自適應AI市場:現狀分析與未來預測 (2024年～2032年)

在預測期（2024-2032 年），自適應人工智慧市場預計複合年增長率將達到 44%。在這一領域，機器學習和資料處理的改進將加速組織對自適應人工智慧的使用。此外，組織正在利用回饋循環和持續學習範例來協調人工智慧的使用，特別是在依賴快速、個人化行動的行業（金融、醫療保健、電子商務）。例如，2021 年 11 月 18 日，領先的呼叫效能管理雲端 Hiya 宣佈在 Hiya Protect 中加入自適應人工智慧，這是第一個即時發現並鎖定犯罪分子的自學習系統。

依組件劃分，市場分為平台與服務。該平台將在 2023 年佔據重要市場佔有率，因為它提供有助於自動化人工智慧開發及其實施的密集服務。此類平台提供了用於自適應人工智慧的資料處理、建模和部署的各種技術，幫助公司有效地監督其自適應人工智慧專案。例如，Profile Software 於 2024 年 3 月 7 日宣布了其新的 "AI.Adaptive" 解決方案。該解決方案整合了生成式人工智慧和大語言模型（LLM）人工智慧技術，以簡化使用者與資料庫、應用程式和自然語言的交互，並提高營運效率。此解決方案由 OpenAI 功能提供支援，採用與 LLM 無關的策略，可與 Profile 的 Axia Suite、Finuevo Suite、Acumen.plus、Centevo Suite、RiskAvert 和 RegiStar 平台進行直接靈活的互動。

依技術劃分，市場分為機器學習 (ML)、自然語言處理 (NLP)、電腦視覺、深度學習、強化學習等。機器學習預計在預測期內（2024-2032 年）將以顯著的複合年增長率成長。這是因為現代公司正在實施強化學習模型，可以從新數據中學習，從而改善預測和反應時間。公司使用 TensorFlow 和 PyTorch 作為機器學習框架。 TensorFlow 和 PyTorch 實現了適應性，因為它們支援在不斷變化的環境中工作的自適應人工智慧的持續學習。這些框架可以即時配置和調整所有領域的關鍵數據，包括醫療保健和金融。透過應用先進的機器學習模型，組織可以獲得更大的洞察力和決策權。

依應用劃分，市場分為即時自適應人工智慧、離線學習/適應、情境感知適應、自主決策等。即時自適應人工智慧將在 2023 年佔據重要市場佔有率。這是因為即時自適應人工智慧對於需要即時、數據驅動決策的應用程式至關重要，從而刺激了快節奏領域中自適應解決方案的採用。此外，這些架構是為了成長，企業現在正在投資即時的邊緣運算和串流資料架構。自適應人工智慧技術在自動駕駛和電子商務等應用領域尤其重要，因為自適應人工智慧可以幫助降低風險、改進個人化方法並提供更好的客戶體驗。

依最終用途，市場分為 BFSI、IT 與電信、醫療與生命科學、製造業、航太與國防、媒體與娛樂、零售與電子商務等。 BFSI 預計在預測期內（2024-2032 年）將以顯著的複合年增長率成長。這主要是由於詐欺和風險檢測以及為客戶提供個人化服務。金融機構正在轉向自適應人工智慧解決方案，這些解決方案可以處理大型資料集，並對潛在的詐欺和合規問題做出更快、更準確的決策。銀行也利用人工智慧透過聊天機器人來提高客戶滿意度，並根據每個客戶的個人資料提供個人化的金融服務。對自適應人工智慧的重視使 BFSI 組織能夠增強安全性、生產力和客戶體驗。

