSAND)
  • TABLE 88 MARKETING & PRICING MANAGEMENT: MARKET, BY TYPE, 2024–2030 (USD THOUSAND)
  • TABLE 89 MARKETING CHANNEL OPTIMIZATION: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 90 MARKETING CHANNEL OPTIMIZATION: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 91 PRICE ELASTICITY MODELING: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 92 PRICE ELASTICITY MODELING: CAUSAL AI MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 93 PROMOTIONAL IMPACT ANALYSIS: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 94 PROMOTIONAL IMPACT ANALYSIS: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 95 COMPETITIVE PRICING ANALYSIS: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 96 COMPETITIVE PRICING ANALYSIS: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 97 OTHER MARKETING & PRICING MANAGEMENT APPLICATIONS: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 98 OTHER MARKETING & PRICING MANAGEMENT APPLICATIONS: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 99 OTHER APPLICATIONS: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 100 OTHER APPLICATIONS: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 101 MARKET, BY VERTICAL, 2019–2023 (USD THOUSAND)
  • TABLE 102 MARKET, BY VERTICAL, 2024–2030 (USD THOUSAND)
  • TABLE 103 BFSI: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 104 BFSI: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 105 HEALTHCARE & LIFE SCIENCES: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 106 HEALTHCARE & LIFE SCIENCES: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 107 RETAIL & E-COMMERCE: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 108 RETAIL & E-COMMERCE: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 109 MANUFACTURING: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 110 MANUFACTURING: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 111 TRANSPORTATION & LOGISTICS: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 112 TRANSPORTATION & LOGISTICS: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 113 MEDIA & ENTERTAINMENT: CAUSAL AI MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 114 MEDIA & ENTERTAINMENT: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 115 TELECOMMUNICATIONS: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 116 TELECOMMUNICATIONS: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 117 ENERGY & UTILITIES: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 118 ENERGY & UTILITIES: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 119 OTHER VERTICALS: MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 120 OTHER VERTICALS: MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 121 MARKET, BY REGION, 2019–2023 (USD THOUSAND)
  • TABLE 122 MARKET, BY REGION, 2024–2030 (USD THOUSAND)
  • TABLE 123 NORTH AMERICA: CAUSAL AI MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 124 NORTH AMERICA: MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 125 NORTH AMERICA: MARKET, BY SOFTWARE TYPE, 2019–2023 (USD THOUSAND)
  • TABLE 126 NORTH AMERICA: MARKET, BY SOFTWARE TYPE, 2024–2030 (USD THOUSAND)
  • TABLE 127 NORTH AMERICA: MARKET, BY CAUSAL AI SOLUTION, 2019–2023 (USD THOUSAND)
  • TABLE 128 NORTH AMERICA: MARKET, BY CAUSAL AI SOLUTION, 2024–2030 (USD THOUSAND)
  • TABLE 129 NORTH AMERICA: MARKET, BY SERVICE, 2019–2023 (USD THOUSAND)
  • TABLE 130 NORTH AMERICA: MARKET, BY SERVICE, 2024–2030 (USD THOUSAND)
  • TABLE 131 NORTH AMERICA: MARKET, BY APPLICATION, 2019–2023 (USD THOUSAND)
  • TABLE 132 NORTH AMERICA: MARKET, BY APPLICATION, 2024–2030 (USD THOUSAND)
  • TABLE 133 NORTH AMERICA: MARKET, BY FINANCIAL MANAGEMENT, 2019–2023 (USD THOUSAND)
