What is Artificial Intelligence as a Service (AIaaS) in the Tech Industry?

Software as a service, Infrastructure as a service, Platform as a service, etc. are common services that everyone has heard of in the tech world. But what about Artificial Intelligence as a service?! Most companies these days use some sort of “as a service” to obtain services for a fee so that they can focus on their core business. But AIaaS is relatively new and its emergence is due to the rising popularity of Artificial Intelligence in the IT industry.

What-is-Artificial-Intelligence-as-a-Service-AIaaS-in-the-Tech-Industry

The International Data Corporation even predicts that 75% of commercial enterprise applications will use Artificial Intelligence by 2021. This means that companies need to buck up their game and integrate AI solutions into their business and production strategies as soon as possible. But Artificial Intelligence is not cheap! So how to do this? The solution is Artificial Intelligence as a service!

First, let’s see what is Artificial Intelligence as a Service and then move on to the vendors offering it as well as its advantages and disadvantages.

What is Artificial Intelligence as a Service?

Almost all companies these days want to use Artificial Intelligence to improve their business. After all, Artificial Intelligence and Data Analytics can be used by companies to better understand their target audience, automate some of their production, create better products according to market demand, etc. All of these things in return increase the profitability of a company which in turn gives them an edge over their competitors. After all, the bottom line in most cases is profit!



However, for a long time in the past, companies needed to invest a lot of money in Artificial Intelligence to get this profit. The AI machines were expensive, programmers who were familiar with AI were expensive and even rarer while there was no good data to be found! While this was not that big a deal for large multinational corporations, it was very difficult for small and mid-level companies. But the popularity and advancement of cloud services have made everything much easier. Now companies can access AI software from a third-party vendor, made a few changes according to heir custom requirements are start getting the benefits of Artificial Intelligence and Data Analytics with a much smaller initial investment.

This is the power of Artificial Intelligence as a Service! AIaaS is the solution for many smaller and mid-level companies that don’t want to build, test, and implement their artificial intelligence systems from scratch. These companies can focus on their core business and obtain value addition from Artificial Intelligence without needing to become data and machine learning experts. So they get increasing profits while decreasing their risk of investment using AIaaS. It’s a win-win situation for all!

Which vendors offer Artificial Intelligence as a Service?

Let’s check out the vendors that offer Artificial Intelligence as a Service.

1. Amazon Web Services (AWS)

Amazon Web Services provides pre-trained Artificial Intelligence Services that can help businesses personalize the experiences for their customers, create accurate forecasting models, perform image and video analysis, perform text analysis natural language processing, etc. Amazon SageMaker is also a service that provides developers and data scientists the ability to build, train, and deploy Machine Learning (ML) models quickly without doing any heavy lifting in each step of the machine learning process which would have been necessary if the ML models were developed from scratch.

2. Microsoft Azure
Microsoft Azure allows companies to easily build, train, and deploy their machine learning models using Azure Machine Learning, Azure Databricks, and ONNX. Azure Cognitive Search also allows companies to discover patterns and relationships in their content using this cloud search service with built-in Artificial Intelligence capabilities. The Azure Cognitive Services allows companies to embed vision, speech, and decision-making abilities into their applications without needing any particular Machine Learning expertise.

3. Google Cloud

Google Cloud’s AI Hub provides companies with enterprise-grade sharing capabilities which includes end-to-end Artificial Intelligence pipelines. Moreover, the AI building blocks of google Cloud are tools that companies can use to add technologies like Computer Vision, Natural Language Processing, Translation, Speech recognition, etc. Cloud AutoML also allows developers that have less Machine Learning expertise to train custom ML models quickly specific to their company needs.



4. IBM Watson Cloud

IBM Watson Cloud allows companies to infuse Artificial Intelligence into their applications so that they can make more accurate predictions, automate the company decisions and processes, and obtain optimized solutions. Some of the pre-built Watson applications offered by IBM include Watson Assistant, Watson Speech to Text, Watson Natural Language Understanding, etc. IBM Watson Cloud also provides AI solutions for specific markets such as AI for Customer service which aims to improve customer experience, AI for Financial Services which aims to accelerate insight extraction from data, AI for Cybersecurity which analysis risk data to speed response times and so on.

What are the advantages of Artificial Intelligence as a Service?

1. Advanced infrastructure with minimal cost

A company that wants to implement Artificial Intelligence in their day to day operations needs to invest heavily in AI equipment. This is usually very expensive as the equipment requires an initial investment and then constant upkeeps. However, companies can implement Artificial Intelligence as a Service with minimal costs as they are accessing AI software from a third-party vendor with no in-house AI equipment or software developed from scratch. This is especially useful for those companies that don’t have AI as their core business but just want to leverage it to enable better decision making.

2. Pay for What you Use

Implementing Artificial Intelligence from scratch is expensive but this expense is reduced by using Artificial Intelligence as a Service. Most AIaaS provides have specific plans for companies that can be bought at a fixed price. This means that a company does not need to finance increasingly complex AI specifications but they can buy what they want and pay just for that. While AI requires a lot of power when it’s been used, companies that buy AIaaS only need that power in short amounts of time and they pay accordingly.

3. Ease of Usage

Software developers don’t need to be Artificial Intelligence experts to implement Artificial Intelligence as a Service. Most companies that offer AIaaS have pre-created packages of different AI services such as Computer Vision, Natural Language Processing, Computer Translation, Speech recognition, etc. that other companies can buy and developers can tweak these packages according to their company requirements without becoming experts. This is not the case if companies decide to implement AI solutions from scratch as that requires specialized knowledge and trained Artificial Intelligence experts.

4. Options for Scalability

Companies can start with smaller projects using Artificial Intelligence as a Service just to see if they are the right corporate fit. And later, when companies are more confident about their projects and more knowledgeable with their data, they can always scale up their projects as the corporate demands change over time. This feature for scalability is offered by almost of the AIaaS vendors for the convenience of companies.



What are the disadvantages of Artificial Intelligence as a Service?

1. Reduced Security

Companies need to share their data with the AIaaS vendors that they hire. This is necessary as Artificial Intelligence and Data Analytics are dependent on quality data to obtain the required services. However, this also means that the company data is not that secure and so companies need to provide extra security measures for data storage and data transit between different servers to ensure that the data isn’t stolen, shared improperly, or tampered with.

2. Increasing reliance on Third-Parties

Artificial Intelligence as a Service by default implies that companies are reliant on their service vendors to provide them with the Ai software they need according to their company requirements. While this is not a bad thing as companies are gaining a lot with a minimum investment in AIaaS, it does mean that companies can suffer if there is a time lag, miscommunications, or any other problems between them and their service providers.

3. Long-Term Costs

Artificial Intelligence as a Service can result in long-term costs for companies as they continue to access more and more services from their AIaaS service providers. However, this is not unique to Artificial Intelligence but a common issue in all “as a service” offerings. So companies should ensure that they use Artificial Intelligence as a Service then the benefits outweigh the costs of developing their Artificial Intelligence system from scratch.

4. Reduced Transparency

When companies buy Artificial Intelligence as a Service from vendors, they can only access the service but not it’s inner workings. In other words, AIaaS is like a black box, and companies can provide input and know the output but they cannot understand how the output is obtained, which AI algorithms are used to obtain the output, etc. Companies also cannot know how their data is used to obtain the output and whether it’s secure enough. This may lead to confusion or misunderstandings between the company and the AIaaS vendor.




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