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市場調查報告書
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1995843

人工智慧驅動的預測市場：策略性洞察與預測（2026-2031）

AI-Based Forecasting Market - Strategic Insights and Forecasts (2026-2031)
出版日期: | 出版商: Knowledge Sourcing Intelligence | 英文 144 Pages | 商品交期: 最快1-2個工作天內

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簡介目錄

全球人工智慧驅動的預測市場預計將從 2026 年的 200 億美元成長到 2031 年的 463 億美元，複合年成長率為 18.3%。

全球人工智慧預測市場被視為支撐各產業數據驅動決策的關鍵要素。企業越來越依賴預測智慧來應對市場波動、最佳化營運並提高規劃準確性。隨著全球市場、供應鏈和客戶行為日益複雜，自動化預測工具的重要性也與日俱增。基於人工智慧的預測解決方案利用機器學習演算法分析大規模資料集、偵測模式並產生預測性洞察，且只需極少的人工干預。這種能力正在推動零售、製造、金融、醫療保健和物流等行業的廣泛應用。企業正從傳統的統計預測方法轉向支援即時分析和持續學習的自適應人工智慧模型。隨著數位轉型步伐的加快，全球對可擴展智慧預測平台的需求持續成長。

市場促進因素

市場成長的主要驅動力是企業產生的數據量快速成長。如今，企業需要管理來自業務系統、數位管道和外部市場資訊來源的大量結構化和非結構化資料。基於人工智慧的預測工具能夠幫助企業將這些數據轉化為可執行的洞察。

另一個重要因素是在不確定的經濟狀況下提高規劃準確性的必要性。企業面臨需求波動、供應鏈中斷和瞬息萬變的市場環境。預測分析使企業能夠主動應對，而非被動反應。

資料準備和模型開發的自動化也是推動其應用的重要因素。人工智慧預測平台簡化了資料整合、模型訓練和效能監控流程，減少了對人工流程和專家知識的依賴。

數位商務和互聯系統的擴展進一步推動了需求成長。即時數據的可用性提高了預測準確性，並支援各業務部門的持續決策。

市場限制因素

儘管成長潛力巨大，但一些因素阻礙了市場發展。實施的複雜性仍然是許多組織面臨的挑戰。將人工智慧預測工具與舊有系統整合需要技術專長和基礎設施投資。

資料品質和管治方面的問題也限制了預測模型的應用。預測模型高度依賴準確且一致的數據。不完整或不一致的資料集會降低預測的可靠性。

成本問題也是一個障礙，尤其對於中小企業而言。先進的分析平台、熟練的人員和資料管理系統都需要大量的初期投資。

對模型透明度和可解釋性的擔憂也可能延緩其在受監管行業的應用，因為在這些行業中，可解釋性至關重要。

技術與細分市場洞察

基於人工智慧的預測解決方案結合了機器學習、統計建模和自動化資料處理。這些系統能夠識別相關的業務指標，整合多個資料來源，並產生客製化的預測模型。

依組成要素的不同，市場區隔可分為軟體平台與服務兩大類。軟體解決方案提供預測建模、視覺化和分析功能。服務包括部署、整合和支援。

部署模式包括雲端部署和本地部署。由於雲端部署具有可擴展性和較低的基礎架構要求，因此越來越受歡迎。

應用領域包括需求預測、財務預測、供應鏈規劃、風險評估和營運預測。具體應用產業包括製造業、零售業、金融服務業、醫療保健業及物流業。

競爭格局與策略展望

當前競爭格局的一個關鍵特徵是，技術供應商正專注於進階分析、自動化和整合柔軟性。供應商正在投資演算法創新和方便用戶使用型介面，以擴大其在各個業務職能中的應用。

分析服務提供者與企業技術供應商之間的策略合作正在推動生態系統的發展。此外，這些公司正致力於透過持續學習框架和即時數據整合來提高模型準確性。

參與企業優先考慮高度擴充性的平台，這些平台支援公司範圍內的部署和跨職能決策。

重點

隨著各組織尋求利用預測智慧來應對複雜性和不確定性，全球基於人工智慧的預測市場正在迅速擴張。資料處理、機器學習和自動化技術的持續進步將進一步加速各行業的應用。儘管應用方面仍存在一些挑戰，但精準預測的策略價值將支撐市場的長期成長。