  • TABLE 134 NORTH AMERICA: MARKET, BY FINANCIAL MANAGEMENT, 2024–2030 (USD THOUSAND)
  • TABLE 135 NORTH AMERICA: MARKET, BY SALES AND CUSTOMER MANAGEMENT, 2019–2023 (USD THOUSAND)
  • TABLE 136 NORTH AMERICA: MARKET, BY SALES AND CUSTOMER MANAGEMENT, 2024–2030 (USD THOUSAND)
  • TABLE 137 NORTH AMERICA: CAUSAL AI MARKET, BY OPERATIONS & SUPPLY CHAIN MANAGEMENT, 2019–2023 (USD THOUSAND)
  • TABLE 138 NORTH AMERICA: MARKET, BY OPERATIONS & SUPPLY CHAIN MANAGEMENT, 2024–2030 (USD THOUSAND)
  • TABLE 139 NORTH AMERICA: MARKET, BY MARKETING & PRICING MANAGEMENT, 2019–2023 (USD THOUSAND)
  • TABLE 140 NORTH AMERICA: MARKET, BY MARKETING & PRICING MANAGEMENT, 2024–2030 (USD THOUSAND)
  • TABLE 141 NORTH AMERICA: MARKET, BY VERTICAL, 2019–2023 (USD THOUSAND)
  • TABLE 142 NORTH AMERICA: MARKET, BY VERTICAL, 2024–2030 (USD THOUSAND)
  • TABLE 143 NORTH AMERICA: MARKET, BY COUNTRY, 2019–2023 (USD THOUSAND)
  • TABLE 144 NORTH AMERICA: MARKET, BY COUNTRY, 2024–2030 (USD THOUSAND)
  • TABLE 145 US: MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 146 US: MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 147 CANADA: CAUSAL AI MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 148 CANADA: MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 149 EUROPE: MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 150 EUROPE: MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 151 EUROPE: MARKET, BY SOFTWARE TYPE, 2019–2023 (USD THOUSAND)
  • TABLE 152 EUROPE: MARKET, BY SOFTWARE TYPE, 2024–2030 (USD THOUSAND)
  • TABLE 153 EUROPE: MARKET, BY CAUSAL AI SOLUTION, 2019–2023 (USD THOUSAND)
  • TABLE 154 EUROPE: MARKET, BY CAUSAL AI SOLUTION, 2024–2030 (USD THOUSAND)
  • TABLE 155 EUROPE: MARKET, BY SERVICE, 2019–2023 (USD THOUSAND)
  • TABLE 156 EUROPE: MARKET, BY SERVICE, 2024–2030 (USD THOUSAND)
  • TABLE 157 EUROPE: MARKET, BY APPLICATION, 2019–2023 (USD THOUSAND)
  • TABLE 158 EUROPE: MARKET, BY APPLICATION, 2024–2030 (USD THOUSAND)
  • TABLE 159 EUROPE: MARKET, BY FINANCIAL MANAGEMENT, 2019–2023 (USD THOUSAND)
  • TABLE 160 EUROPE: MARKET, BY FINANCIAL MANAGEMENT, 2024–2030 (USD THOUSAND)
  • TABLE 161 EUROPE: CAUSAL AI MARKET, BY SALES AND CUSTOMER MANAGEMENT, 2019–2023 (USD THOUSAND)
  • TABLE 162 EUROPE: MARKET, BY SALES AND CUSTOMER MANAGEMENT, 2024–2030 (USD THOUSAND)
  • TABLE 163 EUROPE: MARKET, BY OPERATIONS & SUPPLY CHAIN MANAGEMENT, 2019–2023 (USD THOUSAND)
  • TABLE 164 EUROPE: MARKET, BY OPERATIONS & SUPPLY CHAIN MANAGEMENT, 2024–2030 (USD THOUSAND)
  • TABLE 165 EUROPE: MARKET, BY MARKETING & PRICING MANAGEMENT, 2019–2023 (USD THOUSAND)
  • TABLE 166 EUROPE: MARKET, BY MARKETING & PRICING MANAGEMENT, 2024–2030 (USD THOUSAND)
  • TABLE 167 EUROPE: MARKET, BY VERTICAL, 2019–2023 (USD THOUSAND)
  • TABLE 168 EUROPE: MARKET, BY VERTICAL, 2024–2030 (USD THOUSAND)
  • TABLE 169 EUROPE: MARKET, BY COUNTRY, 2019–2023 (USD THOUSAND)
  • TABLE 170 EUROPE: MARKET, BY COUNTRY, 2024–2030 (USD THOUSAND)
  • TABLE 171 UK: MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 172 UK: MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 173 GERMANY: MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 174 GERMANY: CAUSAL AI MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 175 FRANCE: MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 176 FRANCE: MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 177 REST OF EUROPE: MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 178 REST OF EUROPE: MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 179 ASIA PACIFIC: MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 180 ASIA PACIFIC: MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 181 ASIA PACIFIC: MARKET, BY SOFTWARE TYPE, 2019–2023 (USD THOUSAND)
