시장보고서
상품코드
1709578

AI 앱 시장 규모, 점유율, 동향 분석 보고서 : 기능별, 최종 용도별, 지역별 전망 및 예측(2025-2032년)

Global AI Apps Market Size, Share & Trends Analysis Report By Functionality, By End-use, By Regional Outlook and Forecast, 2025 - 2032

발행일: | 리서치사: KBV Research | 페이지 정보: 영문 275 Pages | 배송안내 : 즉시배송

    
    
    



※ 본 상품은 영문 자료로 한글과 영문 목차에 불일치하는 내용이 있을 경우 영문을 우선합니다. 정확한 검토를 위해 영문 목차를 참고해주시기 바랍니다.

세계 AI 앱 시장 규모는 예측 기간 동안 39.1%의 CAGR로 성장하여 2032년까지 438억 5,000만 달러에 달할 것으로 예상됩니다.

KBV Cardinal matrix - AI 앱 시장의 경쟁 분석

KBV Cardinal matrix에 나타난 분석에 따르면, Microsoft Corporation, Google LLC, NVIDIA Corporation, Amazon Web Services, Inc.가 AI 앱 시장의 선구자입니다. 2025년 1월, Microsoft Corporation과 OpenAI는 파트너십을 연장하여 Azure의 API 독점권을 유지하고 수익을 공유하며 Copilot에 OpenAI 모델을 통합했습니다. Microsoft Corporation과 OpenAI는 파트너십을 2030년까지 연장하고, Azure의 API 독점권을 유지하고, 수익을 공유하며, Copilot과 같은 Microsoft 제품에 OpenAI 모델을 통합하기로 했습니다. Oracle Corporation 및 Salesforce, Inc. 등 AI 앱 시장에서 주요 혁신 기업들과 함께 OpenAI의 연구를 지원하고, AI 앱 시장에서 양사의 역할을 강화할 예정입니다.

출처 : KBV 리서치 및 2차 조사 분석

촉진요인과 억제요인

촉진요인* 스마트폰 및 디바이스 성장 AI 앱에 대한 접근성 확대

  • AI 앱 혁신을 주도하는 기술 및 스타트업에 대한 투자 확대
  • 디지털 전환과 클라우드 도입으로 확장 가능한 AI 도입 실현 가능

억제요인* AI 애플리케이션의 실용화를 위한 높은 개발 비용과 복잡성

  • 데이터 프라이버시, 보안, AI 기술의 윤리적 활용에 대한 우려로 도입이 제한적

기회* AI 앱 개발을 간소화하는 로우코드 및 노코드 플랫폼의 등장으로 AI 앱 개발 간소화

  • AI 혁신과 부문 간 적용을 촉진하기 위한 정부 지원 및 이니셔티브 제공

과제* 끊임없이 진화하는 기술로 인해 AI 애플리케이션의 지속적인 업데이트 및 재교육 필요

  • 기존 산업 및 기업에서 레거시 인프라와의 통합이 어려운 점

시장 성장요인

스마트폰과 커넥티드 디바이스의 폭발적인 보급은 사용자들이 디지털 플랫폼과 소통하는 방식을 변화시켰습니다. 전 세계 수십억 명의 활성 모바일 사용자를 보유한 AI 앱은 지속적으로 사용자층을 확장하고 있으며, 안드로이드부터 iOS까지 앱 개발자들은 실시간 번역, 지능형 사진 정리, 개인화된 추천과 같은 AI 기능을 내장하여 AI를 일상적인 사용자 경험으로 발전시키고 있습니다. AI를 일상적인 사용자 경험으로 진화시키고 있습니다. 따라서 스마트폰과 디바이스의 성장, 그리고 AI 앱에 대한 접근성 확대가 시장 성장을 주도하고 있습니다.

또한, AI 전문 스타트업에 대한 벤처 캐피털과 기관투자자들의 투자는 차세대 애플리케이션 개발을 가속화하고 있습니다. 이러한 자금 조달 라운드는 스타트업에 전문 인력 채용, 고품질 데이터세트에 대한 접근, 최첨단 알고리즘 실험을 위한 리소스를 제공합니다. 그 결과, AI 앱 환경은 기능과 사용자 경험이 빠르게 진화하고 있습니다. 결론적으로, AI 앱의 혁신을 주도하는 기술 기업 및 스타트업에 대한 투자 증가가 시장 성장을 주도하고 있다고 할 수 있습니다.

시장 억제요인

실제 환경에서 효과적으로 작동하는 AI 애플리케이션을 개발하는 것은 기술적으로나 경제적으로 어려운 일이며, AI 모델을 구축하기 위해서는 데이터 과학자, 머신러닝 엔지니어, 도메인 전문가와 같은 인재에 대한 막대한 투자가 필요하지만, 이러한 인재는 부족하고 고가의 보수가 지급되는 경우가 많습니다. 지급되고 있습니다. 또한, 이 과정에는 정확하고 신뢰할 수 있는 모델 학습에 필수적인 방대한 양의 고품질 데이터 확보와 라벨링이 포함됩니다. 따라서 높은 개발 비용과 AI 애플리케이션을 실생활에 적용하기 위한 확장의 복잡성이 시장 성장을 저해하는 요인으로 작용하고 있습니다.

