세계의 AI 추론 PaaS 시장 : 전개별, 용도별, 업계별, 지역별 - 예측(-2030년)
AI Inference Platform-as-a-Service Market by Deployment, Application, Vertical, Region - Global Forecast to 2030
상품코드:1836424
리서치사:MarketsandMarkets
발행일:2025년 10월
페이지 정보:영문 303 Pages
라이선스 & 가격 (부가세 별도)
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한글목차
세계 AI 추론 PaaS 시장 규모는 2025년에 188억 4,000만 달러, 2030년까지 1,052억 2,000만 달러에 이르고, 예측기간 동안 CAGR 41.1%로 성장할 전망입니다.
시장은 실시간 의사결정에 대한 요구가 증가하고 AI 추론과 특정 업계를 위한 SaaS 플랫폼 간의 통합이 진행됨에 따라 강력한 성장을 보여줍니다.
조사 범위
조사 대상 연도
2021-2030년
기준 연도
2024년
예측 기간
2025-2030년
단위
100만 달러
부문
배포, 용도, 산업, 지역
대상 지역
북미, 유럽, 아시아태평양 및 기타 지역
금융, 소매, 의료 등의 부문에서는 사기 탐지, 고객 참여, 임상 의사 결정 지원의 향상에 실시간 인사이트가 활용되고 있으며, 확장 가능한 추론 서비스의 채택이 진행되고 있습니다. 동시에 추론 기능을 SaaS 서비스에 통합함으로써 기업은 대규모 인프라 투자 없이 맞춤형 AI 솔루션을 활용할 수 있습니다. 이러한 동향은 획득 가능한 시장 규모를 확대하고 AI 추론 PaaS를 디지털 전환의 핵심으로 자리매김하고 있습니다.
"프라이빗 클라우드 부문이 2025년부터 2030년까지 두 번째로 높은 CAGR을 나타낼 것으로 예측됩니다."
프라이빗 클라우드 부문은 기업의 데이터 보안, 컴플라이언스 및 맞춤형 인프라에 대한 수요가 증가함에 따라 예측 기간 동안 AI 추론 PaaS 시장에서 두 번째로 높은 CAGR을 나타낼 전망입니다. BFSI, 의료, 정부 등의 부서는 엄격한 규제 프레임워크와 데이터의 기밀성으로 인해 프라이빗 클라우드 배포를 선호합니다. 프라이빗 클라우드의 AI 추론을 통해 기업은 데이터를 완벽하게 제어하고, 대기 시간을 줄이고, 전용 리소스로 높은 성능을 얻을 수 있습니다. 공급업체는 확장성과 거버넌스를 결합한 하이브리드 클라우드 및 프라이빗 클라우드를 제공하여 기업이 대규모 언어 모델(LLM)과 머신러닝 워크로드를 안전하게 배포할 수 있도록 지원합니다. 게다가 유럽과 아시아태평양에서는 국가적 인공지능의 채택이 증가하고 있으며, 사설 클라우드 기반 추론 플랫폼에 대한 수요가 더욱 증가하고 있습니다.
"머신러닝 부문이 2025년 AI 추론 PaaS 시장에서 큰 점유율을 차지할 전망입니다."
금융, 의료, 소매, 제조 등의 최종 용도 업계에서 널리 채택되고 있기 때문에 머신러닝 부문이 2025년에 큰 시장 점유율을 차지할 가능성이 높습니다. 기업은 예측 분석, 사기 감지, 고객 개인화 및 비즈니스 최적화에 머신러닝 알고리즘을 활용하여 확장 가능한 추론 솔루션에 대한 안정적인 수요를 창출하고 있습니다. 실시간 추론, 자동 모델 배포 및 비용 효율적인 확장성을 지원하는 PaaS의 기능은 머신러닝 용도에 적합한 선택입니다. 또한 학습된 모델, API 및 관리형 인프라를 클라우드 플랫폼에서 사용할 수 있어 중소기업 및 스타트업 진입 장벽이 낮아지고 있습니다.
"유럽이 2025년에 큰 시장 점유율을 차지할 것으로 예측됩니다."