  • TABLE 182 ASIA PACIFIC: MARKET, BY SOFTWARE TYPE, 2024–2030 (USD THOUSAND)
  • TABLE 183 ASIA PACIFIC: CAUSAL AI MARKET, BY CAUSAL AI SOLUTION, 2019–2023 (USD THOUSAND)
  • TABLE 184 ASIA PACIFIC: MARKET, BY CAUSAL AI SOLUTION, 2024–2030 (USD THOUSAND)
  • TABLE 185 ASIA PACIFIC: MARKET, BY SERVICE, 2019–2023 (USD THOUSAND)
  • TABLE 186 ASIA PACIFIC: MARKET, BY SERVICE, 2024–2030 (USD THOUSAND)
  • TABLE 187 ASIA PACIFIC: MARKET, BY APPLICATION, 2019–2023 (USD THOUSAND)
  • TABLE 188 ASIA PACIFIC: MARKET, BY APPLICATION, 2024–2030 (USD THOUSAND)
  • TABLE 189 ASIA PACIFIC: MARKET, BY FINANCIAL MANAGEMENT, 2019–2023 (USD THOUSAND)
  • TABLE 190 ASIA PACIFIC: MARKET, BY FINANCIAL MANAGEMENT, 2024–2030 (USD THOUSAND)
  • TABLE 191 ASIA PACIFIC: MARKET, BY SALES AND CUSTOMER MANAGEMENT, 2019–2023 (USD THOUSAND)
  • TABLE 192 ASIA PACIFIC: MARKET, BY SALES AND CUSTOMER MANAGEMENT, 2024–2030 (USD THOUSAND)
  • TABLE 193 ASIA PACIFIC: MARKET, BY OPERATIONS & SUPPLY CHAIN MANAGEMENT, 2019–2023 (USD THOUSAND)
  • TABLE 194 ASIA PACIFIC: MARKET, BY OPERATIONS & SUPPLY CHAIN MANAGEMENT, 2024–2030 (USD THOUSAND)
  • TABLE 195 ASIA PACIFIC: MARKET, BY MARKETING & PRICING MANAGEMENT, 2019–2023 (USD THOUSAND)
  • TABLE 196 ASIA PACIFIC: MARKET, BY MARKETING & PRICING MANAGEMENT, 2024–2030 (USD THOUSAND)
  • TABLE 197 ASIA PACIFIC: MARKET, BY VERTICAL, 2019–2023 (USD THOUSAND)
  • TABLE 198 ASIA PACIFIC: MARKET, BY VERTICAL, 2024–2030 (USD THOUSAND)
  • TABLE 199 ASIA PACIFIC: MARKET, BY COUNTRY, 2019–2023 (USD THOUSAND)
  • TABLE 200 ASIA PACIFIC: MARKET, BY COUNTRY, 2024–2030 (USD THOUSAND)
  • TABLE 201 CHINA: CAUSAL AI MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 202 CHINA: MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 203 INDIA: MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 204 INDIA: MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 205 JAPAN: MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 206 JAPAN: MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 207 SOUTH KOREA: MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 208 SOUTH KOREA: MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 209 ASEAN: CAUSAL AI MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 210 ASEAN: MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 211 REST OF ASIA PACIFIC: MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 212 REST OF ASIA PACIFIC: MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 213 MIDDLE EAST & AFRICA: MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 214 MIDDLE EAST & AFRICA: CAUSAL AI MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 215 MIDDLE EAST & AFRICA: MARKET, BY SOFTWARE TYPE, 2019–2023 (USD THOUSAND)
  • TABLE 216 MIDDLE EAST & AFRICA: MARKET, BY SOFTWARE TYPE, 2024–2030 (USD THOUSAND)
  • TABLE 217 MIDDLE EAST & AFRICA: MARKET, BY CAUSAL AI SOLUTION, 2019–2023 (USD THOUSAND)
  • TABLE 218 MIDDLE EAST & AFRICA: MARKET, BY CAUSAL AI SOLUTION, 2024–2030 (USD THOUSAND)
  • TABLE 219 MIDDLE EAST & AFRICA: MARKET, BY SERVICE, 2019–2023 (USD THOUSAND)
  • TABLE 220 MIDDLE EAST & AFRICA: MARKET, BY SERVICE, 2024–2030 (USD THOUSAND)
  • TABLE 221 MIDDLE EAST & AFRICA: MARKET, BY APPLICATION, 2019–2023 (USD THOUSAND)
  • TABLE 222 MIDDLE EAST & AFRICA: MARKET, BY APPLICATION, 2024–2030 (USD THOUSAND)
  • TABLE 223 MIDDLE EAST & AFRICA: MARKET, BY FINANCIAL MANAGEMENT, 2019–2023 (USD THOUSAND)
  • TABLE 224 MIDDLE EAST & AFRICA: MARKET, BY FINANCIAL MANAGEMENT, 2024–2030 (USD THOUSAND)
  • TABLE 225 MIDDLE EAST & AFRICA: MARKET, BY SALES AND CUSTOMER MANAGEMENT, 2019–2023 (USD THOUSAND)
