Organizations today are highly alert to new trends and innovativeness in the market along with the benefit and well-being of their employees and society at large. This leads to most organizations getting more accommodating when it comes to adopting the latest technologies or strategies in order to maintain a competitive edge and sustainability.

Talking specifically of AI, which is one of the most talked-about technologies of recent times, we can say that almost all businesses across all sectors are showing keen interest in it. Organizations either have already started using the technology or are intending to include this in some way or the other.

According to McKinsey Global Institute, the utilization of AI could yield an additional worldwide economic output of USD 13 trillion by 2030. 

AI has exhibited tremendous success in matching or, to say, surpassing human intelligence in terms of making complex data analysis, decision making, pattern recognition, and making predictions based on the input data. However, there are few challenges around AI adoption and integration. 

These challenges could be:

• Lack of AI experts
• Lack of AI skilling
• High set up costs
• High maintenance
• High requirement for IT resources
• Limited knowledge

These issues pose a barrier to the adoption and utilization of AI to the fullest.

As solution cloud providers, Amazon, Google, IBM, Microsoft, Salesforce, or SAP have started various related services that will provide unique cloud-based AI services to various small to medium scale organizations across multiple sectors.

This brings us to the topic of the day that is Artificial Intelligence as a Service (AIaaS). According to Springer, AIaaS are cloud-based systems that provide on-demand services to organizations and individuals to deploy, develop, train, and manage AI models. 

This is a third-party offering or an outsourcing service that allows organizations to start with AI for their desired purposes and convenience without spending a fortune on the required initial setup investment. Moreover, this reduces risk, as it allows trial and testing of AI-based solutions. 

These solutions are designed keeping in mind the organizations' requirements. This gives businesses the chance to narrow down the features and pricing of the solution that suits their specific requirements. 

In an endeavor to deal with the high initial setup cost or the hardware cost, businesses can opt for specialized hardware through the cloud AI service providers.

AIaaS can be divided into three categories according to the capabilities they provide.

• AI software services that are ready-to-use AI applications and building blocks
• AI developer services that are tools for assisting developers in implementing code to bring out AI capabilities
•  AI infrastructure services that comprise raw computational power for building and training AI algorithms and network and storage capacities to store and share data

AIaaS will lead to more adoption of AI as this eliminates the inertia that organizations have around AI setup and associated costs. Furthermore, this shall make the technology accessible to various organizations aspiring to embed AI in their solutions.

The major players in the market are Microsoft, Google, Amazon, and IBM, as they have their own large public cloud infrastructure and AI platforms. These players offer customer service, process automation, marketing, analytics, predictive maintenance, and hardware setup.

There are various reasons that make AIaaS look promising and booming in recent times. This could be because the AI market is growing, and hence the demand is rising too. Businesses see a lot of value in utilizing AI-based solutions. Also, the success of AI deployment depends a lot on setting up robust AI ecosystems leading to a progressive AI adoption graph.

AIaaS can certainly be called a game-changer or a booster as this will provide a competitive edge to most SMBs and bring innovative AI-enabled solutions to the world that will benefit people at large and increase people's faith in AI.