本報告的主要益處

  • 深入分析：獲得跨地區、客戶群、政策、社會經濟因素、消費者偏好和產業領域的詳細市場洞察。
  • 競爭格局：了解主要企業的策略趨勢，並確定最佳的市場進入方式。
  • 市場促進因素與未來趨勢：我們評估影響市場的關鍵成長要素和新興趨勢。
  • 實用建議：我們支援制定策略決策以開發新的收入來源。
  • 適合各類讀者：非常適合Start-Ups、研究機構、顧問公司、中小企業和大型企業。

我們的報告的使用情況

產業和市場洞察、機會評估、產品需求預測、打入市場策略、區域擴張、資本投資決策、監管分析、新產品開發和競爭情報。

報告範圍

  • 2021年至2025年的歷史數據和2026年至2031年的預測數據
  • 成長機會、挑戰、供應鏈前景、法律規範與趨勢分析
  • 競爭定位、策略和市場佔有率評估
  • 細分市場和區域銷售成長及預測評估
  • 公司簡介，包括策略、產品、財務狀況和主要發展動態。

目錄

第1章：引言

  • 市場概覽
  • 市場的定義
  • 調查範圍
  • 市場區隔
  • 貨幣
  • 先決條件
  • 基準年及預測年調查期
  • 相關人員的主要收益

第2章：調查方法

  • 調查設計
  • 研究過程

第3章執行摘要

  • 主要發現
  • 首席體驗長的觀點

第4章 市場動態

  • 市場促進因素
  • 市場限制因素
  • 波特五力分析
  • 產業價值鏈分析
  • 分析師意見

第5章：人工智慧驅動的預測市場：按技術分類

  • 貝氏網路
  • 演化演算法
  • 深度學習

第6章：人工智慧驅動的預測市場：依最終用戶分類

  • 製造業
  • 衛生保健
  • 零售
  • 農業
  • 其他

第7章 人工智慧驅動的預測市場：按地區分類

  • 北美洲
    • 透過技術
    • 最終用戶
    • 國家
      • 美國
      • 加拿大
      • 墨西哥
  • 南美洲
    • 透過技術
    • 最終用戶
    • 國家
      • 巴西
      • 阿根廷
      • 其他
  • 歐洲
    • 透過技術
    • 最終用戶
    • 國家
      • 英國
      • 德國
      • 法國
      • 義大利
      • 西班牙
      • 其他
  • 中東和非洲
    • 透過技術
    • 最終用戶
    • 國家
      • 沙烏地阿拉伯
      • UAE
      • 其他
  • 亞太地區
    • 透過技術
    • 最終用戶
    • 國家
      • 中國
      • 日本
      • 印度
      • 韓國
      • 澳洲
      • 新加坡
      • 印尼
      • 其他

第8章：競爭環境與分析

  • 主要企業及策略分析
  • 市佔率分析
  • 合併、收購、協議和合作關係
  • 競爭環境儀錶板

第9章：公司簡介

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

The Global AI-Based Forecasting market is forecast to grow at a CAGR of 18.3%, reaching USD 46.3 billion in 2031 from USD 20.0 billion in 2026.

The global AI-based forecasting market is positioned as a critical enabler of data driven decision making across industries. Organizations increasingly rely on predictive intelligence to manage volatility, optimize operations, and improve planning accuracy. The growing complexity of global markets, supply chains, and customer behavior has elevated the importance of automated forecasting tools. AI-based forecasting solutions leverage machine learning algorithms to analyze large datasets, detect patterns, and generate predictive insights with minimal manual intervention. This capability is driving adoption across sectors including retail, manufacturing, finance, healthcare, and logistics. Enterprises are transitioning from traditional statistical forecasting methods to adaptive AI models that support real time analysis and continuous learning. As digital transformation initiatives accelerate, the demand for scalable and intelligent forecasting platforms continues to expand globally.