  • TABLE 226 MIDDLE EAST & AFRICA: MARKET, BY SALES AND CUSTOMER MANAGEMENT, 2024–2030 (USD THOUSAND)
  • TABLE 227 MIDDLE EAST & AFRICA: CAUSAL AI MARKET, BY OPERATIONS & SUPPLY CHAIN MANAGEMENT, 2019–2023 (USD THOUSAND)
  • TABLE 228 MIDDLE EAST & AFRICA: MARKET, BY OPERATIONS & SUPPLY CHAIN MANAGEMENT, 2024–2030 (USD THOUSAND)
  • TABLE 229 MIDDLE EAST & AFRICA: MARKET, BY MARKETING & PRICING MANAGEMENT, 2019–2023 (USD THOUSAND)
  • TABLE 230 MIDDLE EAST & AFRICA: MARKET, BY MARKETING & PRICING MANAGEMENT, 2024–2030 (USD THOUSAND)
  • TABLE 231 MIDDLE EAST & AFRICA: MARKET, BY VERTICAL, 2019–2023 (USD THOUSAND)
  • TABLE 232 MIDDLE EAST & AFRICA: MARKET, BY VERTICAL, 2024–2030 (USD THOUSAND)
  • TABLE 233 MIDDLE EAST & AFRICA: MARKET, BY COUNTRY, 2019–2023 (USD THOUSAND)
  • TABLE 234 MIDDLE EAST & AFRICA: MARKET, BY COUNTRY, 2024–2030 (USD THOUSAND)
  • TABLE 235 SAUDI ARABIA: MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 236 SAUDI ARABIA: MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 237 UAE: MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 238 UAE: MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 239 SOUTH AFRICA: MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 240 SOUTH AFRICA: MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 241 REST OF MIDDLE EAST: MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 242 REST OF MIDDLE EAST: MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 243 LATIN AMERICA: CAUSAL AI MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 244 LATIN AMERICA: MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 245 LATIN AMERICA: MARKET, BY SOFTWARE TYPE, 2019–2023 (USD THOUSAND)
  • TABLE 246 LATIN AMERICA: MARKET, BY SOFTWARE TYPE, 2024–2030 (USD THOUSAND)
  • TABLE 247 LATIN AMERICA: MARKET, BY CAUSAL AI SOLUTION, 2019–2023 (USD THOUSAND)
  • TABLE 248 LATIN AMERICA: MARKET, BY CAUSAL AI SOLUTION, 2024–2030 (USD THOUSAND)
  • TABLE 249 LATIN AMERICA: MARKET, BY SERVICE, 2019–2023 (USD THOUSAND)
  • TABLE 250 LATIN AMERICA: MARKET, BY SERVICE, 2024–2030 (USD THOUSAND)
  • TABLE 251 LATIN AMERICA: MARKET, BY APPLICATION, 2019–2023 (USD THOUSAND)
  • TABLE 252 LATIN AMERICA: MARKET, BY APPLICATION, 2024–2030 (USD THOUSAND)
  • TABLE 253 LATIN AMERICA: MARKET, BY FINANCIAL MANAGEMENT, 2019–2023 (USD THOUSAND)
  • TABLE 254 LATIN AMERICA: MARKET, BY FINANCIAL MANAGEMENT, 2024–2030 (USD THOUSAND)
  • TABLE 255 LATIN AMERICA: MARKET, BY SALES AND CUSTOMER MANAGEMENT, 2019–2023 (USD THOUSAND)
  • TABLE 256 LATIN AMERICA: CAUSAL AI MARKET, BY SALES AND CUSTOMER MANAGEMENT, 2024–2030 (USD THOUSAND)
  • TABLE 257 LATIN AMERICA: MARKET, BY OPERATIONS & SUPPLY CHAIN MANAGEMENT, 2019–2023 (USD THOUSAND)
  • TABLE 258 LATIN AMERICA: MARKET, BY OPERATIONS & SUPPLY CHAIN MANAGEMENT, 2024–2030 (USD THOUSAND)
  • TABLE 259 LATIN AMERICA: MARKET, BY MARKETING & PRICING MANAGEMENT, 2019–2023 (USD THOUSAND)
  • TABLE 260 LATIN AMERICA: MARKET, BY MARKETING & PRICING MANAGEMENT, 2024–2030 (USD THOUSAND)
  • TABLE 261 LATIN AMERICA: MARKET, BY VERTICAL, 2019–2023 (USD THOUSAND)
  • TABLE 262 LATIN AMERICA: MARKET, BY VERTICAL, 2024–2030 (USD THOUSAND)
  • TABLE 263 LATIN AMERICA: MARKET, BY COUNTRY, 2019–2023 (USD THOUSAND)
  • TABLE 264 LATIN AMERICA: MARKET, BY COUNTRY, 2024–2030 (USD THOUSAND)
  • TABLE 265 BRAZIL: MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 266 BRAZIL: MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 267 MEXICO: MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 268 MEXICO: MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 269 REST OF LATIN AMERICA: MARKET, BY OFFERING, 2019–2023 (USD THOUSAND)
  • TABLE 270 REST OF LATIN AMERICA: MARKET, BY OFFERING, 2024–2030 (USD THOUSAND)