유럽은 첨단 디지털 인프라, AI 기술 채택 증가, 국가적 AI 구상 투자 증가 등에 힘입어 2025년 AI 추론 PaaS 시장에서 확고한 지위를 차지할 것으로 예측됩니다. 영국, 독일, 프랑스 등의 국가들은 특히 BFSI, 자동차, 의료 등 산업에서 AI 채택을 선도하고 있습니다. 특히 GDPR(EU 개인정보보호규정) 하에서의 데이터 프라이버시와 컴플라이언스의 중요성은 안전한 현지화된 추론 플랫폼에 대한 수요를 형성하고 있으며, 세계 기업과 현지 클라우드 제공업체는 이러한 요구 사항에 맞는 서비스를 확대하고 있습니다. 유럽의 성장은 클라우드 인프라에 대한 대규모 투자와 하이퍼스케일러와 유럽 기관 간의 파트너십을 통해 촉진되고 있습니다.
이 보고서는 세계 AI 추론 PaaS 시장에 대한 조사 분석을 통해 주요 촉진요인과 억제요인, 경쟁 구도, 미래 동향 등의 정보를 제공합니다.
목차
제1장 서론
제2장 조사 방법
제3장 주요 요약
제4장 중요한 지견
AI 추론 PaaS 시장에서 기업에게 매력적인 기회
AI 추론 PaaS 시장 : 전개별, 용도별
AI 추론 PaaS 시장 : 업계별
AI 추론 PaaS 시장 : 지역별
제5장 시장 개요
소개
시장 역학
성장 촉진요인
억제요인
기회
과제
고객사업에 영향을 주는 동향/혼란
밸류체인 분석
생태계 분석
투자 및 자금조달 시나리오
Porter's Five Forces 분석
주요 이해관계자와 구매 기준
특허 분석
규제 상황
규제기관, 정부기관, 기타 조직
규제
표준
가격 설정 분석
주요 기업이 제공하는 AI 추론 PaaS의 가격대 : 전개별(2024년)
AI 추론 PaaS의 평균 판매가격 : 용도별(2024년)
기술 분석
주요 기술
보완 기술
인접 기술
사례 연구 분석
주요 컨퍼런스 및 이벤트(2025년-2026년)
AI 추론 PaaS 시장에 대한 2025년 미국 관세의 영향
소개
가격의 영향 분석
주요 관세율
국가/지역에 미치는 영향
업계에 미치는 영향
제6장 AI 추론 PaaS 시장 : 전개별
소개
퍼블릭 클라우드
프라이빗 클라우드
하이브리드 클라우드
제7장 AI 추론 PaaS 시장 : 용도별
소개
생성형 AI
머신러닝
자연언어처리
컴퓨터 비전
제8장 AI 추론 PaaS 시장 : 업계별
소개
의료
BFSI
자동차
소매 및 E-Commerce
미디어 및 엔터테인먼트
정부 및 방위
IT 및 통신
기타 산업
제9장 AI 추론 PaaS 시장 : 지역별
소개
북미
북미의 거시경제 전망
미국
캐나다
멕시코
유럽
유럽의 거시 경제 전망
독일
영국
프랑스
이탈리아
스페인
폴란드
북유럽
기타 유럽
아시아태평양
아시아태평양의 거시 경제 전망
중국
한국
일본
인도
호주
인도네시아
말레이시아
태국
베트남
기타 아시아태평양
기타 지역
기타 지역의 거시 경제 전망
남미
아프리카
중동
제10장 경쟁 구도
개요
주요 참가 기업의 전략/강점(2021년-2025년)
수익 분석(2021년-2024년)
시장 점유율 분석(2024년)
기업 평가 및 재무 지표
브랜드 비교
기업 평가 매트릭스 : 주요 기업(2024년)
기업의 평가 매트릭스 : 스타트업/중소기업(2024년)
경쟁 시나리오
제11장 기업 프로파일
주요 기업
MICROSOFT
AMAZON WEB SERVICES, INC.
GOOGLE CLOUD
ORACLE
IBM
ALIBABA CLOUD
SALESFORCE, INC.
TENCENT CLOUD
BAIDU, INC.
TOGETHER AI
기타 기업
COREWEAVE
PREDIBASE
VECTARA
PREM AI
BASETEN
C3.AI, INC.
CLOUDFLARE, INC.
XFERENCE SRL
H2O.AI
DATAROBOT, INC
CEREBRAS
CLOUDERA, INC.
GROQ, INC.
SAMBANOVA, INC.
LATENT AI
MODULAR INC
FIREWORKS AI, INC.
