Artificial intelligence (AI) has evolved from a concept found only in science fiction to a real world resource that is beginning to influence almost every industry.
Modern AI solutions require a combination of vast amounts of raw data, processing power and human expertise to operate effectively, which of course means that it is not feasible for most organizations to strike out and host the necessary infrastructures in-house. This is why AI-as-a-Service (AIaaS) is emerging as the latest and greatest trend in cloud computing.
Here is a look at the advantages that this approach offers and the market pressures which are helping to catalyze the growth of the AIaaS movement.
Solving the data overload issue
Data makes the world go round today, but the problem faced by most businesses is not that they lack information from which they can gain actionable insights, but rather that they are struggling to cope with the sheer volumes of data that are being generated by their operations.
This is where AI-powered big data solutions come into play, allowing machine learning algorithms to be unleashed on mountains of information so that it can be dealt with quickly and efficiently.
Relying on locally hosted hardware to achieve this is unrealistic, of course, if only because of the sheer expense that doing so would create for smaller organizations. You also need data scientists who can wrangle complex infrastructures, interpret SQL server wait stats, arrange your DataOps, and perform a whole bunch of other duties. It is no surprise that AI skills are amongst the most sought-after in the employment market.
AIaaS overcomes these limitations by letting businesses outsource both the software and the hardware elements of big data analytics to a third party provider that is perfectly positioned to shoulder the lion’s share of the operational responsibilities in this context.
The outcome is that AI solutions can be made both more affordable and also eminently scalable, adapting to suit workloads of all sizes according to the needs of individual clients.
While the majority of digital businesses have embraced some form of AI or machine learning solution, there is still a degree of reluctance outside of this sphere because of fears that this technology will cause disruption and reduce the need for human workers, leading to job losses and economic upset.
However, thanks to the accessibility of AIaaS, it is now easier than ever to show skeptical organizations that in fact a combination of AI software solutions and flesh-and-blood employees can actually lead to productivity improvements without negating the need for traditional roles.
Most importantly, AI can be leveraged to accelerate the rate with which insights are gleaned from large data sets, meaning that experts can drill down into the information in a fraction of the time that it would otherwise take them. This benefits individuals as well as entire teams and businesses, and the flexibility of the cloud means that there are very few barriers to experimentation or outright adoption of AIaaS.
The best AI solutions are able to adapt and encompass a wide range of tasks, but because of the promise of a varied and competitive AIaaS marketplace there will also be a rise in the number of providers which aim to target clients within a specific industry.
This level of specialism will clearly be valuable since it will allow businesses to convene with experts who understand what they need to get out of a machine learning analytics package. Whether that means focusing on financial services, insurance, automotive design or anything in between, providers are likely to emerge in order to cater to industrial niches wherever they exist.
Another asset of artificial intelligence when offered as a service that can be sold on subscription is that it will help businesses to keep track of more than just the data that they generate. It can be used to tap into a huge array of other sources, making it much easier to monitor trends, achieve insights and even track brand reputation on social media.
As AI gets better at handling things like natural language processing, it will only continue to improve as a value prospect for companies of all kinds