  • TABLE 271 MARKET: DEGREE OF COMPETITION
  • TABLE 272 REGIONAL FOOTPRINT (12 COMPANIES)
  • TABLE 273 OFFERING FOOTPRINT (12 COMPANIES)
  • TABLE 274 APPLICATION FOOTPRINT (12 COMPANIES)
  • TABLE 275 VERTICAL FOOTPRINT (12 COMPANIES)
  • TABLE 276 CAUSAL AI MARKET: KEY STARTUPS/SMES
  • TABLE 277 MARKET: COMPETITIVE BENCHMARKING OF KEY STARTUPS/SMES
  • TABLE 278 MARKET: PRODUCT LAUNCHES & ENHANCEMENTS, OCTOBER 2022– MAY 2024
  • TABLE 279 MARKET: DEALS, SEPTEMBER 2023–OCTOBER 2024
  • TABLE 280 GOOGLE: COMPANY OVERVIEW
  • TABLE 281 GOOGLE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 282 GOOGLE: PRODUCT LAUNCHES & ENHANCEMENTS
  • TABLE 283 GOOGLE: DEALS
  • TABLE 284 IBM: COMPANY OVERVIEW
  • TABLE 285 IBM: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 286 IBM: PRODUCT LAUNCHES & ENHANCEMENTS
  • TABLE 287 MICROSOFT: COMPANY OVERVIEW
  • TABLE 288 MICROSOFT: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 289 MICROSOFT: PRODUCT LAUNCHES & ENHANCEMENTS
  • TABLE 290 DYNATRACE: COMPANY OVERVIEW
  • TABLE 291 DYNATRACE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 292 DYNATRACE: PRODUCT LAUNCHES & ENHANCEMENTS
  • TABLE 293 DYNATRACE: DEALS
  • TABLE 294 COGNIZANT: COMPANY OVERVIEW
  • TABLE 295 COGNIZANT: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 296 COGNIZANT: PRODUCT LAUNCHES & ENHANCEMENTS
  • TABLE 297 LOGILITY: COMPANY OVERVIEW
  • TABLE 298 LOGILITY: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 299 LOGILITY: DEALS
  • TABLE 300 DATAROBOT: COMPANY OVERVIEW
  • TABLE 301 DATAROBOT: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 302 CAUSALENS: COMPANY OVERVIEW
  • TABLE 303 CAUSALENS: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 304 CAUSALENS: PRODUCT LAUNCHES & ENHANCEMENTS
  • TABLE 305 CAUSALENS: DEALS
  • TABLE 306 CAUSALITY LINK: COMPANY OVERVIEW
  • TABLE 307 CAUSALITY LINK: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 308 CAUSALITY LINK: PRODUCT LAUNCHES & ENHANCEMENTS
  • TABLE 309 CAUSALITY LINK: DEALS
  • TABLE 310 TASKADE: COMPANY OVERVIEW
  • TABLE 311 TASKADE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 312 TASKADE: PRODUCT LAUNCHES & ENHANCEMENTS
  • TABLE 313 ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2019–2023 (USD BILLION)
  • TABLE 314 ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2024–2030 (USD BILLION)
  • TABLE 315 ARTIFICIAL INTELLIGENCE MARKET, BY BUSINESS FUNCTION, 2019–2023 (USD BILLION)
  • TABLE 316 ARTIFICIAL INTELLIGENCE MARKET, BY BUSINESS FUNCTION, 2024–2030 (USD BILLION)
  • TABLE 317 ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2019–2023 (USD BILLION)
  • TABLE 318 ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2024–2030 (USD BILLION)
  • TABLE 319 ARTIFICIAL INTELLIGENCE MARKET, BY VERTICAL, 2019–2023 (USD BILLION)
  • TABLE 320 ARTIFICIAL INTELLIGENCE MARKET, BY VERTICAL, 2024–2030 (USD BILLION)
  • TABLE 321 ARTIFICIAL INTELLIGENCE MARKET, BY REGION, 2019–2023 (USD BILLION)
  • TABLE 322 ARTIFICIAL INTELLIGENCE MARKET, BY REGION, 2024–2030 (USD BILLION)
  • TABLE 323 AI GOVERNANCE MARKET, BY PRODUCT TYPE, 2019–2023 (USD MILLION)
  • TABLE 324 AI GOVERNANCE MARKET, BY PRODUCT TYPE, 2024–2029 (USD MILLION)
  • TABLE 325 AI GOVERNANCE MARKET, BY FUNCTIONALITY, 2019–2023 (USD MILLION)
  • TABLE 326 AI GOVERNANCE MARKET, BY FUNCTIONALITY, 2024–2029 (USD MILLION)
  • TABLE 327 AI GOVERNANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 328 AI GOVERNANCE MARKET, BY END USER, 2024–2029 (USD MILLION)
  • TABLE 329 AI GOVERNANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 330 AI GOVERNANCE MARKET, BY REGION, 2024–2029 (USD MILLION)
LIST OF FIGURES
 