DEEP INFRA
REPLICATE
ANYSCALE, INC
FEATHERLESS.AI
RAFAY SYSTEMS, INC.
제12장 부록
SHW
영문 목차
영문목차
The AI inference PaaS market is projected to reach USD 18.84 billion in 2025 and USD 105.22 billion by 2030, recording a CAGR of 41.1% during the forecast period. The market is witnessing strong growth fueled by the rising need for real-time decision-making and the increasing integration of AI inference with industry-specific SaaS platforms.
Scope of the Report
Years Considered for the Study
2021-2030
Base Year
2024
Forecast Period
2025-2030
Units Considered
Value (USD Million)
Segments
By Deployment, Application, Vertical and Region
Regions covered
North America, Europe, APAC, RoW
Sectors such as finance, retail, and healthcare leverage real-time insights to improve fraud detection, customer engagement, and clinical decision support, driving adoption of scalable inference services. At the same time, embedding inference capabilities into SaaS offerings allows enterprises to unlock tailored AI solutions without heavy infrastructure investments. These trends are expanding the addressable market and positioning AI inference PaaS as a core enabler of digital transformation.
"Private cloud segment is projected to record the second-highest CAGR between 2025 and 2030"
The private cloud segment is expected to grow at the second-highest CAGR in the AI inference PaaS market during the forecast period, driven by the increasing demand for data security, compliance, and customized infrastructure among enterprises. Sectors such as BFSI, healthcare, and government prioritize private cloud deployments due to strict regulatory frameworks and the data sensitivity involved. AI inference on private clouds allows organizations to retain full control over data, reduce latency, and achieve high performance with dedicated resources. Vendors are responding with hybrid and private cloud offerings that combine scalability with governance, enabling enterprises to deploy large language models (LLMs) and machine learning workloads securely. Moreover, the rising adoption of sovereign AI initiatives in Europe and Asia-Pacific further strengthens demand for private cloud-based inference platforms.
"Machine learning segment is expected to hold a major share of the AI inference PaaS market in 2025"
The machine learning segment is likely to account for a significant share of the AI inference PaaS market in 2025, driven by its widespread adoption across end-use industries, such as finance, healthcare, retail, and manufacturing. Enterprises increasingly leverage machine learning algorithms for predictive analytics, fraud detection, customer personalization, and operational optimization, creating steady demand for scalable inference solutions. The ability of PaaS offerings to support real-time inference, automated model deployment, and cost-efficient scalability makes them a preferred choice for machine learning applications. Furthermore, the availability of pre-trained models, APIs, and managed infrastructure on cloud platforms is lowering entry barriers for SMEs and startups.
"Europe is anticipated to hold a significant market share in 2025"
Europe is projected to hold a strong position in the AI inference PaaS market in 2025, supported by advanced digital infrastructure, rising adoption of AI technologies, and increasing investments in sovereign AI initiatives. Countries such as the UK, Germany, and France are leading in AI adoption across industries, particularly in BFSI, automotive, and healthcare. The emphasis on data privacy and compliance, especially under GDPR, shapes the demand for secure and localized inference platforms, with global players and regional cloud providers expanding offerings tailored to these requirements. Growth in Europe is also driven by significant investments in cloud infrastructure and partnerships between hyperscalers and European institutions. In May 2024, Amazon announced major investments to expand cloud operations and a European sovereign cloud project, directly enhancing local compute capacity and enabling enterprises to access compliant inference services within the region. This move reflects a broader trend of hyperscalers localizing infrastructure to address Europe's sovereignty concerns. Alongside Amazon, Microsoft Azure, and Google Cloud are strengthening their European presence, while local providers, such as OVHcloud and Deutsche Telekom, are capturing enterprises prioritizing domestic hosting and trusted AI deployment.
Extensive primary interviews were conducted with key industry experts in the AI inference PaaS market space to determine and verify the market size for various segments and subsegments gathered through secondary research. The breakdown of primary participants for the report is shown below.
