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レポート概要
| 本調査レポートでは、世界のサービスとしての人工知能市場について調査し、イントロダクション、調査手法、エグゼクティブサマリー、市場動向、展開方式別（パブリック、プライベート、ハイブリッド）分析、組織規模別（中小企業、大企業）分析、産業別（金融、小売り、医療、IT・通信、製造）分析、地域別分析、競争状況、投資分析、市場機会・将来動向など、以下の構成でお届けいたします。 ・イントロダクション ・調査手法 ・エグゼクティブサマリー ・市場動向 ・世界のサービスとしての人工知能市場規模：展開方式別（パブリック、プライベート、ハイブリッド） ・世界のサービスとしての人工知能市場規模：組織規模別（中小企業、大企業） ・世界のサービスとしての人工知能市場規模：産業別（金融、小売り、医療、IT・通信、製造） ・世界のサービスとしての人工知能市場規模：地域別 ・競争状況 ・投資分析 ・市場機会・将来動向 |
The global Artificial Intelligence-as-a-Service market was valued at USD 3.91 billion in 2020, and it is expected to reach USD 43.298 billion by 2026, registering a CAGR of 48.9% during the period of 2021-2026. With the increasing number of enterprises and competition among them, companies are rigorously trying to integrate artificial intelligence (AI) technology to their application, business, analytics, and services.
– Moreover, companies are trying to reduce their operational cost to increase profit margins, due to which Artificial Intelligence-as-a-Service (AIaaS) is gaining more prominence over the cloud. Notably, companies are more interested in cloud-based machine learning, which helps in experimenting with their offerings.
– The rising trend of multi-cloud functioning and growing need for cloud-based intelligence services are also increasing the demand for AI as a service. According to IBM, by 2021, 98% of the organization’s plan will adopt multi-cloud architectures, with only 41% having a multi-cloud management strategy and just 38% having procedures and tools to operate a multi-cloud environment. This creates a massive opportunity for AI services.
– Many government organizations, especially in emerging economies, are also understanding the benefits and power of AI; hence, they are extensively promoting AI-based infrastructure development. For instance, Niti Aayog in India launched a national program on AI, including R&D, with increased budget allocation for Digital India, to promote AI, machine learning, 3D printing, and other technologies.
– In addition, the companies are launching services associated with testing AI services. For instance, in April 2019, Google Cloud Platform started offering AI creators a new, shared, end-to-end environment for teams to test, train, and deploy models called the AI Platform. The company also upgraded its AutoML, a service for automating the creation of custom AI models.
– The outbreak of the COVID-19 pandemic has significantly affected several industries and markets globally. COVID-19 has overwhelmed customer service departments. It has impacted the customer experience, made callers less patient, and stressed out many call center agents. The demand for AI Infrastructure as a service has been gaining traction during the pandemic. AI and genomic studies are one essential tool in combating the pandemic.
Key Market Trends
BFSI is Expected to Occupy the Highest Share
– In recent years, AI technology has been increasingly adopted in the BFSI industry, primarily to enhance operational efficiency and enable rich consumer experience. AI is at the forefront of all innovations and will continue to remain so in 2020.
– In the BFSI industry, AI is mainly used as chatbots, algorithmic trading, fraud detection, and customer recommendation. Banks, such as RBS, are implementing chatbots, which is likely to compel other financial institutions to invest in similar technology. As a result, it is expected to create demand for AI-based solutions, which, in turn, is expected to boost the investment by the industry players, thereby, fostering the market growth, over the next six years.
– Artificial intelligence in finance can act as a powerful ally when it comes to analysing real-time activities in any environment. The accurate predictions and forecasts that it provides are based on multiple variables, vital to business planning.
– For Instance, a US leasing company, Crest Financial, used artificial intelligence on the Amazon Web Services platform and immediately saw a significant improvement in risk analysis, without facing any deployment delays associated with traditional data science methods.
– Artificial Intelligence can also provide a faster, more accurate and unbiased assessment of a potential borrower, at a lower cost, by accounting for a wider variety of factors, which leads to a better-informed, data-backed decision.
– For example, Automobile lending companies in the U.S. have reported success with AI for their lending activities as well. A report by Zest Finance shows that atop auto lender in the US was able to cut losses by 23% annually bringing AI on board.