  • FIGURE 1 MARKET: RESEARCH DESIGN
  • FIGURE 2 DATA TRIANGULATION
  • FIGURE 3 CAUSAL AI MARKET: TOP-DOWN AND BOTTOM-UP APPROACHES
  • FIGURE 4 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 1, BOTTOM-UP (SUPPLY-SIDE): REVENUE FROM PRODUCT TYPES OF CAUSAL AI MARKET
  • FIGURE 5 MARKET SIZE ESTIMATION METHODOLOGY- APPROACH 2, BOTTOM-UP (SUPPLY-SIDE): COLLECTIVE REVENUE FROM ALL PRODUCT TYPES OF MARKET
  • FIGURE 6 MARKET SIZE ESTIMATION METHODOLOGY-APPROACH 3, BOTTOM-UP (SUPPLY-SIDE): COLLECTIVE REVENUE FROM ALL PRODUCT TYPES OF MARKET
  • FIGURE 7 MARKET SIZE ESTIMATION METHODOLOGY-APPROACH 4, BOTTOM-UP (DEMAND-SIDE): SHARE OF CAUSAL AI THROUGH OVERALL AI SPENDING
  • FIGURE 8 SOFTWARE TO BECOME LARGER OFFERING BY MARKET SIZE IN 2024
  • FIGURE 9 CAUSAL AI PLATFORMS TO HOLD LARGER SHARE IN 2024
  • FIGURE 10 CAUSAL DISCOVERY SOFTWARE SEGMENT TO LEAD WITHIN CAUSAL AI SOLUTIONS IN 2024
  • FIGURE 11 CONSULTING SERVICES TO ACCOUNT FOR MAJORITY MARKET SHARE IN 2024
  • FIGURE 12 FINANCIAL MANAGEMENT TO EMERGE AS LARGEST APPLICATION SEGMENT IN 2024
  • FIGURE 13 HEALTHCARE & LIFE SCIENCES TO BE FASTEST-GROWING END USER SEGMENT DURING FORECAST PERIOD
  • FIGURE 14 ASIA PACIFIC TO REGISTER FASTEST GROWTH RATE DURING FORECAST PERIOD
  • FIGURE 15 DEMAND FOR EXPLAINABLE AND ACTIONABLE INSIGHTS IN REGULATED INDUSTRIES TO FUEL MARKET
  • FIGURE 16 MARKETING & PRICING MANAGEMENT SEGMENT TO ACCOUNT FOR HIGHEST GROWTH RATE DURING FORECAST PERIOD
  • FIGURE 17 FINANCIAL MANAGEMENT AND BFSI TO BE LARGEST SHAREHOLDERS IN NORTH AMERICA IN 2024
  • FIGURE 18 NORTH AMERICA TO HOLD LARGEST MARKET SHARE IN 2024
  • FIGURE 19 DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES: CAUSAL AI MARKET
  • FIGURE 20 EVOLUTION OF CAUSAL AI
  • FIGURE 21 CAUSAL AI MARKET: SUPPLY CHAIN ANALYSIS
  • FIGURE 22 KEY PLAYERS IN MARKET ECOSYSTEM
  • FIGURE 23 MARKET: INVESTMENT LANDSCAPE AND FUNDING SCENARIO (USD MILLION AND NUMBER OF FUNDING ROUNDS)
  • FIGURE 24 IMPACT OF GENERATIVE AI IN VARIOUS CAUSAL AI USE CASES
  • FIGURE 25 NUMBER OF PATENTS GRANTED IN LAST 10 YEARS, 2015–2024
  • FIGURE 26 REGIONAL ANALYSIS OF PATENTS GRANTED, 2015–2024
  • FIGURE 27 CAUSAL AI MARKET: PORTER’S FIVE FORCES ANALYSIS
  • FIGURE 28 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE END USERS
  • FIGURE 29 KEY BUYING CRITERIA FOR TOP THREE END USERS
  • FIGURE 30 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
  • FIGURE 31 SERVICES SEGMENT TO GROW AT HIGHER CAGR DURING FORECAST PERIOD
  • FIGURE 32 CAUSAL AI PLATFORM SEGMENT TO HOLD LARGER MARKET SIZE IN 2024
  • FIGURE 33 CONSULTING SERVICES SEGMENT TO HOLD LARGEST MARKET SIZE IN 2024
  • FIGURE 34 MARKETING & PRICING MANAGEMENT SEGMENT TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
  • FIGURE 35 HEALTHCARE & LIFE SCIENCES SEGMENT TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
  • FIGURE 36 INDIA TO ACCOUNT FOR HIGHEST CAGR DURING FORECAST PERIOD
  • FIGURE 37 ASIA PACIFIC TO ACCOUNT FOR HIGHEST CAGR DURING FORECAST PERIOD
  • FIGURE 38 NORTH AMERICA: CAUSAL AI MARKET SNAPSHOT
  • FIGURE 39 ASIA PACIFIC: MARKET SNAPSHOT
  • FIGURE 40 OVERVIEW OF STRATEGIES ADOPTED BY KEY CAUSAL AI VENDORS
  • FIGURE 41 TOP FIVE PLAYERS DOMINATING MARKET OVER LAST FIVE YEARS
  • FIGURE 42 SHARE OF LEADING COMPANIES IN CAUSAL AI MARKET, 2023
  • FIGURE 43 PRODUCT COMPARATIVE ANALYSIS
  • FIGURE 44 COMPANY VALUATION AND FINANCIAL METRICS OF KEY VENDORS
  • FIGURE 45 YEAR-TO-DATE (YTD) PRICE TOTAL RETURN AND 5-YEAR STOCK BETA OF KEY VENDORS
  • FIGURE 46 MARKET: COMPANY EVALUATION MATRIX (KEY PLAYERS), 2023
  • FIGURE 47 COMPANY FOOTPRINT (12 COMPANIES)
  • FIGURE 48 CAUSAL AI MARKET: COMPANY EVALUATION MATRIX (STARTUPS/SMES), 2023
  • FIGURE 49 GOOGLE: COMPANY SNAPSHOT
  • FIGURE 50 IBM: COMPANY SNAPSHOT
  • FIGURE 51 MICROSOFT: COMPANY SNAPSHOT
  • FIGURE 52 DYNATRACE: COMPANY SNAPSHOT
  • FIGURE 53 COGNIZANT: COMPANY SNAPSHOT
  • FIGURE 54 LOGILITY: COMPANY SNAPSHOT