기능 전망

기능별로 시장은 자연어 처리(NLP), 컴퓨터 비전, 로봇 공학 및 자동화, 예측 분석 및 기계 학습 등으로 분류됩니다. 컴퓨터 비전 분야는 2024년 28%의 시장 점유율을 차지했습니다. 이는 이미지 및 비디오 분석 분야에서 AI의 도입이 확대되고 있기 때문입니다. 컴퓨터 비전 기술은 애플리케이션이 시각 데이터에서 패턴, 물체, 움직임을 인식할 수 있게함으로써 얼굴 인식, 모니터링, 품질 관리, 의료 영상 자동화 등을 가능하게 합니다.

최종 용도 전망

최종 용도별로는 IT 및 통신, BFSI, 에너지 및 유틸리티, 소매 및 E-Commerce, 엔터테인먼트, 자동차, 제조, 금융, 기타로 분류되며, BFSI 부문은 BFSI 년 시장 매출 점유율 16%를 차지했습니다. 이는 위험 평가, 사기 탐지, 고객 지원, 자동화된 금융 자문, AI 기반 챗봇 및 가상 비서 등 AI 도입이 증가함에 따라 은행 및 금융기관의 고객 참여와 업무 효율성을 향상시키는 데 도움이 되고 있습니다.

지역 전망

지역별로는 북미, 유럽, 아시아태평양, 라틴아메리카, 중동 및 아프리카로 시장을 분석했습니다. 유럽 부문은 2024년 시장 수익의 32%를 차지했습니다. 이는 자동차, 헬스케어, 제조 등 주요 부문에서 디지털 전환과 AI 도입에 대한 투자 증가에 힘입은 것으로 분석됩니다. 유럽 국가들은 전략적 정책, 자금 지원 프로그램, 국경 간 협력을 통해 AI 혁신을 적극적으로 지원하고 있습니다.

AI 앱 시장에서는 신생 스타트업과 중견기업 간의 경쟁이 치열해지고 있습니다. 기업들이 틈새 애플리케이션과 고유한 가치 제안을 모색하면서 혁신이 활발해지고 있습니다. 지배적인 세력이 존재하지 않기 때문에 신규 진입 기업은 인지도를 높이고, 투자를 유치하고, 빠르게 사업을 확장할 수 있습니다. 이러한 민주화된 환경은 실험, 민첩성, 그리고 AI 기반 솔루션의 다양성을 촉진합니다.

AI 앱 시장 범위:

보고서 속성 세부 정보

2024년 시장 규모 : 32억 4,000만 달러

2032년 시장 규모 전망 : 438억 5,000만 달러

기준 연도 : 2024년

실적 기간 : 2021-2023년

예측 기간 : 2025-2032년

매출 성장률 CAGR 39.1% : 2025-2032년

페이지 수 276

표 343

조사 범위 : 시장 동향, 수익 예측 및 전망, 세분화 분석, 지역 및 국가별 분석, 경쟁 상황, Porter's Five Forces 분석, 기업 프로파일링, 기업 전략 전개, SWOT 분석, 승리의 필수 요소

대상 부문 기능성, 최종 용도, 지역

대상 국가* 북미(미국, 캐나다, 멕시코, 기타 북미)

  • 유럽(독일, 영국, 프랑스, 러시아, 스페인, 이탈리아, 기타 유럽)
  • 아시아태평양(일본, 중국, 인도, 한국, 싱가포르, 말레이시아, 기타 아시아태평양)
  • 라틴아메리카, 중동 및 아프리카(브라질, 아르헨티나, UAE, 사우디아라비아, 남아프리카공화국, 나이지리아, 기타 라틴아메리카, 중동 및 아프리카)

참여 기업 : IBM Corporation, DataRobot, Inc. Amazon.com, Inc.), NVIDIA Corporation, Oracle Corporation, Adobe, Inc.