Asia Pacific is Expected to Witness the Highest Growth
– The global investment in artificial intelligence is rapidly increasing, primarily in the Asia-Pacific region. Furthermore, the healthcare industry in Asia-Pacific countries, such as India, is rapidly expanding. Due to this, the scope and demand for artificial intelligence in the industry is increasing. As a result, the region is expected to have a substantial investment opportunity, thereby boosting the market growth over the forecast period.
– Notably, the top tech giants across the world, offering AI services, are opening research labs in the Asia-Pacific region, which is expected to ascend the employment and tap more potential consumers.
– For instance, in January 2019, Microsoft announced the largest artificial intelligence (AI) and the Internet of Things (IoT) lab in China, in a bid to target the region’s growing business sectors, ranging from manufacturing to healthcare. Also, in December 2017, Google announced the opening of its artificial intelligence (AI) research center in China
– Emerging countries, like India and Taiwan, are heavily investing in adopting new AI-based services or models, further expanding the application scope of the studied market. According to Business Next, in Taiwan, startups are developing AI-inspired software that calculates the best times to clean solar panels, thereby, increasing power generation by more than 15%.
Competitive Landscape
The Artificial Intelligence-as-a-Service market is fragmented, with most companies focusing on a silo approach to developing solutions. Going forward, AI will be increasingly embedded within many systems and applications in everything from data management to retail shopping. The fragmented market has a vast number of players who have been making efforts to increase its market footprint, by concentrating on product diversification and development. Some of the recent developments in the market are:
– Oct 2020 – Amazon Web Services (AWS) and Carrier Global Corporation, a leading global provider of healthy, safe, and sustainable building and cold chain solutions, announced a multi-year agreement to co-develop Carrier’s new Lynx digital platform. This suite of tools will provide Carrier customers around the world with enhanced visibility, increased connectivity, and actionable intelligence across their cold chain operations to improve outcomes for temperature-sensitive cargo, including food, medicine, and vaccines.
– Oct 2020 – IBM Corporation announced new capabilities in IBM Maximo for Civil Infrastructure to help prolong the lifespan of aging bridges, tunnels, highways, and railways. New enhancements include the ability to deploy on Red Hat OpenShift for hybrid cloud environments, as well as new AI and 3D model annotation tools that can provide deep industry and task-specific insights to support engineers. Tools, like AI, predictive maintenance, drones, and hybrid cloud, will play an important role in meeting the challenge of rising infrastructure costs, and helping these vital structures endure for future generations.
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1 INTRODUCTION
1.1 Study Assumptions &and Market Definition
1.2 Scope of the Study
2 RESEARCH METHODOLOGY
3 EXECUTIVE SUMMARY
4 MARKET DYNAMICS
4.1 Market Overview
4.2 Industry Attractiveness – Porter’s Five Forces Analysis
4.2.1 Bargaining Power of Suppliers
4.2.2 Bargaining Power of Consumers
4.2.3 Threat of New Entrants
4.2.4 Intensity of Competitive Rivalry
4.2.5 Threat of Substitute Products
4.3 Industry Value Chain Analysis
4.4 Assessment of Impact of COVID-19 on the Industry
4.5 Market Drivers
4.5.1 Increasing Demand for Predictive and Analytics Solutions
4.5.2 Rising Demand for Enhancing Consumer Experience
4.6 Market Challenges
4.6.1 Risks Associated with Data Breaches and Hacks
5 MARKET SEGMENTATION
5.1 Deployment
5.1.1 Public
5.1.2 Private
5.1.3 Hybrid
5.2 Organization Size
5.2.1 Small and Medium Enterprise
5.2.2 Large Enterprise
5.3 End-user Industry
5.3.1 BFSI
5.3.2 Retail
5.3.3 Healthcare
5.3.4 IT and Telecom
5.3.5 Manufacturing
5.3.6 Energy
5.3.7 Other End-user Industries
5.4 Geography
5.4.1 North America
5.4.2 Europe
5.4.3 Asia-Pacific
5.4.4 Latin America
5.4.5 Middle East and Africa
6 COMPETITIVE LANDSCAPE
6.1 Company Profiles
6.1.1 Microsoft Corporation
6.1.2 Google LLC
6.1.3 Amazon Web Services, Inc.
6.1.4 IBM Corporation
6.1.5 BigML Inc
6.1.6 DATAIKU SAS
6.1.7 Salesforce.com Inc.
6.1.8 SAS Institute Inc
6.1.9 Oracle Corporation
6.1.10 H2O.Ai Inc
6.1.11 Craft.AI
7 INVESTMENT ANALYSIS
8 MARKET OPPORTUNITIES AND FUTURE TRENDS