Market Drivers

The primary driver of market growth is the rapid increase in enterprise data generation. Organizations now manage vast volumes of structured and unstructured data from operational systems, digital channels, and external market sources. AI based forecasting tools enable companies to transform this data into actionable insights.

Another key driver is the need for improved planning accuracy in uncertain economic conditions. Businesses face fluctuating demand patterns, supply chain disruptions, and dynamic market environments. Predictive analytics helps organizations respond proactively rather than reactively.

Automation of data preparation and model development also supports adoption. AI forecasting platforms streamline data integration, model training, and performance monitoring. This reduces dependence on manual processes and specialist expertise.

The expansion of digital commerce and connected systems further fuels demand. Real time data availability improves forecast precision and supports continuous decision making across operational functions.

Market Restraints

Despite strong growth potential, several factors restrain market expansion. Implementation complexity remains a challenge for many organizations. Integrating AI forecasting tools with legacy systems requires technical expertise and infrastructure investment.

Data quality and governance issues also limit adoption. Forecasting models depend heavily on accurate and consistent data. Incomplete or inconsistent datasets can reduce prediction reliability.

Cost considerations represent another barrier, particularly for small and medium enterprises. Advanced analytics platforms, skilled personnel, and data management systems require significant upfront investment.

Concerns around model transparency and interpretability may also slow adoption in regulated industries where explainability is critical.

Technology and Segment Insights

AI based forecasting solutions combine machine learning, statistical modeling, and automated data processing. These systems identify relevant business metrics, connect multiple data sources, and generate customized predictive models.

The market can be segmented by component into software platforms and services. Software solutions provide predictive modeling, visualization, and analytics capabilities. Services include implementation, integration, and support.

Deployment models include cloud based and on premise solutions. Cloud deployment is gaining traction due to scalability and lower infrastructure requirements.

Application areas include demand forecasting, financial forecasting, supply chain planning, risk assessment, and operational forecasting. Industry vertical adoption spans manufacturing, retail, financial services, healthcare, and logistics.

Competitive and Strategic Outlook

The competitive landscape is characterized by technology providers focusing on advanced analytics capabilities, automation features, and integration flexibility. Vendors are investing in algorithm innovation and user friendly interfaces to expand adoption across business functions.

Strategic partnerships between analytics providers and enterprise technology vendors support ecosystem development. Companies are also enhancing model accuracy through continuous learning frameworks and real time data integration.

Market participants are prioritizing scalable platforms that support enterprise wide deployment and cross functional decision making.

Key Takeaways

The global AI-based forecasting market is expanding rapidly as organizations seek predictive intelligence to manage complexity and uncertainty. Continued advances in data processing, machine learning, and automation will strengthen adoption across industries. While implementation challenges remain, the strategic value of accurate forecasting will sustain long term market growth.

Key Benefits of this Report

  • Insightful Analysis: Gain detailed market insights across regions, customer segments, policies, socio-economic factors, consumer preferences, and industry verticals.
  • Competitive Landscape: Understand strategic moves by key players to identify optimal market entry approaches.
  • Market Drivers and Future Trends: Assess major growth forces and emerging developments shaping the market.
  • Actionable Recommendations: Support strategic decisions to unlock new revenue streams.
  • Caters to a Wide Audience: Suitable for startups, research institutions, consultants, SMEs, and large enterprises.

What businesses use our reports for

Industry and market insights, opportunity assessment, product demand forecasting, market entry strategy, geographical expansion, capital investment decisions, regulatory analysis, new product development, and competitive intelligence.

Report Coverage

  • Historical data from 2021 to 2025 and forecast data from 2026 to 2031
  • Growth opportunities, challenges, supply chain outlook, regulatory framework, and trend analysis
  • Competitive positioning, strategies, and market share evaluation
  • Revenue growth and forecast assessment across segments and regions
  • Company profiling including strategies, products, financials, and key developments

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