自适应AI市场:现状分析与未来预测 (2024年～2032年)

在预测期（2024-2032 年），自适应人工智慧市场预计复合年增长率将达到 44%。在这一领域，机器学习和资料处理的改进将加速组织对自适应人工智慧的使用。此外，组织正在利用回馈循环和持续学习范例来协调人工智慧的使用，特别是在依赖快速、个人化行动的行业（金融、医疗保健、电子商务）。例如，2021 年 11 月 18 日，领先的呼叫效能管理云端 Hiya 宣布在 Hiya Protect 中加入自适应人工智慧，这是第一个即时发现并锁定犯罪分子的自学习系统。

依组件划分，市场分为平台与服务。该平台将在 2023 年占据重要市场占有率，因为它提供有助于自动化人工智慧开发及其实施的密集服务。此类平台提供了用于自适应人工智慧的资料处理、建模和部署的各种技术，帮助公司有效地监督其自适应人工智慧专案。例如，Profile Software 于 2024 年 3 月 7 日宣布了其新的 "AI.Adaptive" 解决方案。该解决方案整合了生成式人工智慧和大语言模型（LLM）人工智慧技术，以简化使用者与资料库、应用程式和自然语言的交互，并提高营运效率。此解决方案由 OpenAI 功能提供支援，采用与 LLM 无关的策略，可与 Profile 的 Axia Suite、Finuevo Suite、Acumen.plus、Centevo Suite、RiskAvert 和 RegiStar 平台进行直接灵活的互动。

依技术划分，市场分为机器学习 (ML)、自然语言处理 (NLP)、电脑视觉、深度学习、强化学习等。机器学习预计在预测期内（2024-2032 年）将以显着的复合年增长率成长。这是因为现代公司正在实施强化学习模型，可以从新数据中学习，从而改善预测和反应时间。公司使用 TensorFlow 和 PyTorch 作为机器学习框架。 TensorFlow 和 PyTorch 实现了适应性，因为它们支援在不断变化的环境中工作的自适应人工智慧的持续学习。这些框架可以即时配置和调整所有领域的关键数据，包括医疗保健和金融。透过应用先进的机器学习模型，组织可以获得更大的洞察力和决策权。

依应用划分，市场分为即时自适应人工智慧、离线学习/适应、情境感知适应、自主决策等。即时自适应人工智慧将在 2023 年占据重要市场占有率。这是因为即时自适应人工智慧对于需要即时、数据驱动决策的应用程式至关重要，从而刺激了快节奏领域中自适应解决方案的采用。此外，这些架构是为了成长，企业现在正在投资即时的边缘运算和串流资料架构。自适应人工智慧技术在自动驾驶和电子商务等应用领域尤其重要，因为自适应人工智慧可以帮助降低风险、改进个人化方法并提供更好的客户体验。

依最终用途，市场分为 BFSI、IT 与电信、医疗与生命科学、製造业、航太与国防、媒体与娱乐、零售与电子商务等。 BFSI 预计在预测期内（2024-2032 年）将以显着的复合年增长率成长。这主要是由于诈欺和风险检测以及为客户提供个人化服务。金融机构正在转向自适应人工智慧解决方案，这些解决方案可以处理大型资料集，并对潜在的诈欺和合规问题做出更快、更准确的决策。银行也利用人工智慧透过聊天机器人来提高客户满意度，并根据每个客户的个人资料提供个人化的金融服务。对自适应人工智慧的重视使 BFSI 组织能够增强安全性、生产力和客户体验。

为了更了解自适应人工智慧的市场采用情况，市场包括北美（美国、加拿大、北美其他地区）、欧洲（德国、法国、英国、西班牙、义大利、欧洲其他地区）、亚太地区（中国） ，根据其他地区（日本、印度、亚太其他地区）和世界其他地区的全球影响力进行分析。由于製造业、金融和零售等各行业的数位化程度不断提高，预计亚太地区在预测期内（2024-2032年）将以显着的复合年增长率成长。自适应人工智慧越来越多地应用于该领域的预测性维护、客户体验和供应链管理。中国、日本和韩国处于领先地位，在自适应环境的人工智慧方面投入大量资金。该地区正在快速采用5G技术，支援人工智慧的即时自适应部署，实现更快的回应和更高的效率。随着越来越多的组织投资人工智慧研究，此类合作进一步推动了各领域的采用。

该市场营运的主要公司包括 IBM、Google (Alphabet)、微软、亚马逊网路服务、OpenAI、NVIDIA、Marcobate、Scale AI、思科系统和 Hiya。

目录

第1章 市场概要

• 市场定义
• 主要目的
• 相关利益者
• 限制事项

第2章 分析方法或前提条件

• 分析流程
• 分析方法
• 受访者简介

第3章 摘要整理

• 产业摘要
• 各市场区隔预测
  • 市场成长的强度
• 地区展望

第4章 市场动态

• 促进因素
• 机会
• 阻碍因素
• 趋势
• PESTEL分析
• 需求面分析
• 供给面分析
  • 企业合併·收购 (M&A)
  • 投资Scenario
  • 产业考察：主要新创公司及其独特策略

第5章 价格分析

• 价格分析:各地区
• 价格的影响因素

第6章 全球自适应AI的市场收益 (2022～2032年)

第7章 市场分析:各零件

• 平台
• 服务

第8章 市场分析:各技术

• 机器学习 (ML)
• 自然语言处理 (NLP)
• computer vision
• 深层学习
• 强化学习
• 其他

第9章 市场分析:各用途

• 即时自适应AI
• 离线学习·适应
• 情境(脉络)认识适应
• 自规则性的决策
• 其他

第10章 市场分析:各最后类型

• BFSI
• IT·通讯
• 医疗·生命科学
• 製造业
• 航太·防卫
• 媒体·娱乐
• 零售业·电子商务
• 其他

第11章 市场分析:各地区

• 北美
  • 美国
  • 加拿大
  • 其他北美地区
• 欧洲
  • 德国
  • 英国
  • 法国
  • 义大利
  • 西班牙
  • 其他欧洲地区
• 亚太地区
  • 中国
  • 日本
  • 印度
  • 其他亚太地区
• 全球其他地区

第12章 价值链分析

• 市场参与企业一览

第13章 竞争情形

• 竞争仪表板
• 企业的市场定位分析
• 波特的五力分析

第14章 企业简介

• IBM
  • 企业概要
  • 主要的财务指标
  • SWOT分析
  • 产品系列
  • 近几年趋势
• Google (Alphabet Inc.)
• Microsoft
• Amazon Web Services, Inc.
• OpenAI
• NVIDIA Corporation
• Markovate Inc.
• Scale AI
• Cisco Systems, Inc.
• Hiya

第15章 缩写与前提条件

第16章 附录

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