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市场调查报告书
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1604502

基于人工智慧的预测市场：未来预测（2024-2029）

AI-Based Forecasting Market - Forecasts from 2024 to 2029
出版日期: | 出版商: Knowledge Sourcing Intelligence | 英文 135 Pages | 商品交期: 最快1-2个工作天内

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简介目录

基于人工智慧的预测市场预计将以 27.08% 的复合年增长率成长，到 2029 年，市场规模将从 2024 年的 139.96 亿美元达到 333.87 亿美元。

人工智慧预测是指利用人工智慧技术软体和机器学习演算法，根据过去的资料来预测各个业务方面和领域的未来价值。基于人工智慧的预测应用程式自动化资料连接和准备过程。确定不同的业务指标作为预测的基础，并为不同的公司和行业创建客製化的人工智慧预测解决方案。基于人工智慧的预测软体在医疗保健、零售和其他各种製造业需求量很大的主要原因是它需要用户的输入最少，并且需要考虑数千个因素和指标。

然而，演化演算法、深度学习和贝氏网路是基于人工智慧的预测市场中使用最广泛的技术。它的应用为组织带来了优势并减少了製造错误。考虑到这一点，越来越多的组织正在将人工智慧驱动的预测技术纳入其业务流程。例如，透过采用基于人工智慧的预测方法，雷诺兹铝业能够将库存成本降低 100 万英镑，并将预测误差减少约 2%。

因此，人工智慧技术的不断发展以及多个行业越来越多地采用人工智慧驱动的预测技术可能会在预测期内显着增长基于人工智慧的预测市场。

基于人工智慧的预测市场的驱动因素

  • 公司产生的资料量不断增加推动基于人工智慧的预测市场的成长

由于各行业业务业务的数位化，企业及其客户产生的资料量不断增加。因此，企业越来越需要利用人工智慧技术的巨量资料分析解决方案。例如，一项研究发现，公司产生的资料中只有约 40% 得到了有效利用。

然而，透过优化利用基于人工智慧的预测和资料分析模型的公司产生的资料，可以准确预测需求、预测成长以及管理供应链和库存。例如，达能集团透过将基于人工智慧的预测模型整合到业务中，能够改善需求预测并将收益损失减少约 30%。因此，企业正在广泛采用基于人工智慧的预测软体来改善其业务运作。

基于人工智慧的预测市场的地理前景

  • 亚太地区在预测期内将经历指数级增长

由于人工智慧领域投资的增加以及该地区零售和农业领域的影响，亚太地区基于人工智慧的预测市场正在经历高速成长。该地区经济体零售业的成长得益于电子商务和商业活动日益数位化。因此，零售业的许多公司正在采用基于人工智慧的预测工具来集中工作部门，以确保库存储存和下达采购订单的正确管理。例如，亚洲的 HnM 时尚零售店使用人工智慧驱动的需求预测工具来为生产和其他业务决策提供资讯。因此，亚太地区零售业市场规模的不断扩大正在推动基于人工智慧的预测市场的扩张。

为什么要购买这份报告？

  • 富有洞察力的分析：获得涵盖主要和新兴地区的深入市场洞察，重点关注客户细分、政府政策和社会经济因素、消费者偏好、行业明智以及其他子区隔。
  • 竞争格局：了解世界主要企业采取的策略策略，并了解透过正确的策略渗透市场的潜力。
  • 市场驱动因素和未来趋势：探索动态因素和关键市场趋势以及它们将如何塑造未来市场发展。
  • 可行的建议：利用洞察力做出策略决策，以在动态环境中发现新的业务流和收益。
  • 受众广泛：对于新兴企业、研究机构、顾问、中小企业和大型企业有用且具有成本效益。

它有什么用？

产业与市场考量、商机评估、产品需求预测、打入市场策略、地理扩张、资本投资决策、法律规范与影响、新产品开发、竞争影响

分析范围

  • 历史资料与预测（2022-2029）
  • 成长机会、挑战、供应链前景、法规结构、顾客行为、趋势分析
  • 竞争对手定位、策略和市场占有率分析
  • 收益成长率与预测分析：按细分市场/地区（按国家）
  • 公司概况（策略、产品、财务资讯、主要趋势等）

目录

第一章简介

  • 市场概况
  • 市场定义
  • 分析范围
  • 市场区隔
  • 货币
  • 先决条件
  • 基准年和预测年时间表
  • 相关利益者的主要利益

第二章 分析方法

  • 分析设计
  • 分析过程

第三章执行摘要

  • 主要发现
  • CXO观点

第四章市场动态

  • 市场驱动因素
  • 市场限制因素
  • 波特五力分析
  • 产业价值链分析
  • 分析师观点

第五章 基于人工智慧的预测市场：依技术分类

  • 介绍
  • 贝氏网络
  • 演化演算法
  • 深度学习

第六章 基于人工智慧的预测市场：依最终用户划分

  • 介绍
  • 製造业
  • 医疗保健
  • 零售业
  • 农业
  • 其他的

第七章 基于人工智慧的预测市场：按地区

  • 介绍
  • 北美洲
    • 依技术
    • 按最终用户
    • 按国家/地区
  • 南美洲
    • 依技术
    • 按最终用户
    • 按国家/地区
  • 欧洲
    • 依技术
    • 按最终用户
    • 按国家/地区
  • 中东/非洲
    • 依技术
    • 按最终用户
    • 按国家/地区
  • 亚太地区
    • 依技术
    • 按最终用户
    • 按国家/地区

第八章竞争环境及分析

  • 主要企业及策略分析
  • 市场占有率分析
  • 企业合併（M&A）、合约、业务合作
  • 竞争对手仪表板

第九章 公司简介

  • H2O.ai
  • Neptune Labs
  • DataRobot Inc
  • Obviously AI Inc
  • Sage Group PLC
  • Pecan
  • QlikTech International AB
  • Dataiku
  • Anodot Ltd
  • Salesforce Inc
简介目录
Product Code: KSI061614869

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.

AI-based forecasting market 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.

AI-based forecasting market geographical outlook

  • 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.

Reasons for buying this report:-

  • Insightful Analysis: Gain detailed market insights covering major as well as emerging geographical regions, focusing on customer segments, government policies and socio-economic factors, consumer preferences, industry verticals, other sub- segments.
  • Competitive Landscape: Understand the strategic maneuvers employed by key players globally to understand possible market penetration with the correct strategy.
  • Market Drivers & Future Trends: Explore the dynamic factors and pivotal market trends and how they will shape up future market developments.
  • Actionable Recommendations: Utilize the insights to exercise strategic decision to uncover new business streams and revenues in a dynamic environment.
  • Caters to a Wide Audience: Beneficial and cost-effective for startups, research institutions, consultants, SMEs, and large enterprises.

What do businesses use our reports for?

Industry and Market Insights, Opportunity Assessment, Product Demand Forecasting, Market Entry Strategy, Geographical Expansion, Capital Investment Decisions, Regulatory Framework & Implications, New Product Development, Competitive Intelligence

Report Coverage:

  • Historical data & forecasts from 2022 to 2029
  • Growth Opportunities, Challenges, Supply Chain Outlook, Regulatory Framework, Customer Behaviour, and Trend Analysis
  • Competitive Positioning, Strategies, and Market Share Analysis
  • Revenue Growth and Forecast Assessment of segments and regions including countries
  • Company Profiling (Strategies, Products, Financial Information, and Key Developments among others)

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

TABLE OF CONTENTS

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