목차

제1장 시장 범위와 조사 방법

  • 시장 정의
  • 목적
  • 시장 범위
  • 세분화
  • 조사 방법

제2장 시장 요람

  • 주요 하이라이트

제3장 시장 개요

  • 소개
    • 개요
      • 시장 구성과 시나리오
  • 시장에 영향을 미치는 주요 요인
    • 시장 성장 촉진요인
    • 시장 성장 억제요인
    • 시장 기회
    • 시장 과제

제4장 경쟁 분석 - 세계

  • KBV Cardinal Matrix
  • 최근 업계 전체의 전략적 전개
    • 파트너십, 협업, 계약
    • 제품 발매와 제품 확대
    • 인수와 합병
  • 주요 성공 전략
    • 주요 전략
    • 주요 전략적 활동
  • Porter’s Five Forces 분석

제5장 세계의 AI 앱 시장 : 기능별

  • 세계의 자연어 처리(NLP) 시장 : 지역별
  • 세계의 컴퓨터 비전 시장 : 지역별
  • 세계의 로봇공학과 자동화 시장 : 지역별
  • 세계의 예측 분석과 머신러닝 시장 : 지역별
  • 세계의 기타 기능 시장 : 지역별

제6장 세계의 AI 앱 시장 : 최종 용도별

  • 세계의 IT·통신 시장 : 지역별
  • 세계의 BFSI 시장 : 지역별
  • 세계의 소매·E-Commerce 시장 : 지역별
  • 세계의 에너지·유틸리티 시장 : 지역별
  • 세계의 엔터테인먼트 시장 : 지역별
  • 세계의 자동차 시장 : 지역별
  • 세계의 제조 시장 : 지역별
  • 세계 파이낸스(BFSI를 제외한) 시장 : 지역별
  • 세계의 기타 최종 용도 시장 : 지역별

제7장 세계의 AI 앱 시장 : 지역별

  • 북미
    • 북미의 시장 : 국가별
      • 미국
      • 캐나다
      • 멕시코
      • 기타 북미
  • 유럽
    • 유럽의 시장 : 국가별
      • 독일
      • 영국
      • 프랑스
      • 러시아
      • 스페인
      • 이탈리아
      • 기타 유럽
  • 아시아태평양
    • 아시아태평양의 시장 : 국가별
      • 중국
      • 일본
      • 인도
      • 한국
      • 싱가포르
      • 말레이시아
      • 기타 아시아태평양
  • 라틴아메리카, 중동 및 아프리카
    • 라틴아메리카, 중동 및 아프리카의 시장 : 국가별
      • 브라질
      • 아르헨티나
      • 아랍에미리트
      • 사우디아라비아
      • 남아프리카공화국
      • 나이지리아
      • 기타 라틴아메리카, 중동 및 아프리카

제8장 기업 개요

  • IBM Corporation
  • DataRobot, Inc
  • Salesforce, Inc
  • Google LLC(Alphabet Inc)
  • OpenAI, LL.C
  • Microsoft Corporation
  • Amazon Web Services, Inc(Amazon.com, Inc.)
  • NVIDIA Corporation
  • Oracle Corporation
  • Adobe, Inc

제9장 AI 앱 시장 성공 필수 조건

ksm 25.05.19

The Global AI Apps Market size is expected to reach $43.85 billion by 2032, rising at a market growth of 39.1% CAGR during the forecast period.

The North America segment recorded 34% revenue share in the market in 2024. The strong presence of leading AI companies, advanced digital infrastructure, and high levels of investment in AI research and development supports it. The region's well-established technology ecosystem, particularly in the U.S. and Canada, has fostered the rapid integration of AI applications across various industries, including healthcare, finance, manufacturing, and retail.

The major strategies followed by the market participants are Partnerships as the key developmental strategy to keep pace with the changing demands of end users. For instance, In March, 2025, Oracle Corporation and NVIDIA partnered to accelerate agentic AI app development by integrating NVIDIA AI tools with Oracle Cloud Infrastructure. The collaboration enables no-code deployment, real-time inference, and advanced AI search, supporting enterprise-scale AI applications across industries with enhanced performance and flexibility. Additionally, In September, 2024, Salesforce, Inc. and IBM have partnered to integrate Salesforce's Agentforce autonomous AI agents with IBM's watsonx platform. This collaboration enhances business automation, decision-making, and productivity by enabling organizations, especially in regulated industries-to build and deploy tailored AI agents using enterprise data. These solutions exemplify the evolution and expansion of AI applications across industries.

KBV Cardinal Matrix - AI Apps Market Competition Analysis

Based on the Analysis presented in the KBV Cardinal matrix; Microsoft Corporation, Google LLC, NVIDIA Corporation and Amazon Web Services, Inc. are the forerunners in the AI Apps Market. In January, 2025, Microsoft Corporation and OpenAI extended their partnership through 2030, maintaining API exclusivity on Azure, sharing revenue, and integrating OpenAI models into Microsoft products like Copilot. A new Azure commitment supports OpenAI's research, strengthening both companies' roles in the AI Apps Market. Companies such as Oracle Corporation and Salesforce, Inc. are some of the key innovators in this Market.

