Artificial Intelligence as a Service: Game Changer in Cloud Computing
Artificial Intelligence as a Service (AIaaS) is a platform that allows anyone to use Artificial Intelligence technology regardless of their knowledge. AI is considered to be the ability of a computer program to mimic human perceptive and cognitive ability by storing information and learning through analyzing them. The outsourcing of Artificial Intelligence by managed service providers as bidding by any third party effectively forms the Artificial Intelligence as a Service (AIaaS) market.
Benefits – The Prime Driver
The adoption of AI technology by the service providers helps them automate their repetitive monitoring tasks, simultaneously analyze data, resolute the internal issues, and also helps in the implementation at affordable prices, which in turn raises customer satisfaction, which can indirectly save costs and increase the production rate. That is primarily attracting the focus of managed services providers to incorporate machine learning or AI capabilities in their programs. This factor is steadfast in its stand to support the growth of the Artificial Intelligence as a Service market.
Migration is the Key to Expansion
Cloud computing services involve employing facilities like network, storage, and software development platforms over the “cloud” or the Internet. Initially, cloud hosting services were utilized only by large enterprises. They are considered the new prototype in software development, where even the SMEs can utilize the processing power of cloud-based AI, cloud storage, and business processing that were initially used only by large enterprises. Imagine a vast network that can hold wide and unimaginable amounts of information in the form of data sets that can help the AI systems to recognize the patterns and learn from them. This is the backbone of cloud computing services when combined with the AI technology platform.
The cloud hosters have raised the demand after the simplification of operations and maintenance of software infrastructure through IaaS and SaaS was completed. The same logic is applied to the AI technologies, where their access is granted through the development of the Artificial Intelligence platform as a Service by optimizing several factors such as the enhancement of the core business, transparent payments post the usage, minimal time invested for development, and the state of dynamic availability that has increased strategic flexibility.
Several disadvantages arise upon the continuous reliance on the service providers for AI-run cloud computing, for instance, the limited number of solutions with minimized innovation and minimal security for transactions and data handling.
In the beginning, only the pioneers or the tech giants with the required technical expertise, dependable IT groundwork, and very affordable pockets could acquire the scarce and costly data science skills that are integral to cloud computing services. Nowadays, large enterprises like Google, Amazon, China’s BAT, etc., and many budding startups are investing in integrating AI into cloud computing billion-dollar developmental platforms and services to transform their operation and make them accessible to a specific industry or end-use.
There is a continuous cycle of fierce competition among the AI service operators that require rapid improvement in AI solutions through continuous upgrades. This is further augmented by the easy access of the consumers to the cloud-based deliveries that are minimally customized and remain the same to all types of consumers. The latter issue can withhold the advancement of the AI providers since it lacks customization, which can be solved if the end-user employs its own IT infrastructure to develop its own solutions.
The enhanced results that the companies obtain from AI solutions can sometimes be unsatisfactory at times. Hence, to counteract that, the enterprises must get the real picture of the challenges and issues the AI can help the best and must understand its strategy behind. This necessitates the executives to have clear cut technical know-how, business strategies as well as the requirement from the data science’s point of view. The presence of technical experts in the companies will ensure the building of effectively functioning models.