Richmond, Dec. 19, 2023 (GLOBE NEWSWIRE) -- According to a research report "Causal AI Market”, by Offering (Platform and Services {Consulting Services, Deployment & Integration, Training, Support, and Maintenance}), Deployment (Cloud, On-premises), End-user Industry (Healthcare & Lifesciences, BFSI, Retail & e-commerce, Transportation & Logistics, Manufacturing, Other Verticals), and Region - Global Forecast to 2030".
Global Causal AI Market Report Scope:
| Report | Details |
| Market size value in 2023 | USD 30.0 Million |
| Market size value in 2030 | USD 359.7 Million |
| CAGR (2023-2030) | 42.6% |
| Forecast Period | 2023–2030 |
| Historic Data | 2019 |
| Forecast Units | Value (USD Million/USD Billion) |
| Segments Covered | Offering, Deployment, End User Industry and Region |
| Geographies Covered | North America, Europe, Asia Pacific, and RoW |
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| Sample of Companies Covered |
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TOC Covers in Depth & Breath on Causal AI Market
170 - Market Data Tables
65 - List of Figures
225 – Pages
The report includes Vendor Assessment (Company Profiles, Market Positioning, Strategies, Recent Developments, Capabilities & Product Offerings / Mapping), Technology Assessment (Developments & Economic Impact), Partner & Customer Ecosystem (Product Services, Proposition & Key Features) Competitive Index & Regional FootPrint by MarketDigits.
Market Overview
The global Causal AI market presents a dynamic landscape driven by the escalating demand for advanced artificial intelligence solutions. Causal AI, or Causal Inference, involves the study of cause-and-effect relationships within data, enabling businesses to derive actionable insights and make informed decisions. The market is propelled by the increasing adoption of AI across diverse industries, including finance, healthcare, retail, and manufacturing, among others. The significant factors driving the market is the growing recognition of the limitations of traditional machine learning models in understanding causal relationships. Causal AI addresses this gap by focusing on understanding the cause-and-effect dynamics in data, providing a more accurate and interpretable approach to decision-making. The market is characterized by innovations and advancements in AI algorithms, with companies investing in research and development to enhance the capabilities of Causal AI models. As businesses increasingly recognize the value of understanding causal relationships in data, the adoption of Causal AI is expected to witness substantial growth. Furthermore, the global Causal AI market is poised for expansion as businesses seek more nuanced and accurate insights from their data. The market dynamics are shaped by a growing awareness of the limitations of traditional AI approaches, coupled with the increasing recognition of the importance of causal relationships in decision-making across various industries.
Major vendors in the global Causal AI Market:-
- IBM
- CausaLens
- Microsoft
- Causaly
- Geminos
- AWS (Amazon Web Services)
- Aitia
- Xplain Data
- INCRMNTAL
- Logility
- Cognino.ai
- H2O.ai
- DataRobot
- Cognizant
- Scalnyx
- Causality Link
- Dynatrace
- Parabole.ai
- Datma
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Advancements in Causal Inference Algorithms
Rising The continuous advancements in Causal Inference algorithms serve as a significant driver for the Global Causal AI Market. As researchers and data scientists delve deeper into developing sophisticated algorithms for causal modeling, the capabilities of Causal AI are expanding. These advancements enable the identification of complex causal relationships within large datasets, leading to more accurate predictions and informed decision-making. The evolution of algorithms that can handle non-linear relationships and account for confounding variables further enhances the applicability of Causal AI across diverse industries, fostering its adoption for a wide range of use cases.
Market Dynamics
Drivers:
- Increasing Demand for Explainable AI
- Advancements in Causal Inference Algorithms
- Growing Awareness of Causal Inference Benefits
Opportunities:
- Healthcare Optimization and Personalized Medicine
- Financial Risk Management and Fraud Detection
- Supply Chain Optimization and Predictive Maintenance
Healthcare Optimization and Personalized Medicine
A significant market opportunity for Causal AI lies in healthcare optimization and personalized medicine. Causal AI's ability to discern cause-and-effect relationships within complex biological systems is crucial for understanding the impact of various factors on health outcomes. This creates opportunities for tailoring medical treatments and interventions based on an individual's unique characteristics and response patterns. Healthcare providers can leverage Causal AI to optimize treatment plans, predict patient responses, and identify personalized therapeutic approaches. As the healthcare industry continues to embrace data-driven decision-making, the adoption of Causal AI for personalized medicine is poised to revolutionize patient care and treatment strategies.
The market for Causal AI is dominated by North America.
In 2023, North America plays pivotal role in propelling the evolution and progress of Causal AI. The increasing prominence of Causal AI stems from the growing demand among businesses and organizations for advanced analytics solutions that enable profound insights and informed decision-making. Governments in North America, notably in the United States and Canada, have instituted initiatives aimed at fostering the growth and acceptance of AI. These initiatives involve allocating funding and resources to support research and innovation endeavors in the AI domain. In the United States, the National Institute of Standards and Technology (NIST) has been actively engaged in formulating standards and guidelines pertinent to AI applications across diverse industries, including healthcare and finance. This concerted effort underscores the commitment to establishing a framework that promotes responsible and effective utilization of AI technologies, further solidifying North America's position as a driving force in the realm of Causal AI.
The Causal AI market is experiencing robust growth worldwide, with Asia Pacific emerging as the fastest-growing region after the dominant North America. The Asia Pacific region, encompassing countries like China, Japan, and India, is emerging as a key player in the Causal AI market. Rapid technological advancements, increasing digitization, and a focus on AI-driven innovation contribute to the growing adoption of Causal AI in the region. Industries such as e-commerce, finance, and healthcare are leveraging Causal AI to gain a competitive edge and address complex business challenges.
The cloud segment is anticipated to hold the largest market share during the forecast period
Based on deployment the market is divided into cloud and on-premises. The cloud-based deployment model offers organizations a versatile, scalable, and economical approach to leverage potent causal inference tools. This deployment model empowers organizations to adjust their resources seamlessly, whether scaling up or down, without requiring substantial upfront investments in hardware or software. Cloud-based causal AI platforms enhance accessibility, permitting users to connect from anywhere with an internet connection, facilitating remote collaboration and data sharing. Furthermore, this deployment model alleviates the burden on organizations to handle and sustain their hardware infrastructure, resulting in reduced IT resources and costs. Cloud providers commonly furnish robust security and compliance features, assuring the safeguarding of data security and privacy.
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