Source: KBV Reseaarch and Secondary Research Analysis

Driving and Restraining Factors

Drivers * Smartphone and Device Growth Expanding Access to AI Apps

  • Rising Tech and Startup Investments Driving AI App Innovation
  • Digital Transformation and Cloud Adoption Enabling Scalable AI Deployment

Restraints * High Development Costs and Complexity in Scaling AI Applications for Real-World Use

  • Concerns Over Data Privacy, Security, and Ethical Use of AI Technologies Limiting Adoption

Opportunities * Rise of Low-Code and No-Code Platforms Simplifying AI App Development

  • Government Support and Initiatives Encouraging AI Innovation and Application Across Sectors

Challenges * Constantly Evolving Technology Requiring Continuous Updates and Retraining of AI Applications

  • Integration Difficulties with Legacy Infrastructure in Traditional Industries and Enterprises

Market Growth Factors

The explosive growth of smartphones and connected devices has redefined how users interact with digital platforms. With billions of active mobile users worldwide, AI apps have a ready and ever-expanding audience. From Android to iOS, app developers embed AI features like real-time language translation, intelligent photo sorting, and personalized recommendations, making AI an everyday user experience. Hence, smartphone and device growth and expanding access to AI apps are driving the market's growth.

Additionally, Venture capital and institutional investments in AI-focused startups are accelerating the development of next-generation applications. These funding rounds provide startups with the resources to hire specialized talent, access premium datasets, and experiment with cutting-edge algorithms. As a result, the AI app landscape is experiencing rapid evolution in capability and user experience. In conclusion, rising tech and startup investments driving AI app innovation propel the market's growth.

Market Restraining Factors

Developing AI applications that function effectively in real-world environments is technically challenging and financially demanding. Building AI models requires significant investment in talent-such as data scientists, machine learning engineers, and domain experts-who are often in short supply and command high salaries. Additionally, the process involves sourcing and labelling vast amounts of high-quality data, essential for training accurate and reliable models. Hence, high development costs and complexity in scaling AI applications for real-world use are hindering the market's growth.

Functionality Outlook

Based on functionality, the market is characterized into natural language processing (NLP)s, computer vision, robotics & automation, predictive analytics & machine learning, and others. The computer vision segment procured 28% revenue share in the market in 2024. This is fuelled by the growing implementation of AI in image and video analysis. Computer vision technology empowers applications to recognize patterns, objects, and movements in visual data, enabling facial recognition, surveillance, quality control, and medical imaging automation.

End-use Outlook

By end-use, the market is divided into IT & telecommunications, BFSI, energy & utilities, retail & e-commerce, entertainment, automotive, manufacturing, finance, and others. The BFSI segment garnered 16% revenue share in the market in 2024. Owing to the increasing adoption of AI for risk assessment, fraud detection, customer support, and automated financial advisory. AI-powered chatbots and virtual assistants are helping banks and financial institutions improve customer engagement and operational efficiency.

Regional Outlook

Region-wise, the market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The Europe segment witnessed 32% revenue share in the market in 2024. This is driven by growing investments in digital transformation and the adoption of AI across key sectors such as automotive, healthcare, and manufacturing. European countries actively support AI innovation through strategic policies, funding programs, and cross-border collaborations.

The AI apps market sees intensified competition among emerging startups and mid-sized firms. Innovation thrives as companies explore niche applications and unique value propositions. The absence of dominant forces allows newer entrants to gain visibility, attract investments, and rapidly scale. This democratized landscape fosters experimentation, agility, and a broader diversity of AI-driven solutions.

AI Apps Market Coverage:

Report Attribute Details

Market size value in 2024 USD 3.24 Billion

Market size forecast in 2032 USD 43.85 Billion

Base Year 2024

Historical period 2021 to 2023

Forecast Period 2025 to 2032

Revenue Growth Rate CAGR of 39.1% from 2025 to 2032

Number of Pages 276

Tables 343

Report Coverage Market Trends, Revenue Estimation and Forecast, Segmentation Analysis, Regional and Country Breakdown, Competitive Landscape, Porter's 5 Forces Analysis, Company Profiling, Companies Strategic Developments, SWOT Analysis, Winning Imperatives

Segments Covered Functionality, End-use, Region

Country Scope * North America (US, Canada, Mexico, and Rest of North America)

  • Europe (Germany, UK, France, Russia, Spain, Italy, and Rest of Europe)
  • Asia Pacific (Japan, China, India, South Korea, Singapore, Malaysia, and Rest of Asia Pacific)
  • LAMEA (Brazil, Argentina, UAE, Saudi Arabia, South Africa, Nigeria, and Rest of LAMEA)

Companies Included IBM Corporation, DataRobot, Inc., Salesforce, Inc., Google LLC (Alphabet Inc.), OpenAI, LLC, Microsoft Corporation, Amazon Web Services, Inc. (Amazon.com, Inc.), NVIDIA Corporation, Oracle Corporation, Adobe, Inc.

