AI as a Service Market Size, Share with Focus on Emerging Technologies, Top Countries Data, Top Key Players Update, and Forecast 2028

AI as a Service Market Size, Share with Focus on Emerging Technologies, Top Countries Data, Top Key Players Update, and Forecast 2028

May 08
17:10 2023
AI as a Service Market Size, Share with Focus on Emerging Technologies, Top Countries Data, Top Key Players Update, and Forecast 2028
IBM (US), Microsoft (US), Google (US), AWS (US), FICO (US), SAS Institute (US), Baidu (China), SAP (Germany), Salesforce (US), Oracle (US), Iris.AI (US), Craft.AI (France), BigML (US), H2O.ai (US), Vital.ai (US), Fuzzy.ai (Canada), RainBird Technologies (UK), SiftScience (US) DataBricks (US), CenturySoft (India), Alibaba (China), and Meya.ai (KSA).
AI as a Service Market by Offering (SaaS, PaaS, IaaS), Technology (Machine Learning, Natural Language Processing, Context Awareness, Computer Vision), Cloud Type (Public, Private, Hybrid), Organization Size, Vertical and Region – Global Forecast to 2028

The AI as a Service Market is estimated to grow from USD 9.3 billion in 2023 to USD 55.0 billion by 2028, at a CAGR of 42.6% during the forecast period. AI is driving new capabilities and innovations in AIaaS, enabling providers to offer new and innovative services such as natural language processing and image recognition. Additionally, AI is transforming AIaaS by enabling new capabilities such as customization, automation, and innovation. This technology is transforming the way companies approach their data management and analytics needs, enabling them to automate their decision-making processes and gain valuable insights from their data.

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Healthcare & Lifesciences to account to account for higher CAGR during the forecast period

The AIaaS market for healthcare is categorized into various applications, such as patient data and risk analysis, medical imaging and diagnostics, precision medicine, lifestyle management and monitoring, drug discovery, inpatient care and hospital management, virtual assistant, wearables, and research. The growth in patient data due to the increasing adoption of Electronic Medical Records (EMR) and various advantages, such as predictive analytics and risk management, offered by AI systems to healthcare providers and payers, are supporting the growth of the patient data and risk analysis segment. The market for the medical imaging and diagnostics segment is projected to grow at the highest CAGR during the forecast period. Factors such as the presence of a large volume of imaging data, advantages offered by AI systems to radiologists in diagnosis and treatment management, and the influx of a large number of startups in this segment fuel the growth of medical imaging & diagnostics.

SMEs to account for higher CAGR during the forecast period

The market for AI as a Service is bifurcated based on organization size into large enterprises and SMEs. The CAGR of SMEs is estimated to be highest during the forecast period. AIaaS solutions provide SMEs access to advanced AI capabilities and resources without requiring significant upfront investments. These solutions can help SMEs automate repetitive tasks, such as customer support and data entry, freeing up resources for other business activities. AIaaS solutions can help SMEs gain insights from data, enabling them to make more informed decisions and identify new growth opportunities. AIaaS solutions can provide SMEs with the ability to compete with larger organizations by allowing them to access the same level of AI capabilities and resources.

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Key players operating in the AI as a Service market across the globe are IBM (US), Microsoft (US), Google (US), AWS(US), FICO(US), SAS Institute(US), Baidu(China), SAP(Germany), Salesforce(US), Oracle(US), Iris.AI(), Craft.AI(France), BigML(US),  H2O.ai(US), Vital.ai(US), Fuzzy.ai(Canada), RainBird Technologies(UK), SiftScience(US) DataBricks(US), CenturySoft(India), DataRobot(US), Alibaba(China), Tencent(China), Dataiku(US), Yottamine analytics (US), Tecnotree (Finland), Cloudera(US) and Meya.ai (KSA). These AI as a Service vendors have adopted various organic and inorganic strategies to sustain their positions and increase their market shares in the global market.

IBM (International Business Machines Corporation) is an American multinational technology company founded in 1911, that produces and sells computer hardware, middleware, and software, as well as providing hosting and consulting services in areas ranging from mainframe computers to nanotechnology. IBM’s AI offerings are part of the company’s Watson suite of products, which is designed to help businesses harness the power of AI and cognitive computing. IBM Watson offers several AIaaS solutions, including natural language processing (NLP), speech recognition, and image recognition. IBM has a presence in more than 175 countries in North America, Europe, Asia Pacific, the Middle East & Africa, and Latin America.

A multinational technology company Google, was founded in 1998 and headquartered in Menlo Park, US. Google offers a range of products and services that include internet search, cloud computing, online advertising, and AI as a Service (AIaaS). Google’s AIaaS offerings are designed to help businesses of all sizes leverage the power of AI and machine learning to drive innovation and growth. Google’s AIaaS offerings are part of its Google Cloud Platform, which includes a suite of products and services designed to help businesses harness the power of cloud computing and AI. Google Cloud AI Platform is one of Google’s flagships AIaaS offerings, providing businesses with tools to build, train, and deploy machine learning models at scale. Google Cloud AI Platform is available in many regions across the world, including the United States, Canada, Europe, Asia Pacific, and South America.

Amazon Web Services (AWS) is a subsidiary of Amazon.com and was launched in 2006 as a cloud computing and infrastructure service provider. Businesses of all sizes leverage the power of AI and machine learning to drive innovation and growth.  AWS provides a comprehensive set of AI and ML services designed to help businesses of all sizes build and deploy intelligent applications in the cloud. With services like Amazon SageMaker, businesses can easily build and train custom machine learning models using popular frameworks like TensorFlow and Apache MX Net. AWS also offers pre-trained models and services like Amazon Rekognition, which can quickly detect and recognize objects, faces, and text in images and videos. Natural language processing (NLP) is another area where AWS excels, with services like Amazon Comprehend that can analyze large volumes of text to extract insights and identify sentiment. And for speech recognition and translation, Amazon Transcribe and Amazon Translate provide reliable, accurate results. AWS has a global presence, with data centers and regions in various locations around the world, including North America, South America, Europe, Asia Pacific, and the Middle East.

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