AI-Based Forecasting Market Size, Share, Opportunities, And Trends By Technology (Bayesian Network, Evolutionary Algorithms, Deep Learning), By End Users (Manufacturing, Healthcare, Retail, Agriculture, Others), And By Geography - Forecasts From 2024 To 2029

The AI-based forecasting market is expected to grow at a CAGR of 27.08%, reaching a market size of US$33.387 billion in 2029 from US$13.996 billion in 2024.

AI-based forecasting refers to the employment of AI technology software and machine learning algorithms to predict the future values of different business aspects and sectors based on past data. An AI-based forecasting application automates data connection and preparation processes. It identifies different business metrics on which to base the forecast to create a customized AI forecasting solution for different enterprises and departments. The major reasons for the high demand for AI-based forecasting software across the healthcare, retail, and various other manufacturing sectors are the demand for minimal input from the user and the consideration of several thousand factors and metrics.

However, evolutionary algorithms, deep learning, and Bayesian networks are some of the most widely used technologies in the AI-based forecasting market. Its application provides an edge to organizations and reduces manufacturing errors. With this in mind, more organizations embrace AI-powered forecasting techniques in their business processes. For instance, with the incorporation of an AI-based forecasting approach in Reynolds Aluminium, it was possible to reduce its inventory cost by 1 million pounds and reduce errors in its forecasting by about 2%.

Therefore, due to the constant evolution in AI technology and the increasing adoption of AI-powered forecasting methods across several industries, the AI-based forecasting market can grow significantly over the forecast period.

What are the AI-based forecasting market growth drivers?

• An increase in the amount of data generated by companies is fueling the AI-based forecasting market growth

The digitalization of companies' business operations in different fields is resulting in massive growth in the data generated by companies and their customers. This results in the need for big data analytics solutions using AI technology in enterprises. For instance, a survey revealed that a medium portion of around 40% of the data generated by an enterprise is being effectively utilized.

However, the optimum utilization of the data generated by companies by using them in AI-based forecasting and data analytics models could help them to accurately predict demand, forecast growth, and manage supply chains and inventories. For instance, the integration of an AI-based forecasting model in the business operations of Danone Group enabled the company to enhance its demand forecasting and lower revenue loss by around 30%. Hence, companies are extensively adopting AI-based forecasting software to improve their business operations.

• The incorporation of AI-based forecasting software in weather predictions is increasing the AI-based forecasting market growth

AI-based weather forecasting software uses satellite and other aerial image sources to examine weather patterns and conditions. Due to the higher accuracy of AI-based forecasting models, the farmers could prevent the loss of their harvest in case of a disaster. For instance, a collaboration between the World Bank and the Government of India enabled Indian farmers to generate 37% more revenue by using the AI-sponsored weather prediction tool by Cropin Technologies.

The disturbances in weather and the changes in rainfall patterns accounted for by global warming increase the demand for AI-based weather forecasting to prevent the loss of crops cultivated by farmers worldwide. For instance, the Ministry of Agriculture and Farmers’ Welfare in India announced that approximately 5.04 mha of agricultural area in India was affected due to natural calamities in 2021. Therefore, the increasing amount of crop and harvest damage across the world due to erratic weather changes generates a high level of demand for AI-based forecasting products.

What are the major challenges restraining AI-based forecasting market?

• The high levels of cost associated with AI-based forecasting tools are hampering the market growth

The additional cost of installing and implementing AI-powered forecasting solutions could discourage small and medium-sized business enterprises from purchasing such solutions. The effective working of AI-based forecasting requires employees with expertise in the working of such software. Therefore, a company newly incorporating such software solutions might have to incur additional expenses to conduct workshops and training sessions. In addition, the company should spend to maintain and update its AI-based forecasting service to prevent it from becoming obsolete. Hence, such costs could prevent the application of AI-based forecasting software across certain companies.

What are the key geographical trends shaping the AI-based forecasting market?

• Asia Pacific is witnessing exponential growth during the forecast period

AI-based forecasting in the Asia Pacific region is witnessing high growth due to increasing investments in the field of AI and the influence of the retail and agricultural sectors in this region. This growth in the retail sector of the economies in this region can be because of increased e-commerce activities and business activity digitalization. Consequently, a large proportion of companies in the retailing industry are incorporating the use of AI-based forecast tools for centralizing working departments to ensure proper management of inventory storage and issued purchase orders. For instance, the Asian HnM fashion retail stores use AI-driven demand forecasting tools to make production and other business decisions. Therefore, the increasing market size of the retail sector in the Asia Pacific region encourages AI-based forecasting market expansion.

Recent developments in the AI-based forecasting market

• In March 2023, Zionex, Inc., a company specializing in the production of technological business solutions, introduced its latest SaaS software product based on AI, PlanNEL Beta. It has different forecasting and planning features, including AI demand planning, AI-sponsored baseline forecasting, and other AI-based inventory management and prediction tools.
• In October 2022, Everything But Water, a US-based retail firm, announced its decision to integrate the AI-based forecasting, planning, and other solutions offered by Atuit.ai, a Zebra Technologies unit, into its business operations to enhance the quality of its business operations.
• In June 2022, Quantive, a company providing technological execution solutions to businesses, acquired a UK-based AI-tech company, Cliff.ai, by Greendeck Technologies, Ltd. The acquisition improved forecasting, data analysis, and other data-driven decision features in its business strategy application, Quantive Results.