Recent Strategies Deployed in the Market

  • Apr-2025: NVIDIA Corporation has completed its acquisition of AI startup Lepton AI, which provides cloud-based GPU services. The deal strengthens NVIDIA's position in the AI applications market. Lepton's co-founders, Yangqing Jia and Junjie Bai, will continue with the company post-acquisition.
  • Mar-2025: Adobe, Inc. launched AI-driven innovations for Customer Experience Orchestration, including the Experience Platform Agent Orchestrator, GenStudio enhancements, and expanded Firefly integration. Strategic partnerships and AI agents enable scalable personalization, boosting marketing, content, and enterprise workflows.
  • Mar-2025: DataRobot, Inc. launched AI application suites for finance and supply chain operations integrated with SAP. These pre-built, customizable apps enable rapid AI adoption, real-time insights, and optimized workflows, helping businesses enhance forecasting, reduce risks, and improve operational efficiency across SAP environments.
  • Mar-2025: NVIDIA Corporation expands its Omniverse Physical AI OS with new blueprints and integrations, enabling industrial partners to build AI apps for robotics, manufacturing, and digital twins. Companies like GM, SAP, and Foxconn adopt it to drive large-scale AI application development.
  • Feb-2025: DataRobot, Inc. acquired Agnostiq to boost agentic AI application development and simplify compute orchestration across hybrid environments. Integrating Agnostiq's Covalent platform enables scalable, efficient AI deployments, reducing complexity and costs while enhancing performance, targeting growth in the enterprise AI applications market.

List of Key Companies Profiled

  • IBM Corporation
  • DataRobot, Inc.
  • Salesforce, Inc.
  • Google LLC (Alphabet Inc.)
  • OpenAI, LLC
  • Microsoft Corporation
  • Amazon Web Services, Inc. (Amazon.com, Inc.)
  • NVIDIA Corporation
  • Oracle Corporation
  • Adobe, Inc.

Global AI Apps Market Report Segmentation

By Functionality

  • Natural Language Processing (NLP)s
  • Computer Vision
  • Robotics & Automation
  • Predictive Analytics and Machine Learning
  • Other Functionality

By End-use

  • IT & Telecommunications
  • BFSI
  • Retail & E-commerce
  • Energy & Utilities
  • Entertainment
  • Automotive
  • Manufacturing
  • Finance (Excluding BFSI)
  • Other End-use

By Geography

  • North America
    • US
    • Canada
    • Mexico
    • Rest of North America
  • Europe
    • Germany
    • UK
    • France
    • Russia
    • Spain
    • Italy
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Singapore
    • Malaysia
    • Rest of Asia Pacific
  • LAMEA
    • Brazil
    • Argentina
    • UAE
    • Saudi Arabia
    • South Africa
    • Nigeria
  • Rest of LAMEA

Table of Contents

Chapter 1. Market Scope & Methodology

  • 1.1 Market Definition
  • 1.2 Objectives
  • 1.3 Market Scope
  • 1.4 Segmentation
    • 1.4.1 Global AI Apps Market, by Functionality
    • 1.4.2 Global AI Apps Market, by End-use
    • 1.4.3 Global AI Apps Market, by Geography
  • 1.5 Methodology for the research

Chapter 2. Market at a Glance

  • 2.1 Key Highlights

Chapter 3. Market Overview

  • 3.1 Introduction
    • 3.1.1 Overview
      • 3.1.1.1 Market Composition and Scenario
  • 3.2 Key Factors Impacting the Market
    • 3.2.1 Market Drivers
    • 3.2.2 Market Restraints
    • 3.2.3 Market Opportunities
    • 3.2.4 Market Challenges

Chapter 4. Competition Analysis - Global

  • 4.1 KBV Cardinal Matrix
  • 4.2 Recent Industry Wide Strategic Developments
    • 4.2.1 Partnerships, Collaborations and Agreements
    • 4.2.2 Product Launches and Product Expansions
    • 4.2.3 Acquisition and Mergers
  • 4.3 Top Winning Strategies
    • 4.3.1 Key Leading Strategies: Percentage Distribution (2021-2025)
    • 4.3.2 Key Strategic Move: (Partnerships, Collaborations & Agreements: 2023, Nov - 2025, Mar) Leading Players
  • 4.4 Porter Five Forces Analysis

Chapter 5. Global AI Apps Market by Functionality

  • 5.1 Global Natural Language Processing (NLP)s Market by Region
  • 5.2 Global Computer Vision Market by Region
  • 5.3 Global Robotics & Automation Market by Region
  • 5.4 Global Predictive Analytics and Machine Learning Market by Region
  • 5.5 Global Other Functionality Market by Region

Chapter 6. Global AI Apps Market by End-use

  • 6.1 Global IT & Telecommunications Market by Region
  • 6.2 Global BFSI Market by Region
  • 6.3 Global Retail & E-commerce Market by Region
  • 6.4 Global Energy & Utilities Market by Region
  • 6.5 Global Entertainment Market by Region
  • 6.6 Global Automotive Market by Region
  • 6.7 Global Manufacturing Market by Region
  • 6.8 Global Finance (Excluding BFSI) Market by Region
  • 6.9 Global Other End-use Market by Region