The study contains insights from various industry experts, from component suppliers to Tier 1 companies and OEMs. The break-up of the primaries is as follows:
By Company Type: Tier 1 - 50%, Tier 2 - 30%, and Tier 3 - 20%
By Designation: C-level Executives - 20%, Directors - 30%, and Others - 50%
By Region: North America - 40%, Europe - 20%, Asia Pacific- 30%, and RoW - 10%
The AI inference PaaS market is dominated by a few globally established players, such as Microsoft (US), Amazon Web Services, Inc. (US), Google Cloud (US), Oracle (US), IBM (US), Alibaba Cloud (China), Salesforce, Inc. (US), Tencent Cloud (China), Baidu, Inc. (China), Together AI (US), CoreWeave (US), Predibase (US), Vectara (US), Prem AI (US), and Baseten (China), among others. The study includes an in-depth competitive analysis of these key players in the AI inference PaaS market and their company profiles, recent developments, and key market strategies.
Research Coverage:
The report segments the AI inference PaaS market based on deployment (public cloud, private cloud, and hybrid cloud), application (generative AI, machine learning, natural language processing, and computer vision), and vertical (healthcare, BFSI, automotive, retail & e-commerce, media & entertainment, government & defense, IT & telecom, and other verticals). It also discusses the market's drivers, restraints, opportunities, and challenges. It gives a detailed view of the market across four main regions (North America, Europe, Asia Pacific, and RoW). The report includes an ecosystem analysis of key players.
Key Benefits of Buying the Report:
Analysis of key drivers (surging adoption of generative AI and large language models, increasing preference for cloud-native AI architectures, rising need for real-time decision making), restraints (high cost of AI accelerators and service pricing volatility, vendor lock-in concerns, data privacy and regulatory restrictions), opportunities (availability of on-demand inference for SMEs and startups, rise in sovereign AI and regional cloud partnerships, integration of AI inference platforms with industry-specific SaaS solutions), challenges (latency and bandwidth issues in cloud-only setups, complexities in managing AI models in dynamic production environments)
Service Development/Innovation: Detailed insights on upcoming technologies, research and development activities, and new launches in the AI inference PaaS market
Market Development: Comprehensive information about lucrative markets through the analysis of the AI inference PaaS market across varied regions
Market Diversification: Exhaustive information about new products and services, untapped geographies, recent developments, and investments in the AI inference PaaS market
Competitive Assessment: In-depth assessment of market shares, growth strategies, and product offerings of leading players, such as Microsoft (US), Amazon Web Services, Inc. (US), Google Cloud (US), Oracle (US), IBM (US), Alibaba Cloud (China), Salesforce, Inc. (US), Tencent Cloud (China), Baidu, Inc. (China), and Together AI (US)
TABLE OF CONTENTS
1 INTRODUCTION
1.1 STUDY OBJECTIVES
1.2 MARKET DEFINITION
1.3 STUDY SCOPE
1.3.1 MARKETS COVERED AND REGIONAL SCOPE
1.3.2 INCLUSIONS AND EXCLUSIONS
1.3.3 YEARS CONSIDERED
1.4 CURRENCY CONSIDERED
1.5 LIMITATIONS
1.6 STAKEHOLDERS
2 RESEARCH METHODOLOGY
2.1 RESEARCH DATA
2.1.1 SECONDARY DATA
2.1.1.1 List of key secondary sources
2.1.1.2 Key data from secondary sources