為了更了解自適應人工智慧的市場採用情況，市場包括北美（美國、加拿大、北美其他地區）、歐洲（德國、法國、英國、西班牙、義大利、歐洲其他地區）、亞太地區（中國） ，根據其他地區（日本、印度、亞太其他地區）和世界其他地區的全球影響力進行分析。由於製造業、金融和零售等各行業的數位化程度不斷提高，預計亞太地區在預測期內（2024-2032年）將以顯著的複合年增長率成長。自適應人工智慧越來越多地應用於該領域的預測性維護、客戶體驗和供應鏈管理。中國、日本和韓國處於領先地位，在自適應環境的人工智慧方面投入大量資金。該地區正在快速採用5G技術，支援人工智慧的即時自適應部署，實現更快的回應和更高的效率。隨著越來越多的組織投資人工智慧研究，此類合作進一步推動了各領域的採用。

該市場營運的主要公司包括 IBM、Google (Alphabet)、微軟、亞馬遜網路服務、OpenAI、NVIDIA、Marcobate、Scale AI、思科系統和 Hiya。

目錄

第1章 市場概要

• 市場定義
• 主要目的
• 相關利益者
• 限制事項

第2章 分析方法或前提條件

• 分析流程
• 分析方法
• 受訪者簡介

第3章 摘要整理

• 產業摘要
• 各市場區隔預測
  • 市場成長的強度
• 地區展望

第4章 市場動態

• 促進因素
• 機會
• 阻礙因素
• 趨勢
• PESTEL分析
• 需求面分析
• 供給面分析
  • 企業合併·收購 (M&A)
  • 投資Scenario
  • 產業考察：主要新創公司及其獨特策略

第5章 價格分析

• 價格分析:各地區
• 價格的影響因素

第6章 全球自適應AI的市場收益 (2022～2032年)

第7章 市場分析:各零件

• 平台
• 服務

第8章 市場分析:各技術

• 機器學習 (ML)
• 自然語言處理 (NLP)
• computer vision
• 深層學習
• 強化學習
• 其他

第9章 市場分析:各用途

• 即時自適應AI
• 離線學習·適應
• 情境(脈絡)認識適應
• 自規則性的決策
• 其他

第10章 市場分析:各最後類型

• BFSI
• IT·通訊
• 醫療·生命科學
• 製造業
• 航太·防衛
• 媒體·娛樂
• 零售業·電子商務
• 其他

第11章 市場分析:各地區

• 北美
  • 美國
  • 加拿大
  • 其他北美地區
• 歐洲
  • 德國
  • 英國
  • 法國
  • 義大利
  • 西班牙
  • 其他歐洲地區
• 亞太地區
  • 中國
  • 日本
  • 印度
  • 其他亞太地區
• 全球其他地區

第12章 價值鏈分析

• 市場參與企業一覽

第13章 競爭情形

• 競爭儀表板
• 企業的市場定位分析
• 波特的五力分析

第14章 企業簡介

• IBM
  • 企業概要
  • 主要的財務指標
  • SWOT分析
  • 產品系列
  • 近幾年趨勢
• Google (Alphabet Inc.)
• Microsoft
• Amazon Web Services, Inc.
• OpenAI
• NVIDIA Corporation
• Markovate Inc.
• Scale AI
• Cisco Systems, Inc.
• Hiya

第15章 縮寫與前提條件

第16章 附錄

Adaptive AI is a type of artificial intelligence that constantly learns and modifies itself based on data collected in real-time, changing its underlying parameters and output based on the environment and data received as well as feedback. While conventional AI is based on a set of training models, adaptive AI is a non-invasive technology that learns and evolves on its own. Adding to this, flexibility makes adaptive AI ideal in applications that require quick response and flexibility such as autonomous driving, healthcare, and fraud detection. As a result of making changes to the data and conditions, adaptive AI offers customized answers that can change as the user's requirements and the market change. The adaptive AI market is fostered by the requirement of real-time decision-making that allows companies to offer fast solutions to various industries including finance and healthcare. The market is also driven by the need to offer individualized customer interactions, as adaptive AI can customize the service according to the user's actions.