Chapter 7. Global AI Apps Market by Region

  • 7.1 North America AI Apps Market
    • 7.1.1 North America AI Apps Market by Functionality
      • 7.1.1.1 North America Natural Language Processing (NLP)s Market by Country
      • 7.1.1.2 North America Computer Vision Market by Country
      • 7.1.1.3 North America Robotics & Automation Market by Country
      • 7.1.1.4 North America Predictive Analytics and Machine Learning Market by Country
      • 7.1.1.5 North America Other Functionality Market by Country
    • 7.1.2 North America AI Apps Market by End-use
      • 7.1.2.1 North America IT & Telecommunications Market by Country
      • 7.1.2.2 North America BFSI Market by Country
      • 7.1.2.3 North America Retail & E-commerce Market by Country
      • 7.1.2.4 North America Energy & Utilities Market by Country
      • 7.1.2.5 North America Entertainment Market by Country
      • 7.1.2.6 North America Automotive Market by Country
      • 7.1.2.7 North America Manufacturing Market by Country
      • 7.1.2.8 North America Finance (Excluding BFSI) Market by Country
      • 7.1.2.9 North America Other End-use Market by Country
    • 7.1.3 North America AI Apps Market by Country
      • 7.1.3.1 US AI Apps Market
        • 7.1.3.1.1 US AI Apps Market by Functionality
        • 7.1.3.1.2 US AI Apps Market by End-use
      • 7.1.3.2 Canada AI Apps Market
        • 7.1.3.2.1 Canada AI Apps Market by Functionality
        • 7.1.3.2.2 Canada AI Apps Market by End-use
      • 7.1.3.3 Mexico AI Apps Market
        • 7.1.3.3.1 Mexico AI Apps Market by Functionality
        • 7.1.3.3.2 Mexico AI Apps Market by End-use
      • 7.1.3.4 Rest of North America AI Apps Market
        • 7.1.3.4.1 Rest of North America AI Apps Market by Functionality
        • 7.1.3.4.2 Rest of North America AI Apps Market by End-use
  • 7.2 Europe AI Apps Market
    • 7.2.1 Europe AI Apps Market by Functionality
      • 7.2.1.1 Europe Natural Language Processing (NLP)s Market by Country
      • 7.2.1.2 Europe Computer Vision Market by Country
      • 7.2.1.3 Europe Robotics & Automation Market by Country
      • 7.2.1.4 Europe Predictive Analytics and Machine Learning Market by Country
      • 7.2.1.5 Europe Other Functionality Market by Country
    • 7.2.2 Europe AI Apps Market by End-use
      • 7.2.2.1 Europe IT & Telecommunications Market by Country
      • 7.2.2.2 Europe BFSI Market by Country
      • 7.2.2.3 Europe Retail & E-commerce Market by Country
      • 7.2.2.4 Europe Energy & Utilities Market by Country
      • 7.2.2.5 Europe Entertainment Market by Country
      • 7.2.2.6 Europe Automotive Market by Country
      • 7.2.2.7 Europe Manufacturing Market by Country
      • 7.2.2.8 Europe Finance (Excluding BFSI) Market by Country
      • 7.2.2.9 Europe Other End-use Market by Country
    • 7.2.3 Europe AI Apps Market by Country
      • 7.2.3.1 Germany AI Apps Market
        • 7.2.3.1.1 Germany AI Apps Market by Functionality
        • 7.2.3.1.2 Germany AI Apps Market by End-use
      • 7.2.3.2 UK AI Apps Market
        • 7.2.3.2.1 UK AI Apps Market by Functionality
        • 7.2.3.2.2 UK AI Apps Market by End-use
      • 7.2.3.3 France AI Apps Market
        • 7.2.3.3.1 France AI Apps Market by Functionality
        • 7.2.3.3.2 France AI Apps Market by End-use
      • 7.2.3.4 Russia AI Apps Market
        • 7.2.3.4.1 Russia AI Apps Market by Functionality
        • 7.2.3.4.2 Russia AI Apps Market by End-use
      • 7.2.3.5 Spain AI Apps Market
        • 7.2.3.5.1 Spain AI Apps Market by Functionality
        • 7.2.3.5.2 Spain AI Apps Market by End-use
      • 7.2.3.6 Italy AI Apps Market
        • 7.2.3.6.1 Italy AI Apps Market by Functionality
        • 7.2.3.6.2 Italy AI Apps Market by End-use
      • 7.2.3.7 Rest of Europe AI Apps Market
        • 7.2.3.7.1 Rest of Europe AI Apps Market by Functionality
        • 7.2.3.7.2 Rest of Europe AI Apps Market by End-use
  • 7.3 Asia Pacific AI Apps Market
    • 7.3.1 Asia Pacific AI Apps Market by Functionality
      • 7.3.1.1 Asia Pacific Natural Language Processing (NLP)s Market by Country
      • 7.3.1.2 Asia Pacific Computer Vision Market by Country
