Remember when software as a service (SaaS) was the future of computing?
Though SaaS had been around since the 1960s—a period when computers were enormous and few businesses could even afford them—it didn’t truly gain broad market momentum until the late 1990s when the internet became a widespread and accessible resource. The internet meant businesses could move software applications to off-site data centers, no longer clogging up mainframes, LANs, and/or local hard drives with programs and data.
Software innovators around the time of the dot-com boom saw the advantages of the SaaS recurring revenue model (paying a monthly or yearly subscription for application access) and industry pioneers like Salesforce and Evernote were born. SaaS was also a way for small and mid-size businesses to punch above their weight. They could subscribe to leading software applications that powered efficiency and innovation without big hardware and infrastructure investments.
How SaaS was being used almost 20 years ago, is an excellent way to understand where the marketplace is today with AI as more businesses leverage it to innovate and advance without the time and expense of developing their own AI-based systems.
Now it’s AI’s turn
Like SaaS, AI has been around since the 1960s. However, up until now, computational limitations kept AI from flourishing. Only so much data could be accessed and processed at once. The recent and exponential surge of computer processing power is the reason the possibilities for AI have exploded.
Computers today can access massive sets of data and complete sophisticated tasks in milliseconds. They have the computational power to do work that requires human behaviors like learning and thinking. Now businesses are beginning to identify more and more places where they transfer straightforward work and basic processes to AI. Much like SaaS 20 years ago, AI is a new way for businesses to outperform by tapping into technology that bolsters efficiency and innovation capabilities.
Big global technology firms have vast data science and gathering capabilities and the in-house talent to design and program sophisticated AI-infused solutions. However, the majority of small and midsize businesses need the support of outside resources to tap into the power of AI without taking on big development investments and tech talent hires.
AIaaS providers to watch
Global tech leaders like Google, IBM, Amazon, Microsoft and Salesforce that have large, public cloud-based platforms, are evolving into SaaS providers of AI services (or AIaaS). These tech giants are infusing their cloud platforms and services with AI features like speech recognition, image/face identification, and predictive analytics. For example, Google, over its massive cloud platform, offers tools like AI Hub, AI Building Blocks and AI Platform to help organizations incorporate AI capabilities into their projects and applications. Also offering AI in SaaS form, Amazon has SageMaker, a web service that Amazon describes as a tool for enabling “developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale.”
The AI offerings of the big tech leaders will continue to expand as pioneering tech startups jump into the rapidly growing AIaaS marketplace to provide competing solutions and inventive disruptions. The good news for businesses without the resources to create their own team of AI-savvy data scientists and developers is that they don’t have to sit on the sidelines of this rapid technology advancement. Just as SaaS reduced the complexity and investment that comes with owning and managing software, AIaaS is reducing the cost and complexity of optimizing business intelligence with AI.