 

The research methodology for the global Causal AI market report involved the use of extensive secondary sources and directories, as well as various reputed open-source databases, to identify and collect information useful for this technical and market-oriented study. In-depth interviews were conducted with various primary respondents, including key opinion leaders, subject matter experts on causal inference, causal modelling and causal discovery, high-level executives of multiple companies offering Causal AI, and industry consultants to obtain and verify critical qualitative and quantitative information and assess the market prospects and industry trends.

Secondary Research

In the secondary research process, various secondary sources were referred to for identifying and collecting information for the study. The secondary sources included annual reports; press releases and investor presentations of companies; white papers, certified publications such as Journal of Big Data, Journal of Artificial Intelligence Research, Data & Knowledge Engineering (DKE) Journal, Big Data and Cognitive Computing Journal, International Journal of Data Science and Analytics, and International Journal of Advances in Intelligent Informatics; and articles from recognized associations and government publishing sources including but not limited to AI Global, Global Initiative on Ethics of Autonomous and Intelligent Systems, Global Partnership on Artificial Intelligence, The Responsible AI Institute, European AI Alliance, AI for Good (United Nations), and World Economic Forum’s Whitepaper on Future of Mobility and Big Data.

The secondary research was used to obtain key information about the industry’s value chain, the market’s monetary chain, the overall pool of key players, market classification and segmentation according to industry trends to the bottom-most level, regional markets, and key developments from the market and technology-oriented perspectives.

Primary Research

In the primary research process, a diverse range of stakeholders from both the supply and demand sides of the Causal AI ecosystem were interviewed to gather qualitative and quantitative insights specific to this market. From the supply side, key industry experts, such as chief executive officers (CEOs), vice presidents (VPs), marketing directors, technology & innovation directors, as well as technical leads from vendors offering Causal AI were consulted. Additionally, system integrators, service providers, and IT service firms that implement and support Causal AIs were included in the study. On the demand side, input from IT decision-makers, infrastructure managers, and AI/data analytics heads was collected to understand the user perspectives and adoption challenges within targeted industries.

The primary research ensured that all crucial parameters affecting the Causal AI market—from technological advancements and evolving use cases (financial management, marketing & pricing management, operations & supply chain management, etc.) to regulatory and compliance needs (GDPR, EU AI Act, California Consumer Privacy Act etc.)—were considered. Each factor was thoroughly analyzed, verified through primary research, and evaluated to obtain precise quantitative and qualitative data for this market.