AI-Based Forecasting Market Scope:

Report Metric	Details
AI-Based Forecasting Market Size in 2024	US$13.996 billion
AI-Based Forecasting Market Size in 2029	US$33.387 billion
Growth Rate	CAGR of 27.08%
Study Period	2019 to 2029
Historical Data	2019 to 2022
Base Year	2024
Forecast Period	2024 – 2029
Forecast Unit (Value)	USD Billion
Segmentation	Technology End-Users Geography
Geographical Segmentation	North America, South America, Europe, Middle East and Africa, Asia Pacific
List of Major Companies in AI-Based Forecasting Market	H2O.ai Neptune Labs DataRobot Inc Obviously AI Inc Sage Group PLC
Customization Scope	Free report customization with purchase

 

The AI-based forecasting market is segmented and analyzed as follows:

• By Technology
  • Bayesian Network
  • Evolutionary Algorithms
  • Deep Learning
• By End-Users
  • Manufacturing
  • Healthcare
  • Retail
  • Agriculture
  • Others
• By Geography
  • North America
    • USA
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Others
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Others
  • Middle East and Africa
    • Saudi Arabia
    • UAE
    • Others
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Singapore
    • Indonesia
    • Others

1. INTRODUCTION

1.1. Market Overview

1.2. Market Definition

1.3. Scope of the Study

1.4. Market Segmentation

1.5. Currency

1.6. Assumptions

1.7. Base and Forecast Years Timeline

1.8. Key Benefits to the Stakeholder

2. RESEARCH METHODOLOGY  

2.1. Research Design

2.2. Research Processes

3. EXECUTIVE SUMMARY

3.1. Key Findings

3.2. CXO Perspective

4. MARKET DYNAMICS

4.1. Market Drivers

4.2. Market Restraints

4.3. Porter’s Five Forces Analysis

4.3.1. Bargaining Power of Suppliers

4.3.2. Bargaining Power of Buyers

4.3.3. Threat of New Entrants

4.3.4. Threat of Substitutes

4.3.5. Competitive Rivalry in the Industry

4.4. Industry Value Chain Analysis

4.5. Analyst View

5. AI-BASED FORECASTING MARKET BY TECHNOLOGY 

5.1. Introduction

5.2. Bayesian Network

5.3. Evolutionary Algorithms

5.4. Deep Learning

6. AI-BASED FORECASTING MARKET BY END-USER 

6.1. Introduction

6.2. Manufacturing

6.3. Healthcare

6.4. Retail

6.5. Agriculture

6.6. Others

7. AI-BASED FORECASTING MARKET BY GEOGRAPHY

7.1. Introduction

7.2. North America

7.2.1. By Technology 

7.2.2. By End-User 

7.2.3. By Country

7.2.3.1. USA

7.2.3.2. Canada

7.2.3.3. Mexico

7.3. South America

7.3.1. By Technology 

7.3.2. By End-User 

7.3.3. By Country

7.3.3.1. Brazil

7.3.3.2. Argentina

7.3.3.3. Others

7.4. Europe

7.4.1. By Technology 

7.4.2. By End-User 

7.4.3. By Country

7.4.3.1. United Kingdom

7.4.3.2. Germany

7.4.3.3. France

7.4.3.4. Italy

7.4.3.5. Spain

7.4.3.6. Others

7.5. Middle East and Africa

7.5.1. By Technology 

7.5.2. By End-User 

7.5.3. By Country

7.5.3.1. Saudi Arabia

7.5.3.2. UAE

7.5.3.3. Others

7.6. Asia Pacific

7.6.1. By Technology 

7.6.2. By End-User 

7.6.3. By Country

7.6.3.1. China

7.6.3.2. Japan

7.6.3.3. India

7.6.3.4. South Korea

7.6.3.5. Australia

7.6.3.6. Singapore

7.6.3.7. Indonesia

7.6.3.8. Others

8. COMPETITIVE ENVIRONMENT AND ANALYSIS

8.1. Major Players and Strategy Analysis

8.2. Market Share Analysis

8.3. Mergers, Acquisitions, Agreements, and Collaborations

8.4. Competitive Dashboard

9. COMPANY PROFILES

9.1. H2O.ai

9.2. Neptune Labs

9.3. DataRobot Inc

9.4. Obviously AI Inc

9.5. Sage Group PLC

9.6. Pecan

9.7. QlikTech International AB

9.8. Dataiku

9.9. Anodot Ltd

9.10. Salesforce Inc

H2O.ai

Neptune Labs

DataRobot Inc

Obviously AI Inc

Sage Group PLC

Pecan

QlikTech International AB

Dataiku

Anodot Ltd

Salesforce Inc