      • 7.3.1.3 Asia Pacific Robotics & Automation Market by Country
      • 7.3.1.4 Asia Pacific Predictive Analytics and Machine Learning Market by Country
      • 7.3.1.5 Asia Pacific Other Functionality Market by Country
    • 7.3.2 Asia Pacific AI Apps Market by End-use
      • 7.3.2.1 Asia Pacific IT & Telecommunications Market by Country
      • 7.3.2.2 Asia Pacific BFSI Market by Country
      • 7.3.2.3 Asia Pacific Retail & E-commerce Market by Country
      • 7.3.2.4 Asia Pacific Energy & Utilities Market by Country
      • 7.3.2.5 Asia Pacific Entertainment Market by Country
      • 7.3.2.6 Asia Pacific Automotive Market by Country
      • 7.3.2.7 Asia Pacific Manufacturing Market by Country
      • 7.3.2.8 Asia Pacific Finance (Excluding BFSI) Market by Country
      • 7.3.2.9 Asia Pacific Other End-use Market by Country
    • 7.3.3 Asia Pacific AI Apps Market by Country
      • 7.3.3.1 China AI Apps Market
        • 7.3.3.1.1 China AI Apps Market by Functionality
        • 7.3.3.1.2 China AI Apps Market by End-use
      • 7.3.3.2 Japan AI Apps Market
        • 7.3.3.2.1 Japan AI Apps Market by Functionality
        • 7.3.3.2.2 Japan AI Apps Market by End-use
      • 7.3.3.3 India AI Apps Market
        • 7.3.3.3.1 India AI Apps Market by Functionality
        • 7.3.3.3.2 India AI Apps Market by End-use
      • 7.3.3.4 South Korea AI Apps Market
        • 7.3.3.4.1 South Korea AI Apps Market by Functionality
        • 7.3.3.4.2 South Korea AI Apps Market by End-use
      • 7.3.3.5 Singapore AI Apps Market
        • 7.3.3.5.1 Singapore AI Apps Market by Functionality
        • 7.3.3.5.2 Singapore AI Apps Market by End-use
      • 7.3.3.6 Malaysia AI Apps Market
        • 7.3.3.6.1 Malaysia AI Apps Market by Functionality
        • 7.3.3.6.2 Malaysia AI Apps Market by End-use
      • 7.3.3.7 Rest of Asia Pacific AI Apps Market
        • 7.3.3.7.1 Rest of Asia Pacific AI Apps Market by Functionality
        • 7.3.3.7.2 Rest of Asia Pacific AI Apps Market by End-use
  • 7.4 LAMEA AI Apps Market
    • 7.4.1 LAMEA AI Apps Market by Functionality
      • 7.4.1.1 LAMEA Natural Language Processing (NLP)s Market by Country
      • 7.4.1.2 LAMEA Computer Vision Market by Country
      • 7.4.1.3 LAMEA Robotics & Automation Market by Country
      • 7.4.1.4 LAMEA Predictive Analytics and Machine Learning Market by Country
      • 7.4.1.5 LAMEA Other Functionality Market by Country
    • 7.4.2 LAMEA AI Apps Market by End-use
      • 7.4.2.1 LAMEA IT & Telecommunications Market by Country
      • 7.4.2.2 LAMEA BFSI Market by Country
      • 7.4.2.3 LAMEA Retail & E-commerce Market by Country
      • 7.4.2.4 LAMEA Energy & Utilities Market by Country
      • 7.4.2.5 LAMEA Entertainment Market by Country
      • 7.4.2.6 LAMEA Automotive Market by Country
      • 7.4.2.7 LAMEA Manufacturing Market by Country
      • 7.4.2.8 LAMEA Finance (Excluding BFSI) Market by Country
      • 7.4.2.9 LAMEA Other End-use Market by Country
    • 7.4.3 LAMEA AI Apps Market by Country
      • 7.4.3.1 Brazil AI Apps Market
        • 7.4.3.1.1 Brazil AI Apps Market by Functionality
        • 7.4.3.1.2 Brazil AI Apps Market by End-use
      • 7.4.3.2 Argentina AI Apps Market
        • 7.4.3.2.1 Argentina AI Apps Market by Functionality
        • 7.4.3.2.2 Argentina AI Apps Market by End-use
      • 7.4.3.3 UAE AI Apps Market
        • 7.4.3.3.1 UAE AI Apps Market by Functionality
        • 7.4.3.3.2 UAE AI Apps Market by End-use
      • 7.4.3.4 Saudi Arabia AI Apps Market
        • 7.4.3.4.1 Saudi Arabia AI Apps Market by Functionality
        • 7.4.3.4.2 Saudi Arabia AI Apps Market by End-use
      • 7.4.3.5 South Africa AI Apps Market
        • 7.4.3.5.1 South Africa AI Apps Market by Functionality
        • 7.4.3.5.2 South Africa AI Apps Market by End-use
      • 7.4.3.6 Nigeria AI Apps Market
        • 7.4.3.6.1 Nigeria AI Apps Market by Functionality
        • 7.4.3.6.2 Nigeria AI Apps Market by End-use
      • 7.4.3.7 Rest of LAMEA AI Apps Market
        • 7.4.3.7.1 Rest of LAMEA AI Apps Market by Functionality
        • 7.4.3.7.2 Rest of LAMEA AI Apps Market by End-use

