Causal AI Market worth $3,488.66 million by 2030, growing at a CAGR of 31.47% - Exclusive Report by 360iResearch

The Global Causal AI Market to grow from USD 390.66 million in 2022 to USD 3,488.66 million by 2030, at a CAGR of 31.47%.

PUNE, MAHARASHTRA, INDIA, November 15, 2023 /EINPresswire.com/ -- The "Causal AI Market by Offering (Platform, Services), Deployment (Cloud, On-Premise), Vertical - Global Forecast 2023-2030" report has been added to 360iResearch.com's offering.

The Global Causal AI Market to grow from USD 390.66 million in 2022 to USD 3,488.66 million by 2030, at a CAGR of 31.47%.

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Causal AI includes advanced artificial intelligence technologies that enable machines to understand causal relationships within complex systems. This cutting-edge technology is aimed at improving decision-making processes by providing more accurate predictions and insights based on cause-and-effect reasoning. Increasing demand for better predictive analytics across industries to make data-driven decisions in a competitive landscape is expanding the usage of causal AI models to make more informed decisions. The growing availability of large-scale data sets combined with advancements in computational power has enabled researchers and developers to create more sophisticated machine learning algorithms that handle complex causal relationships. As technologies continue to improve and become more accessible, the adoption rate of causal AI solutions is increasing rapidly. The complexity involved in developing accurate models capable of identifying genuine causality from mere correlation within vast amounts of data hampers market growth. Growing technological advancements in the development of causal AI models, which help to identify cause-and-effect relationships within large amounts of data, are expected to create opportunities for market growth.

Deployment: Increasing adoption of cloud-based causal AI due to its cost-effectiveness, and quicker implementation
Cloud-based causal AI solutions are gaining traction due to their scalability, ease of access, and reduced upfront costs. These solutions are ideal for businesses seeking flexibility in managing resources and quick implementation. On-premises causal AI solutions cater to organizations that prioritize data security, control, and customization. These solutions are often preferred by companies in regulated industries, such as finance and healthcare, where strict data privacy regulations require businesses to store and process sensitive information on their premises. Cloud deployment offers scalability, accessibility, cost-effectiveness, and quicker implementation compared to on-premises options. However, it may not be suitable for businesses with strict data privacy requirements or those seeking extensive customization of their AI infrastructure. On the other hand, on-premises deployment provides greater control over data security and system customization while adhering to compliance regulations but requires higher upfront investment and longer implementation times.

Vertical: Growing utilization of causal AI by the healthcare and life science industry for diagnosis and drug development
The banking, financial services & insurance sector is increasingly adopting Causal AI for fraud detection, risk management, and client service improvement. Causal AI has been revolutionizing the healthcare and lifesciences sectors through personalized treatment plans, drug discovery, and early disease diagnosis. In the manufacturing sector, Causal AI has been instrumental in optimizing supply chain processes, improving production efficiency through predictive maintenance and enabling smart factory transformation. Retailers and e-commerce platforms leverage Causal AI to enhance customer experiences by offering personalized recommendations, optimizing pricing strategies, and managing inventory. Transportation and logistics industries benefit from Causal AI in optimizing route planning, predicting vehicle maintenance requirements, and improving warehouse operations. The adoption of Causal AI across various verticals is transforming businesses through improved efficiency, cost savings, and enhanced decision-making capabilities.

Offering: Expanding usage of platforms as it offers a higher degree of control over model development
Platforms provide a comprehensive set of tools and functionalities that enable users to develop, deploy, and manage complex Causal AI models. These platforms offer various features such as data preprocessing, model development, visualization tools, and integration with existing systems. Services are provided by specialized causal AI consulting firms and vendors that offer customized solutions tailored to clients' specific needs. These services range from advising on causal modeling strategies to full-scale implementation of end-to-end causal AI solutions

Regional Insights:
The Americas continues to witness robust demand for causal AI solutions as an AI innovation with Silicon Valley at its core. The region is characterized by a strong appetite for technology adoption among businesses and research institutions. Moreover, governments in North America have been actively supporting AI research programs with substantial funding and incentives that further bolster the demand for causal AI technologies. Europe is fast becoming another crucial region in the global causal AI landscape due to its advanced digital infrastructure and ongoing investments in R&D initiatives. The European Commission's significant investments in artificial intelligence projects demonstrate governmental support towards making Europe an AI powerhouse. In Africa and Middle East regions, there is burgeoning interest in leveraging big data analytics and machine learning capabilities within their economies; however, they require overcoming limited skill sets or inadequate resource challenges. The causal AI market in the APAC region has an exponential growth potential. China shows this region as one of the global frontrunners in AI research, backed by the Chinese government's ambitious plan to become an AI superpower. Industrialized nations, including Japan and Singapore, are also investing heavily in AI adoption, focusing on areas such as robotics, autonomous vehicles, and healthcare. Meanwhile, emerging markets such as India and Southeast Asia present unique opportunities for causal AI implementation due to their large population size and rapidly evolving technology landscape.