2.1.2 PRIMARY DATA
2.1.2.1 List of primary interview participants
2.1.2.2 Breakdown of primaries
2.1.2.3 Key data from primary sources
2.1.2.4 Key industry insights
2.1.3 SECONDARY AND PRIMARY RESEARCH
2.2 MARKET SIZE ESTIMATION
2.2.1 BOTTOM-UP APPROACH
2.2.1.1 Approach to arrive at market size using bottom-up analysis (demand side)
2.2.2 TOP-DOWN APPROACH
2.2.2.1 Approach to arrive at market size using top-down analysis (supply side)
2.3 MARKET BREAKDOWN AND DATA TRIANGULATION
2.4 RESEARCH ASSUMPTIONS
2.5 RESEARCH LIMITATIONS
2.6 RISK ANALYSIS
3 EXECUTIVE SUMMARY
4 PREMIUM INSIGHTS
4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN AI INFERENCE PAAS MARKET
4.2 AI INFERENCE PAAS MARKET, BY DEPLOYMENT AND APPLICATION
4.3 AI INFERENCE PAAS MARKET, BY VERTICAL
4.4 AI INFERENCE PAAS MARKET, BY GEOGRAPHY
5 MARKET OVERVIEW
5.1 INTRODUCTION
5.2 MARKET DYNAMICS
5.2.1 DRIVERS
5.2.1.1 Surging adoption of generative AI and large language models
5.2.1.2 Increasing preference for cloud-native AI architectures
5.2.1.3 Rising need for real-time decision making
5.2.2 RESTRAINTS
5.2.2.1 High cost of AI accelerators and service pricing volatility
5.2.2.2 Vendor lock-in concerns
5.2.2.3 Data privacy and regulatory restrictions
5.2.3 OPPORTUNITIES
5.2.3.1 Availability of on-demand inference for SMEs and startups
5.2.3.2 Rise in sovereign AI and regional cloud partnerships
5.2.3.3 Integration of AI inference platforms with industry-specific SaaS solutions
5.2.4 CHALLENGES
5.2.4.1 Latency and bandwidth issues in cloud-only setups
5.2.4.2 Complexities in managing AI models in dynamic production environments
5.3 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
5.4 VALUE CHAIN ANALYSIS
5.5 ECOSYSTEM ANALYSIS
5.6 INVESTMENT AND FUNDING SCENARIO
5.7 PORTER'S FIVE FORCES ANALYSIS
5.7.1 INTENSITY OF COMPETITIVE RIVALRY
5.7.2 BARGAINING POWER OF SUPPLIERS
5.7.3 BARGAINING POWER OF BUYERS
5.7.4 THREAT OF SUBSTITUTES
5.7.5 THREAT OF NEW ENTRANTS
5.8 KEY STAKEHOLDERS AND BUYING CRITERIA
5.8.1 KEY STAKEHOLDERS IN BUYING PROCESS
5.8.2 BUYING CRITERIA
5.9 PATENT ANALYSIS
5.10 REGULATORY LANDSCAPE
5.10.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
5.10.2 REGULATIONS
5.10.3 STANDARDS
5.11 PRICING ANALYSIS
5.11.1 PRICING RANGE OF AI INFERENCE PAAS OFFERED BY KEY PLAYERS, BY DEPLOYMENT, 2024
5.11.2 AVERAGE SELLING PRICE OF AI INFERENCE PAAS, BY APPLICATION, 2024
5.12 TECHNOLOGY ANALYSIS
5.12.1 KEY TECHNOLOGIES
5.12.1.1 Machine learning
5.12.1.2 Cloud computing
5.12.2 COMPLEMENTARY TECHNOLOGIES
5.12.2.1 Big data analytics
5.12.3 ADJACENT TECHNOLOGIES
5.12.3.1 High-performance computing (HPC)
5.13 CASE STUDY ANALYSIS
5.13.1 FORETHOUGHT OPTIMIZES AI INFERENCE AND SCALABILITY USING AWS SAGEMAKER
5.13.2 DOCUSIGN BOOSTS PRODUCTIVITY USING NVIDIA TRITON INFERENCE SERVER ON AZURE
5.13.3 SMEG UK LTD DELIVERS SMARTER CUSTOMER SERVICE THROUGH ORACLE GENERATIVE AI SOLUTIONS
5.13.4 CERN BUILDS LARGE-SCALE AI MODELS FOR SCIENTIFIC DISCOVERY USING OCI DATA SCIENCE
5.13.5 FIREWORKS AI BOOSTS AI MODEL PERFORMANCE WITH OCI AI INFRASTRUCTURE
5.14 KEY CONFERENCES AND EVENTS, 2025-2026
5.15 IMPACT OF 2025 US TARIFF ON AI INFERENCE PAAS MARKET
5.15.1 INTRODUCTION
5.15.2 PRICE IMPACT ANALYSIS
5.15.3 KEY TARIFF RATES
5.15.4 IMPACT ON COUNTRIES/REGIONS
5.15.4.1 US
5.15.4.2 Europe
5.15.4.3 Asia Pacific
5.15.5 IMPACT ON VERTICALS
6 AI INFERENCE PAAS MARKET, BY DEPLOYMENT
6.1 INTRODUCTION
6.2 PUBLIC CLOUD