Chapter 8. Company Profiles

  • 8.1 IBM Corporation
    • 8.1.1 Company Overview
    • 8.1.2 Financial Analysis
    • 8.1.3 Regional & Segmental Analysis
    • 8.1.4 Research & Development Expenses
    • 8.1.5 Recent strategies and developments:
      • 8.1.5.1 Partnerships, Collaborations, and Agreements:
      • 8.1.5.2 Acquisition and Mergers:
    • 8.1.6 SWOT Analysis
  • 8.2 DataRobot, Inc.
    • 8.2.1 Company Overview
    • 8.2.2 Recent strategies and developments:
      • 8.2.2.1 Partnerships, Collaborations, and Agreements:
      • 8.2.2.2 Product Launches and Product Expansions:
      • 8.2.2.3 Acquisition and Mergers:
    • 8.2.3 SWOT Analysis
  • 8.3 Salesforce, Inc.
    • 8.3.1 Company Overview
    • 8.3.2 Financial Analysis
    • 8.3.3 Regional Analysis
    • 8.3.4 Research & Development Expenses
    • 8.3.5 Recent strategies and developments:
      • 8.3.5.1 Partnerships, Collaborations, and Agreements:
      • 8.3.5.2 Product Launches and Product Expansions:
    • 8.3.6 SWOT Analysis
  • 8.4 Google LLC (Alphabet Inc.)
    • 8.4.1 Company Overview
    • 8.4.2 Financial Analysis
    • 8.4.3 Segmental and Regional Analysis
    • 8.4.4 Research & Development Expenses
    • 8.4.5 Recent strategies and developments:
      • 8.4.5.1 Partnerships, Collaborations, and Agreements:
    • 8.4.6 SWOT Analysis
  • 8.5 OpenAI, L.L.C.
    • 8.5.1 Company Overview
    • 8.5.2 Recent strategies and developments:
      • 8.5.2.1 Partnerships, Collaborations, and Agreements:
    • 8.5.3 SWOT Analysis
  • 8.6 Microsoft Corporation
    • 8.6.1 Company Overview
    • 8.6.2 Financial Analysis
    • 8.6.3 Segmental and Regional Analysis
    • 8.6.4 Research & Development Expenses
    • 8.6.5 Recent strategies and developments:
      • 8.6.5.1 Partnerships, Collaborations, and Agreements:
      • 8.6.5.2 Acquisition and Mergers:
    • 8.6.6 SWOT Analysis
  • 8.7 Amazon Web Services, Inc. (Amazon.com, Inc.)
    • 8.7.1 Company Overview
    • 8.7.2 Financial Analysis
    • 8.7.3 Segmental and Regional Analysis
    • 8.7.4 Recent strategies and developments:
      • 8.7.4.1 Partnerships, Collaborations, and Agreements:
      • 8.7.4.2 Product Launches and Product Expansions:
    • 8.7.5 SWOT Analysis
  • 8.8 NVIDIA Corporation
    • 8.8.1 Company Overview
    • 8.8.2 Financial Analysis
    • 8.8.3 Segmental and Regional Analysis
    • 8.8.4 Research & Development Expenses
    • 8.8.5 Recent strategies and developments:
      • 8.8.5.1 Partnerships, Collaborations, and Agreements:
      • 8.8.5.2 Acquisition and Mergers:
    • 8.8.6 SWOT Analysis
  • 8.9 Oracle Corporation
    • 8.9.1 Company Overview
    • 8.9.2 Financial Analysis
    • 8.9.3 Segmental and Regional Analysis
    • 8.9.4 Research & Development Expense
    • 8.9.5 Recent strategies and developments:
      • 8.9.5.1 Partnerships, Collaborations, and Agreements:
      • 8.9.5.2 Product Launches and Product Expansions:
    • 8.9.6 SWOT Analysis
  • 8.10. Adobe, Inc.
    • 8.10.1 Company Overview
    • 8.10.2 Financial Analysis
    • 8.10.3 Segmental and Regional Analysis
    • 8.10.4 Research & Development Expense
    • 8.10.5 Recent strategies and developments:
      • 8.10.5.1 Product Launches and Product Expansions:
    • 8.10.6 SWOT Analysis

Chapter 9. Winning Imperatives of AI Apps Market

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