Once the initial phase of market engineering was completed, including detailed calculations for market statistics, segment-specific growth forecasts, and data triangulation, an additional round of primary research was undertaken. This step was crucial for refining and validating critical data points, such as Causal AI offerings (causal AI platforms, causal discovery tools, causal modelling tools, causal inference tools, root cause analysis tools, and causal AI services), industry adoption trends, the competitive landscape, and key market dynamics like demand drivers (increasing demand for explainable AI in regulated industries, growing demand for robust counterfactual analysis, surge in demand for predictive maintenance and root cause analysis, shift from predictive analytics to causal AI-based prescriptive analytics), challenges (lack of standardized tools and frameworks for causal inference, high computational costs for causal modeling), and opportunities (Causal AI in precision healthcare and drug discovery, scalable causal inference APIs for real-time applications, integrating causal AI with IoT for real-time decision making.)

In the complete market engineering process, the top-down and bottom-up approaches and several data triangulation methods were extensively used to perform the market estimation and market forecast for the overall market segments and subsegments listed in this report. Extensive qualitative and quantitative analysis was performed on the complete market engineering process to record the critical information/insights throughout the report.

Causal AI Market Size, and Share

Note: Three tiers of companies are defined based on their total revenue as of 2023; tier 1 = revenue more
than USD 500 million, tier 2 = revenue between USD 100 million and 500 million, tier 3 = revenue less
than USD 100 million Source: MarketsandMarkets Analysis

To know about the assumptions considered for the study, download the pdf brochure

Market Size Estimation

To estimate and forecast the Causal AI market and its dependent submarkets, both top-down and bottom-up approaches were employed. This multi-layered analysis was further reinforced through data triangulation, incorporating both primary and secondary research inputs. The market figures were also validated against the existing MarketsandMarkets repository for accuracy. The following research methodology has been used to estimate the market size:

Causal AI Market : Top-Down and Bottom-Up Approach

Causal AI Market Top Down and Bottom Up Approach

Data Triangulation

After arriving at the overall market size using the market size estimation processes as explained above, the market was split into several segments and subsegments. To complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment, data triangulation and market breakup procedures were employed, wherever applicable. The overall market size was then used in the top-down procedure to estimate the size of other individual markets via percentage splits of the market segmentation.

Market Definition

Causal AI focuses on understanding and modeling cause-and-effect relationships within data to move beyond correlation-based predictions. By employing techniques like causal discovery, intervention analysis, and counterfactual reasoning, it enables AI systems to simulate interventions, predict outcomes, and make robust, explainable decisions even in novel or shifting environments. Rooted in principles of causal inference and structural causal models, Causal AI enhances generalization, fairness, and transparency while providing actionable insights. It has wide-ranging applications in healthcare, finance, marketing, and AI ethics to create adaptive and trustworthy AI systems.

Stakeholders

  • Causal AI platform vendors
  • Root cause analysis software vendors
  • Causal AI service providers
  • Causal inferencing software providers
  • Causal discovery software providers
  • Causal modelling software providers
  • Business analysts
  • Cloud service providers
  • Enterprise end-users
  • Distributors and Value-added Resellers (VARs)
  • Government agencies
  • Independent Software Vendors (ISV)
  • Market research and consulting firms
  • AI technology providers

Report Objectives

  • To define, describe, and predict the Causal AI market by offering, application, and region
  • To provide detailed information related to major factors (drivers, restraints, opportunities, and industry-specific challenges) influencing the market growth
  • To analyze the micro markets with respect to individual growth trends, prospects, and their contribution to the total market
  • To analyze the opportunities in the market for stakeholders by identifying the high-growth segments of the Causal AI market
  • To analyze opportunities in the market and provide details of the competitive landscape for stakeholders and market leaders
  • To forecast the market size of segments for five main regions: North America, Europe, Asia Pacific, Middle East Africa, and Latin America
  • To profile key players and comprehensively analyze their market rankings and core competencies.
  • To analyze competitive developments, such as partnerships, new product launches, and mergers and acquisitions, in the Causal AI market
  • To analyze the impact of recession across all the regions across the Causal AI market

Available Customizations

With the given market data, MarketsandMarkets offers customizations as per the company’s specific needs. The following customization options are available for the report:

Product Analysis

  • Product matrix provides a detailed comparison of the product portfolio of each company

Geographic Analysis as per Feasibility

  • Further breakup of the North American market for Causal AI
  • Further breakup of the European market for Causal AI
  • Further breakup of the Asia Pacific market for Causal AI
  • Further breakup of the Latin American market for Causal AI
  • Further breakup of the Middle East & Africa market for Causal AI

Company Information

  • Detailed analysis and profiling of additional market players (up to five)

Previous Versions of this Report

Causal AI Market by Offering (Causal AI Platforms, Causal Discovery, Causal Inference, Causal Modelling, Root Cause Analysis), Application (Financial Management, Sales & Customer Management, Operations & Supply Chain Management) - Global Forecast to 2030

Report Code TC 8644
Published in May, 2023, By MarketsandMarkets™
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