Causal AI Market is expected to develop at a USD 543.73 Million by 2032 | Riding on a Strong 40.3% CAGR

The global causal AI market size is expected to reach USD 543.73 million by 2032, according to a new study by Polaris Market Research. The report “Causal AI Market Share, Size, Trends, Industry Analysis Report, By Offering (Platform, Cloud, On-premises, Services); By Vertical; By Region; Segment Forecast, 2023 – 2032” gives a detailed insight into current market dynamics and provides analysis on future market growth.

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The growing adoption and utilization of big data analytics drive the market’s growth. The proliferation of data has created a need for advanced analytics techniques to extract valuable insights. Causal AI techniques can uncover causal relationships within large datasets, helping businesses identify hidden patterns and make more accurate predictions. The latest Worldwide Big Data and Analytics (BDA) Spending Guide from International Data Corporation (IDC) predicts that Australia and New Zealand (ANZ) will spend USD 8.9 Million on BDA solutions over the five years between 2021 and 2026, growing at a compound annual growth rate of 13.3%. In 2022, these expenses are expected to total USD 5.5 Million. The growing prominence of big data analytics drives the demand for causal AI. By combining the power of big data analytics with causal AI techniques, organizations can unlock deeper insights, improve decision-making, address the limitations of correlation-based analyses, and achieve more accurate predictions and actionable outcomes.

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An increase in company funding is fuelling the research and development activities in the Causal AI field. CausaLens, a company specializing in Causal AI, has successfully raised USD 45 million in a Series A funding round in 2022. Molten Ventures and Dorilton Ventures took the lead in the funding round. This substantial investment will empower causaLens to expand its operations and bring the remarkable advantages of Causal AI to organizations across various sectors and geographical regions. The funding will support the company’s efforts in advancing the adoption and application of Causal AI, enabling businesses to leverage its transformative capabilities for improved decision-making and insights.

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Causal AI Market Report Highlights

  • Platform segment is anticipated to witness faster growth in the coming years due to the growing need for data integration and preprocessing.
  • Healthcare & Life Sciences segment accounted for the larger market share owing to the complex healthcare challenges, growing demand for precision medicine and personalized care.
  • APAC is projected to register a higher growth rate in the study period owing to the rise in the AI adoption rate in healthcare, retail, BFSI, industrial and automation sectors.
  • North America is expected to grow larger revenue share owing to the growing investments in computational technology.
  • The global players include OpenAI, Google, Microsoft, Amazon, IBM, Facebook, Apple, Baidu, Salesforce, NVIDIA, Intel, Tencent, Alibaba, Huawei, Samsung, Oracle, SAP, Adobe, Twitter, Lyft, Uber, Pinterest, Netflix, Spotify, Airbnb, Dropbox, Slack, Zoom, TikTok, Snapchat, WeChat, Attivio, Ayasdi, Clarifai, Descartes Labs, Indico, Anki & iCarbonX.

Key Features and Drivers:

Causal Inference and Prediction:
Causal AI algorithms leverage sophisticated statistical and machine learning techniques to infer causal relationships from observational data, experimental data, or a combination of both. By identifying causal factors and predicting outcomes, organizations can gain deeper insights into complex systems and make data-driven decisions with greater confidence.

Decision Support and Optimization:
Causal AI enables organizations to optimize processes, strategies, and interventions by identifying the most influential variables and causal pathways that drive desired outcomes. This technology helps businesses prioritize actions, allocate resources effectively, and achieve desired goals by leveraging causal insights to inform decision-making.

Explainability and Interpretability:
Unlike black-box machine learning models that provide opaque predictions, causal AI models offer explainability and interpretability by revealing the underlying causal mechanisms and relationships between variables. This transparency enables stakeholders to understand the rationale behind predictions and trust the insights generated by the AI system.

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Applications:

Healthcare and Life Sciences:
Causal AI is used in healthcare and life sciences for clinical decision support, drug discovery, treatment optimization, and disease prevention. By analyzing patient data and biomedical research, causal AI helps healthcare providers identify risk factors, understand disease mechanisms, and personalize treatment plans for better patient outcomes.

Financial Services and Risk Management:
In the financial services industry, causal AI is applied to risk management, portfolio optimization, fraud detection, and customer segmentation. By analyzing financial data and market trends, causal AI helps financial institutions identify causal factors influencing market behavior, assess risk exposure, and make informed investment decisions.

Marketing and Customer Analytics:
Causal AI enables marketers to understand the drivers of customer behavior, predict purchase decisions, and optimize marketing campaigns. By analyzing customer data and campaign metrics, causal AI helps marketers identify influential factors such as demographics, preferences, and promotional strategies that drive customer engagement and sales.

Polaris Market Research has segmented the causal AI market report based on offering, vertical and region:

Causal AIOffering Outlook (Revenue – USD Million, 2019 – 2032)

  • Platform
    • By Deployment
      • Cloud
      • On-premises
  • Services
    • Consulting Services
    • Deployment & Integration
    • Training, Support, and Maintenance

Causal AI, Vertical Outlook (Revenue – USD Million, 2019 – 2032)

  • Healthcare & Lifesciences
  • BFSI
  • Retail & eCommerce
  • Transportation & Logistics
  • Manufacturing
  • Other Verticals

Causal AI, Regional Outlook (Revenue – USD Million, 2019-2032)

  • North America
  • Europe
  • Asia Pacific
  • Latin America
  • Middle East & Africa

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