"AI as a Service" (AIaaS) is a rapidly growing market, offering various plug-and-play AI services and tools. AIaaS enables its customers (users) - who may lack the expertise, data, and/or resources to develop their own systems - to easily build and integrate AI capabilities into their applications. Yet, it is known that AI systems can encapsulate biases and inequalities that can have societal impact. This paper argues that the context-sensitive nature of fairness is often incompatible with AIaaS' 'one-size-fits-all' approach, leading to issues and tensions. Specifically, we review and systematise the AIaaS space by proposing a taxonomy of AI services based on the levels of autonomy afforded to the user. We then critically examine the different categories of AIaaS, outlining how these services can lead to biases or be otherwise harmful in the context of end-user applications. In doing so, we seek to draw research attention to the challenges of this emerging area.

The market is anticipated to expand at a CAGR of 37.1% from 2022 to 2030. Artificial intelligence as a service (AIaaS) is a third-party artificial intelligence outsourcing service that allows large enterprises and SMEs to explore development opportunities without requiring a significant initial investment. It enables businesses or end-users to experiment with AI for various applications while limiting initial investment and risk. The increased R&D efforts of AI as service vendors and governments across countries are driving the artificial intelligence-as-a-service market. Furthermore, greater AIaaS integration with blockchain and increased investment in AIaaS by governments and end-users are likely to drive the artificial intelligence-as-a-service market. For instance, in July 2022, the United Nations Development Programme (UNDP), a United Nations agency, and the Telangana government established data in climate resilient agriculture (DiCRA), an AI-powered platform service focused on providing farmers with climate change information.

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! When it comes to artificial intelligence (AI) adoption, there is a growing gap between the haves and the have-nots. According to IBM, the global AI adoption rate went up by 4 percentage points in 2022, reaching nearly 35%. However, the study also found that the gap in AI adoption between larger and smaller companies also grew significantly in the past year.

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Over the last decade, artificial intelligence (AI) technologies have increasingly relied on neural networks to perform pattern recognition, machine learning (ML) and prediction. However, with ML models that consist of billions of parameters, training becomes more complicated as the model is unable to fit on a single GPU. Large language models (LLMs) such as GPT-3 and Gopher cost millions of dollars and require vast amounts of computing resources, making it challenging for cash and resource-constrained organizations to enter the field.

Artificial intelligence as a Service (AIaaS), refers to pre-trained computer learning algorithms, natural language processing (NLP), and robotic process automation (RPA) in the cloud to automate business operations. It is very similar to software-as-a-service (SaaS). AIaaS is a service that allows businesses to access AI models, without the need for advanced AI programming skills. This blog lists the expected growth figures for the AI business, including the deployment model, end-user application, verticals, and geography. Companies will not be able to build their own AI solutions for these small services.

Artificial intelligence as a service (AIaaS) refers to the use of pre-trained machine learning algorithms, robotic process automation (RPA) to natural language processing (NLP) in the cloud to automate business processes. In this respect, it is similar to software as a service (SaaS). However, AIaaS allows business users to access AI models without requiring advanced AI programming skills. This blog shares the anticipated growth figures of the AI business covering as per deployment model, end-user application, verticals, and geography. Building the own AI solution for these different small services will therefore not make any sense for companies because they are all associated with substantial upfront costs and management, which is sometimes not easy for the new joiners.

You think AI is too expensive? Artificial Intelligence as a Service (AIaaS) is a third-party, low-cost, high-value AI-based service to businesses and startups. AIaaS refers to off-the-shelf AI tools that enable companies to implement and scale AI techniques at a fraction of the cost of doing it in-house. AIaaS providers offer solutions ranging from simple data entry work to complex machine learning (ML) tasks. Companies can determine what offers they want within what budget.

Soumen helps enterprises to embrace data and augment cognitive intelligence. Every day we read about some new AI breakthrough. AI is omnipresent in our everyday lives whether we use mobile devices, wearables or voice assistants or stream our favorite shows. Enterprises control the epicenter of the AI economy, and they drive the innovation through a new trajectory, attracting investors through their impeccably timed innovations promising the new efficiency frontier. A new forecast from IDC Worldwide predicts the AI market will have worldwide revenues surpassing $300 billion in 2024 with a five-year compound annual growth rate (CAGR) of 17.1%.

Almost all companies today use at least one type of service offering to focus on their core business and outsource other needs to outside experts and vendors. Now, the same service approach is being applied to a new area: AIaaS. The number of terms and products is constantly growing, and in this article, we'll have a look at what AIaaS stands for. AIaaS invites individuals and companies to experiment with AI for a variety of purposes without a large upfront investment. Everything as a service refers to any software that can be invoked over the network as it is cloud-based.

Software as a Service, or SaaS, is a concept that is familiar to many. Long-time Photoshop users will recall when Adobe stopped selling its product and instead shifted to a subscriber model. Netflix and Disney are essentially Movies as a Service, particularly at a time when ownership of physical media is losing ground to media streaming. Artificial Intelligence as a Service (AIaaS) has been growing in market adoption in recent years, but the uninitiated might be asking: what exactly is it? In a nutshell, AIaaS is what happens when a company develops and licenses use of an AI to another company, most often to solve a very specific problem.