FPNV Positioning Matrix:

The FPNV Positioning Matrix is essential for assessing the Causal AI Market. It provides a comprehensive evaluation of vendors by examining key metrics within Business Strategy and Product Satisfaction, allowing users to make informed decisions based on their specific needs. This advanced analysis then organizes these vendors into four distinct quadrants, which represent varying levels of success: Forefront (F), Pathfinder (P), Niche (N), or Vital(V).

Market Share Analysis:

The Market Share Analysis offers an insightful look at the current state of vendors in the Causal AI Market. By comparing vendor contributions to overall revenue, customer base, and other key metrics, we can give companies a greater understanding of their performance and what they are up against when competing for market share. The analysis also sheds light on just how competitive any given sector is about accumulation, fragmentation dominance, and amalgamation traits over the base year period studied.

Key Company Profiles:

The report delves into recent significant developments in the Causal AI Market, highlighting leading vendors and their innovative profiles. These include Accenture PLC, Amazon Web Services, Inc., BigML, Inc., BMC Software, Inc., Causality Link LLC, cognino.ai, Cognizant Technology Solutions Corporation, Databricks, Inc, Dynatrace LLC, EXPERT.AI, Fair Isaac Corporation, Geminos Software, Google LLC by Alphabet Inc., Hewlett Packard Enterprise Development LP, Impulse Innovations Limited (causaLens), INCRMNTAL Ltd., Infosys Limited, Intel Corporation, International Business Machines Corporation, Kyndryl Inc., Logility, Microsoft Corporation, Oracle Corporation, Parabole.ai, Salesforce, Inc., SAP SE, SCALNYX, and Xplain Data GmbH.

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Market Segmentation & Coverage:

This research report categorizes the Causal AI Market in order to forecast the revenues and analyze trends in each of following sub-markets:

Based on Offering, market is studied across Platform and Services. The Services is further studied across Consulting Services, Deployment & Integration, and Training, Support, and Maintenance. The Platform is projected to witness significant market share during forecast period.

Based on Deployment, market is studied across Cloud and On-Premise. The Cloud is projected to witness significant market share during forecast period.

Based on Vertical, market is studied across Banking, Financial Services & Insurance, Healthcare & Lifesciences, Manufacturing, Retail & eCommerce, and Transportation & Logistics. The Manufacturing is projected to witness significant market share during forecast period.

Based on Region, market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom. The Americas commanded largest market share of 39.09% in 2022, followed by Europe, Middle East & Africa.

Key Topics Covered:

1. Preface
2. Research Methodology
3. Executive Summary
4. Market Overview
5. Market Insights
6. Causal AI Market, by Offering
7. Causal AI Market, by Deployment
8. Causal AI Market, by Vertical
9. Americas Causal AI Market
10. Asia-Pacific Causal AI Market
11. Europe, Middle East & Africa Causal AI Market
12. Competitive Landscape
13. Competitive Portfolio
14. Appendix

The report provides insights on the following pointers:
1. Market Penetration: Provides comprehensive information on the market offered by the key players
2. Market Development: Provides in-depth information about lucrative emerging markets and analyzes penetration across mature segments of the markets
3. Market Diversification: Provides detailed information about new product launches, untapped geographies, recent developments, and investments
4. Competitive Assessment & Intelligence: Provides an exhaustive assessment of market shares, strategies, products, certification, regulatory approvals, patent landscape, and manufacturing capabilities of the leading players
5. Product Development & Innovation: Provides intelligent insights on future technologies, R&D activities, and breakthrough product developments

The report answers questions such as:
1. What is the market size and forecast of the Causal AI Market?
2. Which are the products/segments/applications/areas to invest in over the forecast period in the Causal AI Market?
3. What is the competitive strategic window for opportunities in the Causal AI Market?
4. What are the technology trends and regulatory frameworks in the Causal AI Market?
5. What is the market share of the leading vendors in the Causal AI Market?
6. What modes and strategic moves are considered suitable for entering the Causal AI Market?

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Mr. Ketan Rohom
360iResearch
+ 1 530-264-8485
[email protected]