The Adaptive AI Market is expected to grow with a significant CAGR of 44% during the forecast period (2024-2032). This sector allows improvements in machine learning and data processing to facilitate the use of adaptive AI by organizations. Furthermore, organizations are leveraging feedback loops and the continuous learning paradigm to adjust the use of AI, especially in industries that rely on quick and individualized actions (finance, healthcare, and e-commerce). For instance, on November 18, 2021, Hiya, the leading call performance management cloud, revealed that it has added Adaptive AI to Hiya Protect which is the first self-learning system that seeks out and closes down criminals in real time.

Based on the component, the market is segmented into platforms and services. The platform held a significant share of the market in 2023 Because platforms offer focused services that help in the automation of AI development and its implementation. Such platforms offer different technologies for data handling, modeling, and deployment of adaptive AI that help companies to oversee adaptive AI projects effectively. For instance, on March 7, 2024, Profile Software launched its new "AI.Adaptive" solution, which simplifies user interaction into natural language with databases and applications, enhancing operational efficiency by integrating Generative AI and Large Language Models (LLMs) artificial intelligence technologies. The solution, enhanced by the capabilities of OpenAI, adopts an LLM-agnostic strategy, enabling direct and flexible interaction with Profile's Axia Suite, Finuevo Suite, Acumen.plus, Centevo Suite, RiskAvert and RegiStar platforms.

Based on technology, the market is segmented into machine learning (ML), natural language processing (NLP), computer vision, deep learning, reinforcement learning, and others. Machine learning is expected to grow with a significant CAGR during the forecast period (2024-2032) owing to the modern enterprises are now implementing Reinforcement Learning models that can learn from new data and therefore improve forecasting and reaction time. Companies use TensorFlow and PyTorch as ML frameworks that allow for adaptability because they support continuous learning for adaptive AI that can work in evolving contexts. These frameworks enable real-time providence and tuning of the data which is crucial in all sectors including health and finance. The application of advanced machine learning models helps organizations to gain better insights and decision-making power.

Based on the application, the market is segmented into real-time adaptive AI, offline learning and adaptation, context-aware adaptation, autonomous decision-making, and others. Real-time adaptive AI held a considerable share of the market in 2023. This is because real-time adaptive AI is important for applications that require instantaneous data-driven decision-making thus fueling the uptake of adaptive solutions in fast-paced sectors. Moreover, these architectures are for growth, and companies are now investing in edge computing and streaming data architectures that are real-time. Technologies with adaptive AI are especially important in application areas such as autonomous driving and e-commerce, given that adaptive AI helps reduce risks, improve individual approaches, and provide better customer experience.

Based on end-use, the market is segmented into BFSI, IT & telecommunications, healthcare & life sciences, manufacturing, aerospace & defense, media & entertainment, retail & e-commerce, and others. BFSI is expected to grow with a significant CAGR during the forecast period (2024-2032). This is mainly due to the detection of fraud and risks, as well as to the provision of individual services to customers. Financial organizations are turned to adaptive AI solutions that are capable of processing large data sets and making decisions on potential fraud and compliance issues faster and more accurately. Also, banks are using AI for customer satisfaction through chatbots and individualized financial services to cater to each customer's profile. This emphasis on adaptive AI is allowing BFSI organizations to enhance security, productivity, and customer experience.

For a better understanding of the market adoption of Adaptive AI, the market is analyzed based on its worldwide presence in countries such as North America (U.S., Canada, and the Rest of North America), Europe (Germany, France, U.K., Spain, Italy, Rest of Europe), Asia-Pacific (China, Japan, India, Rest of Asia-Pacific), Rest of World. Asia-Pacific is expected to grow with a significant CAGR during the forecast period (2024-2032) due to the increased digitalization across various sectors including manufacturing, finance, and retail. Adaptable AI is being used more and more in this area for predictive maintenance, customer experience, and supply chain management. China, Japan, and South Korea are leading the way, with significant spending on AI for the adaptive environment. The 5G technology is rapidly being embraced in the region and this supports the real-time adaptive deployment of AI which enhances quick response and high efficiency. These collaborations are driving adaptive AI adoption across various sectors even more as more organizations invest in AI research.