6.2.1 RISING ADOPTION OF GEN AI AND LARGE LANGUAGE MODELS ACROSS INDUSTRIES TO ACCELERATE SEGMENTAL GROWTH
6.3 PRIVATE CLOUD
6.3.1 GROWING FOCUS ON ENTERPRISE CONTROL AND INTELLECTUAL PROPERTY PROTECTION TO FUEL SEGMENTAL GROWTH
6.4 HYBRID CLOUD
6.4.1 INCREASING COMPLEXITY OF AI WORKLOADS TO CONTRIBUTE TO SEGMENTAL GROWTH
7 AI INFERENCE PAAS MARKET, BY APPLICATION
7.1 INTRODUCTION
7.2 GENERATIVE AI
7.2.1 RULE-BASED MODELS
7.2.1.1 Strong focus on operational efficiency, governance, and regulatory compliance to bolster segmental growth
7.2.2 STATISTICAL MODELS
7.2.2.1 Increasing need for low-latency, real-time predictions to foster segmental growth
7.2.3 DEEP LEARNING
7.2.3.1 Rapid advances in hardware, optimized serving frameworks, and access to pre-trained models and repositories to drive market
7.2.4 GENERATIVE ADVERSARIAL NETWORKS (GANS)
7.2.4.1 Mounting demand for synthetic content, creative AI applications, and high-fidelity simulation environments to fuel segmental growth
7.2.5 AUTOENCODERS
7.2.5.1 Rise in fraud detection and cybersecurity use cases to boost segmental growth
7.2.6 CONVOLUTIONAL NEURAL NETWORKS (CNNS)
7.2.6.1 Increasing adoption of visual AI across industries to contribute to segmental growth
7.2.7 TRANSFORMER MODELS
7.2.7.1 Growing demand for contextual AI and LLM-based productivity tools to augment segmental growth
7.3 MACHINE LEARNING
7.3.1 INCREASING AVAILABILITY OF STRUCTURED AND UNSTRUCTURED DATA TO ACCELERATE SEGMENTAL GROWTH
7.4 NATURAL LANGUAGE PROCESSING
7.4.1 RISING ADOPTION OF CHATBOTS, VOICE ASSISTANTS, AND TEXT ANALYTICS TO BOLSTER SEGMENTAL GROWTH
7.5 COMPUTER VISION
7.5.1 MOUNTING DEMAND FOR AUTOMATION OF SURVEILLANCE, MANUFACTURING, AND HEALTHCARE TO FUEL SEGMENTAL GROWTH
8 AI INFERENCE PAAS MARKET, BY VERTICAL
8.1 INTRODUCTION
8.2 HEALTHCARE
8.2.1 GROWING FOCUS ON COST-EFFICIENT CLINICAL WORKFLOWS AND DIGITAL HEALTH TO BOOST SEGMENTAL GROWTH
8.3 BFSI
8.3.1 RISING EMPHASIS ON REAL-TIME FRAUD DETECTION AND RISK ASSESSMENT TO FUEL SEGMENTAL GROWTH
8.4 AUTOMOTIVE
8.4.1 MOUNTING DEMAND FOR CONNECTED, AUTONOMOUS, AND ELECTRIC VEHICLE TECHNOLOGIES TO DRIVE MARKET
8.5 RETAIL & E-COMMERCE
8.5.1 INCREASING ADOPTION OF AI-DRIVEN MARKETING AND SALES ANALYTICS TO CONTRIBUTE TO SEGMENTAL GROWTH
8.6 MEDIA & ENTERTAINMENT
8.6.1 ESCALATING DIGITAL CONTENT CONSUMPTION TO ACCELERATE SEGMENTAL GROWTH
8.7 GOVERNMENT & DEFENSE
8.7.1 INCREASING INVESTMENT IN MODERNIZATION AND SOVEREIGN AI INITIATIVES TO FOSTER SEGMENTAL GROWTH
8.8 IT & TELECOM
8.8.1 RISING NEED TO OPTIMIZE INTERNAL OPERATIONS AND DELIVER INTELLIGENT SERVICES TO BOLSTER SEGMENTAL GROWTH
8.9 OTHER VERTICALS
9 AI INFERENCE PAAS MARKET, BY REGION
9.1 INTRODUCTION
9.2 NORTH AMERICA
9.2.1 MACROECONOMIC OUTLOOK FOR NORTH AMERICA
9.2.2 US
9.2.2.1 Rising deployment of AI-powered applications in industries to boost market growth
9.2.3 CANADA
9.2.3.1 Increasing government investment in compute infrastructure to accelerate market growth
9.2.4 MEXICO
9.2.4.1 Strong focus on building data center cluster to meet surging demand for enterprise cloud services to drive market
9.3 EUROPE
9.3.1 MACROECONOMIC OUTLOOK FOR EUROPE
9.3.2 GERMANY
9.3.2.1 Mounting demand for intelligent, scalable, and locally compliant platforms in manufacturing sectors to augment market growth
9.3.3 UK
9.3.3.1 Rising implementation of policies to strengthen compute capacity and enhance digital sovereignty to fuel market growth
9.3.4 FRANCE
