How Big Tech Is Profiting by Selling AI-as-a-Service

Artificial intelligence (AI) is still in its infancy, but it is truly a transformational technology. Thus far, mainly the companies with the largest stores of data have been able to benefit from the science. When talking about AI, most are referring to machine learning and, more specifically, deep learning, a technique that requires the processing of massive amounts of data in order to train these systems.

Technology companies like (NASDAQ: AMZN), Alphabet (NASDAQ: GOOGL) (NASDAQ: GOOG), and International Business Machines Corporation (NYSE: IBM) are the biggest examples of companies tapping into this data-driven revolution.

So far these innovations haven't been largely available to smaller companies, but that is changing. The widespread adoption of cloud computing is beginning to alter that dynamic, as companies are working to incorporate these capabilities into their cloud offerings. This is just the beginning of the transition to AI-as-a-Service.

Enabled by big data

How these tech titans came by the data necessary to train AI systems varies. Amazon has tons of information on the customers who frequent its e-commerce site. Alphabet has years of records from Google's internet search engine. With no similar source of such data, IBM gathered it through acquisitions and partnerships.

These companies initially found ways to improve their business operations and products using the insights gained from AI. As early as 1999, Google was using a primitive form of AI to improve its search results. Amazon has used the technology to make product recommendations, provide forecasting, and optimize its logistics. IBM has long performed business analytics for its large client base, so adding AI to the mix was a natural fit -- one the company labeled cognitive computing.

Show me the money

Due to the different path each company has taken to AI, the way they are monetizing the technology varies.

IBM has focused on a number of industries like healthcare and has been stockpiling data. Several years ago, IBM bought cloud-based analytics company Explorys and population health specialist Phytel to gain access to their expansive clinical data sets. The company then acquired Merge Technologies and Truven Health Analytics for $1 billion and $2.6 billion, respectively, both of which increased its access to patient health-related data. IBM has been culling information from these records in an ongoing effort to find solutions for healthcare providers. The company has been using the same data aggregation strategy to expand into other industries like retail, finance, and insurance.

Amazon is in a unique position among its tech brethren. The company has a history of using the technology it develops to solve challenges internally and then using those solutions to generate additional revenue. Amazon Web Services (AWS) began as a way of renting unused space on its servers and has now become the company's most profitable business. The company recently increased the number of AI tools it made available to its AWS customers. It also used AI developed internally to introduce what are among the most popular products on its e-commerce website -- the Echo family of smart speakers.

Google is a pioneer in AI, first using the data to improve the results for its flagship search, then using its DeepMind AI system to configure the servers in its data center to maximize efficiency and reduce power consumption. It also was among the first to develop an AI-centric chip for its servers. The tensor processing unit (TPU) was designed to address the specific requirements of training AI systems. Most recently, Google has been adding its unique brand of AI functionality to its cloud computing to differentiate itself from the competition. Its self-driving car unit, Waymo, will likely roll out a consumer-facing ride-hailing service once its ongoing consumer testing phase is complete.

What the future holds

AI is still in its infancy, and companies are just now beginning to find ways to monetize the AI they have spent years, and untold millions of dollars, to develop. Some of the technology will find its way into consumer-facing devices like smart speakers, while others will take the form of business services in the cloud. There will likely be other applications that we simply can't as yet imagine. Stay tuned.



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*Stock Advisor returns as of January 2, 2018
