Posted March 15, 2018 By Cynthia Harvey

AI as a service is growing. Cloud-based AI services are one of the easiest and least expensive ways to get started with machine learning and cognitive computing.

In their never-ending quest to stay ahead of the competition, a growing number of enterprises are looking for ways to incorporate artificial intelligence into their applications, products, services and big data analytics. And one of the easiest and most popular ways to get started with the technology is by using cloud-based AI as a service (AIaaS) offerings.

According to IDC, worldwide spending on cognitive and AI systems is expected to increase at a compound annual growth rate (CAGR) of 50.1 percent through 2021. That means total spending on these technologies will increase from $12.0 billion in 2017 to a whopping $57.6 billion by 2021.

Much of that spending will likely go to cloud-based AI services. The RightScale 2018 State of the Cloud Survey revealed that organizations are particularly interested in using cloud services related to one particular type of AI: machine learning. When survey respondents were asked which types of public cloud services they planned to use in the future, machine learning services were the number one vote-getter, with 46 percent either experimenting with the technology or planning to deploy it, despite the fact that only 12 percent are currently using those services.

Clearly, organizations are interested in AI as a service, and the cloud vendors are responding with a growing number of products.

Types of AI as a Service

There are myriads types of AI as a Service because “artificial intelligence” is a broad term that covers a wide array of technologies. At its core, AI is about creating machines that can do the same sorts of things that human brains can do. For example, AI includes computer vision technologies that can see and identify the objects in pictures. It also includes natural language processing technologies that enable systems to carry on a normal conversation, as well as machine learning technologies that allow computers to learn without being explicitly programmed.

AI as a service offerings make one or more of these types of artificial intelligence technologies available as a cloud service. Currently, the AI as a service products on the market generally fall into the following categories:

  • Bots and digital assistants:For many people, the first thing that comes to mind when they hear the phrase “artificial intelligence” is a digital assistant like Apple’s Siri, Microsoft’s Cortana or Amazon’s Alexa. These tools use natural language processing technology to carry on conversations with users, and many also use machine learning to improve their skills over time. Many enterprises want to add similar functionality to their products and websites. In fact, according to IDC, the AI use case that saw the most spending in 2017 was automated customer service agents. But creating your own bot from scratch is a monumental undertaking. As an alternative, several vendors offer bot platforms as a service. Organizations train the bots with their own data and then use them to answer simple questions, freeing up human customer service agents for more complicated tasks.


Benefits of AI as a Service

Some organizations, mostly very large enterprises, choose to invest in their own AI research and hardware. However, many prefer to use AI as a service because this approach offers a number of benefits, including the following:

  • Low costs: Not only does AI as a service eliminate the need to pay for expensive hardware upfront, it also allows organizations to pay only for the time that they need that hardware. In cloud computing jargon, most AI workloads are said to be “bursty,” that is, they require a whole lot of computing power for a short period of time. AI as a service charges organizations only for what they use, lowering their costs significantly.
  • Usability: Some of the most best artificial intelligence tools are available with open source licenses, but while they are inexpensive, these open source AI tools aren’t always very easy to use. The cloud AI services generally make it easier for developers to access artificial intelligence capabilities without requiring them to be experts in the technology.

Drawbacks of AI as a Service





AI as a Service Vendors

All of the leading cloud computing vendors offer AI as a service, and some smaller vendors has cloud-based AI services as well. Here’s an overview:

Vendor Bots APIs ML Frameworks Fully Managed ML
AWS ·   Lex


·  Comprehend

·  Polly

·  Rekognition

·  Translate

·  Transcribe


·   Machine Learning

·   Deep Learning AMIs

·   Apache MXNet on AWS

·   TensorFlow on AWS

Microsoft Azure ·  Bot Service ·  Bing Web Search API

·  Text Analytics API

·  Face API

·  Computer Vision API


·  Machine Learning ·  Machine Learning Studio
Google Cloud · Dialogflow · Natural Language

· Speech API

· Translation API

· Vision API

· Video Intelligence


· Machine Learning Engine · AutoML
IBM Cloud ·Conversation

·Watson Virtual Agent


·Watson Discovery

·Discovery News

·Natural Language Understanding

·Watson Knowledge Studio

·Visual Recognition

·Speech to Text

·Text to Speech

·Language Translator

·Natural Language Classifier

·Personality Insights

·Tone Analyzer


·Watson Machine Learning N/A

Other AI as a Service Vendors

The list of additional entrants into the AI as a Service sector will certainly grow rapidly. As a start:


Salesforce myEinstein