What is a Predictive AI?

Predictive AI is an umbrella term encompassing artificial intelligence techniques specifically designed for predicting future events or trends based on data analysis and pattern recognition. It involves the use of machine learning algorithms to make informed predictions.

How big is Predictive AI Market?

The net revenue generated by the global Predictive AI Market in 2023 was nearly USD 14.9 Billion . Over the next ten years, the Predictive AI industry is expected to surge at 21.9% CAG R, concluding at a valuation of USD 108.0 Billion by 2033 . Projected to Reach at a USD 18.2 Billion in 2024.

Who are the key companies/players in the Predictive AI Market?

Some key players operating in the Predictive AI Market include IBM Corporation, SAS Institute Inc., Microsoft Corporation, SAP SE, Oracle Corporation, Salesforce.com Inc., Alteryx, Inc., RapidMiner Inc., Statistica (Dell Technologies), TIBCO Software Inc., MathWorks Inc., KNIME AG, Other Key Players

What industries benefit the most from Predictive AI solutions?

Predictive AI finds applications across various industries, including finance, healthcare, e-commerce, and manufacturing. It is particularly beneficial for industries that rely on data-driven decision-making and want to anticipate future trends or behaviors.

What is the Difference Between Predictive AI and Generative AI?

Predictive AI focuses on forecasting future outcomes based on historical data, while generative AI is designed to generate new content, such as images, text, or music, often without direct human input. They serve different purposes in terms of prediction and creation.

What Are the Key Benefits of Using Predictive AI in Business?

The key benefits of employing Predictive AI in business include: Informed Decision-Making: Provides actionable insights for strategic decision-making. Risk Mitigation: Helps identify and mitigate potential risks based on predictive analysis. Efficient Operations: Optimizes business processes by anticipating future trends and demands. Personalized Marketing: Enables targeted and personalized marketing strategies. Cost Savings: Predictive AI can lead to cost efficiencies by optimizing resource allocation.

What challenges are associated with implementing Predictive AI in a business setting?

Challenges may include data quality issues, the need for large and diverse datasets, interpretability of models, and ethical considerations. Overcoming these challenges is crucial for successful implementation.

Global Predictive AI Market By Deployment Model (On-Premises, Cloud-Based), By Solution (Software (Time Series Analysis, Regression Analysis, Classification and Categorization, Clustering, Others), Services (Consulting, Implementation, Support and Maintenance)), By Application (Financial Forecasting, Sales and Marketing, Risk Management, Supply Chain Management, Fraud Detection and Security, Other Applications), By Technology (Machine Learning, Natural Language Processing (NLP), Deep Learning, Other Technologies), By Organization Size (Large Enterprises, Small and Medium-sized Enterprises (SMEs)), By End-User Industry (BFSI, Healthcare, Retail and E-commerce, Manufacturing, Telecommunications and Others), By Region, and Key Companies - Industry Segment Outlook, Market Assessment, Competition Scenario, Trends and Forecast 2024-2033

Published date: March 2024
Report ID: 112622
Number of Pages: 301
Format:

- IBM Corporation
- SAS Institute Inc.
- Microsoft Corporation Company Profile
- SAP SE Company Profile
- Oracle Corporation
- Salesforce.com Inc.
- Alteryx, Inc.
- RapidMiner Inc.
- Statistica (Dell Technologies)
- TIBCO Software Inc.
- MathWorks Inc.
- KNIME AG
- Other Key Players