Some of the major players operating in the market include IBM, Google (Alphabet Inc.), Microsoft, Amazon Web Services, Inc., OpenAI, NVIDIA Corporation, Markovate Inc., Scale AI, Cisco Systems, Inc., Hiya.

TABLE OF CONTENTS

1.MARKET INTRODUCTION

• 1.1. Market Definitions
• 1.2. Main Objective
• 1.3. Stakeholders
• 1.4. Limitation

2.RESEARCH METHODOLOGY OR ASSUMPTION

• 2.1. Research Process of the Adaptive AI Market
• 2.2. Research Methodology of the Adaptive AI Market
• 2.3. Respondent Profile

3.EXECUTIVE SUMMARY

• 3.1. Industry Synopsis
• 3.2. Segmental Outlook
  • 3.2.1. Market Growth Intensity
• 3.3. Regional Outlook

4.MARKET DYNAMICS

• 4.1. Drivers
• 4.2. Opportunity
• 4.3. Restraints
• 4.4. Trends
• 4.5. PESTEL Analysis
• 4.6. Demand Side Analysis
• 4.7. Supply Side Analysis
  • 4.7.1. Merger & Acquisition
  • 4.7.2. Investment Scenario
  • 4.7.3. Industry Insights: Leading Startups and Their Unique Strategies

5.PRICING ANALYSIS

• 5.1. Regional Pricing Analysis
• 5.2. Price Influencing Factors

6.GLOBAL ADAPTIVE AI MARKET REVENUE (USD BN), 2022-2032F

7.MARKET INSIGHTS BY COMPONENT

• 7.1. Platform
• 7.2. Services

8.MARKET INSIGHTS BY TECHNOLOGY

• 8.1. Machine Learning (ML)
• 8.2. Natural Language Processing (NLP)
• 8.3. Computer Vision
• 8.4. Deep Learning
• 8.5. Reinforcement Learning
• 8.6. Others

9.MARKET INSIGHTS BY APPLICATION

• 9.1. Real-time Adaptive AI
• 9.2. Offline Learning and Adaptation
• 9.3. Context-aware Adaptation
• 9.4. Autonomous Decision-Making
• 9.5. Others

10.MARKET INSIGHTS BY END-USE

• 10.1. BFSI
• 10.2. IT & Telecommunications
• 10.3. Healthcare & Life Sciences
• 10.4. Manufacturing
• 10.5. Aerospace & Defense
• 10.6. Media & Entertainment
• 10.7. Retail & E-commerce
• 10.8. Others

11.MARKET INSIGHTS BY REGION

• 11.1. North America
  • 11.1.1. U.S.
  • 11.1.2. Canada
  • 11.1.3. Rest of North America
• 11.2. Europe
  • 11.2.1. Germany
  • 11.2.2. France
  • 11.2.3. UK
  • 11.2.4. Spain
  • 11.2.5. Italy
  • 11.2.6. Rest of Europe
• 11.3. Asia-Pacific
  • 11.3.1. China
  • 11.3.2. Japan
  • 11.3.3. India
  • 11.3.4. Rest of APAC
• 11.4. Rest of the World

12.VALUE CHAIN ANALYSIS

• 12.1. List of Market Participants

13.COMPETITIVE LANDSCAPE

• 13.1. Competition Dashboard
• 13.2. Competitor Market Positioning Analysis
• 13.3. Porter Five Forces Analysis

14.COMPANY PROFILES

• 14.1. IBM
  • 14.1.1. Company Overview
  • 14.1.2. Key Financials
  • 14.1.3. SWOT Analysis
  • 14.1.4. Product Portfolio
  • 14.1.5. Recent Developments
• 14.2. Google (Alphabet Inc.)
• 14.3. Microsoft
• 14.4. Amazon Web Services, Inc.
• 14.5. OpenAI
• 14.6. NVIDIA Corporation
• 14.7. Markovate Inc.
• 14.8. Scale AI
• 14.9. Cisco Systems, Inc.
• 14.10. Hiya

15.ACRONYMS & ASSUMPTION

16.ANNEXURE