9.3.4.1 Growing emphasis on scaling compute resources and strengthening data sovereignty to bolster market growth
9.3.5 ITALY
9.3.5.1 Increasing investment in sovereign compute infrastructure to contribute to market growth
9.3.6 SPAIN
9.3.6.1 Government-backed digital transformation initiatives to accelerate market growth
9.3.7 POLAND
9.3.7.1 Strategic investments in compute infrastructure and government-led digitalization to support market growth
9.3.8 NORDICS
9.3.8.1 High commitment to sustainable digital infrastructure and advanced connectivity to boost market growth
9.3.9 REST OF EUROPE
9.4 ASIA PACIFIC
9.4.1 MACROECONOMIC OUTLOOK FOR ASIA PACIFIC
9.4.2 CHINA
9.4.2.1 Large-scale AI adoption and strategic investments in computing infrastructure to contribute to market growth
9.4.3 SOUTH KOREA
9.4.3.1 Rapid digital transformation and rise of industry-leading technology firms to foster market growth
9.4.4 JAPAN
9.4.4.1 Large-scale investments in AI platforms to accelerate market growth
9.4.5 INDIA
9.4.5.1 Booming startup ecosystem and government-led digital initiatives to fuel market growth
9.4.6 AUSTRALIA
9.4.6.1 Robust cloud infrastructure and growing ecosystem of AI adopters to bolster market growth
9.4.7 INDONESIA
9.4.7.1 Increasing digital-first population and integration of AI into core industries to augment market growth
9.4.8 MALAYSIA
9.4.8.1 Expanding data center footprint to expedite market growth
9.4.9 THAILAND
9.4.9.1 Growing focus on digital sovereignty and data localization to bolster market growth
9.4.10 VIETNAM
9.4.10.1 Proliferating infrastructure investment and strong ecosystem of digital infrastructure to foster market growth
9.4.11 REST OF ASIA PACIFIC
9.5 ROW
9.5.1 MACROECONOMIC OUTLOOK FOR ROW
9.5.2 SOUTH AMERICA
9.5.2.1 Growing demand for scalable and cost-effective solutions to support digital transformation to drive market
9.5.3 AFRICA
9.5.3.1 South Africa
9.5.3.1.1 AI-driven transformation in healthcare and e-commerce sectors to accelerate market growth
9.5.3.2 Other African countries
9.5.4 MIDDLE EAST
9.5.4.1 Bahrain
9.5.4.1.1 Robust digital infrastructure and progressive regulatory environment to augment market growth
9.5.4.2 Kuwait
9.5.4.2.1 Increasing investment in digital infrastructure and government support for technological innovation to drive market
9.5.4.3 Oman
9.5.4.3.1 Strong commitment to diversifying the economy and enhancing technological capabilities to foster market growth
9.5.4.4 Qatar
9.5.4.4.1 Innovative smart city initiatives and commitment to digital transformation to accelerate market growth
9.5.4.5 Saudi Arabia
9.5.4.5.1 Increasing investment in AI infrastructure and focus on digital transformation to expedite market growth
9.5.4.6 UAE
9.5.4.6.1 Rising deployment of AI to enhance operational efficiency to contribute to market growth
9.5.4.7 Rest of Middle East
10 COMPETITIVE LANDSCAPE
10.1 OVERVIEW
10.2 KEY PLAYER STRATEGIES/RIGHT TO WIN, 2021-2025
10.3 REVENUE ANALYSIS, 2021-2024
10.4 MARKET SHARE ANALYSIS, 2024
10.5 COMPANY VALUATION AND FINANCIAL METRICS
10.6 BRAND COMPARISON
10.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2024
10.7.1 STARS
10.7.2 EMERGING LEADERS
10.7.3 PERVASIVE PLAYERS
10.7.4 PARTICIPANTS
10.7.5 COMPANY FOOTPRINT: KEY PLAYERS, 2024
10.7.5.1 Company footprint
10.7.5.2 Region footprint
10.7.5.3 Deployment footprint
10.7.5.4 Application footprint
10.7.5.5 Vertical footprint
10.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2024
