AIaaS stands for Artificial Intelligence as a Service, which refers to companies, cloud providers, and platforms that provide access to turnkey AI solutions. Like Software as a Service (SaaS), it helps you use AI in your business without developing them in-house.

AIaaS gives smaller businesses access to artificial intelligence and machine learning, and can help organizations test new ideas without large investments. But there are challenges to using AIaaS solutions. Let’s take a look at the industry, some of the players, and break down what you need to be aware of.

What is AIaaS?

Building an in-house AI solution doesn’t make sense for most businesses. Businesses today need artificial intelligence for a range of operations, from chatbots and text analysis software to more complex predictive analytics tools.

AIaaS makes AI technology accessible to everyone. Through APIs and intuitive, low-code tools, users can harness the power of AI without writing a single line of code.

There are many different types of AI services, and when you’re ready to buy, you’ll probably have a good idea of what you’re looking for – it will all come down to your pain points and what you need to improve. When deciding on AI tools to use, consider the three main categories of artificial intelligence – bots, APIs, and machine learning.

APIs

Many solutions provide APIs. APIs act as intermediaries, allowing two pieces of software to interact. You can use APIs for Natural Language Processing, sentiment analysis, and extracting entities from text, among other tasks. Most of these services are offered ‘as a service’ and can be implemented right away with a few lines of code.

Bots

Chatbots use AI to create human-like conversations with users. This technology allows businesses to automate mundane back-end operations and deliver a superb customer experience.

Machine learning

AIaaS makes it easy for businesses to adopt machine learning technology. You can use pre-trained models or customize tools to suit specific business needs. All this, without needing any machine learning expertise.

Leading AIaaS companies

There are hundreds of available AIaaS providers, so we can’t detail all of them here, but these startups will give you an idea of what is possible with either a little coding or no coding at all.

Of course, all the tech and cloud giants provide various levels of AIaaS, including AWS, Google Cloud, Microsoft Azure, and IBM Developer Cloud. Still, the landscape is peppered with contenders that have their niche solutions. Here are a few examples.

Element AI

Element AI creates software solutions that learn and improve. It helps large organizations across multiple industries operationalize AI with access to a global network of experts and engineers, integrating AI technology, advisory assistance, and end-to-end support.

Mindlayer

MindLayer has built an AIaaS platform to help businesses create scalable and intelligent conversational apps or chatbots without prior knowledge in machine learning or natural language processing. The service comes with a simple-to-use framework that allows non-experts to build autonomous systems capable of tasks in few weeks instead of months.

ucfunnel

ucfunnel is a data-driven company that focuses on the B2B sector. Since 2015, the team has created several innovative and efficient marketing tools, including smart SDKs. ucfunnel also offers customizable AIaaS to online businesses who would like to develop and design their solution.

H20.ai

H2O.ai is a cloud-based machine learning platform that allows you to harness the power of big data, combining powerful machine learning algorithms with simple APIs.

The challenges of AIaaS

Data privacy and security: Protecting your company data is a top priority. Whether you want to protect data from hackers or are legally required to do so, establishing data privacy and security programs can help you create both long-term value and short-term gains. It’s vital to ensure your chosen AIaaS provider can meet your needs in this area.

Vendor lock-in: It may seem easy to switch to a different AIaaS provider. However, each uses different response formats, and changing requires some effort. End-to-end ML services or components are harder to switch since your teams need to get familiar with them to be effective.

Data governance: Some companies in highly regulated industries such as banking or healthcare may limit data storage in the cloud. Such companies may not be able to leverage AIaaS.

Long-run costs: AIaaS allows businesses to implement AI into their business quickly. However, the price may be high in the long run, and companies need to understand both short and long-term costs before making significant AIaaS investments.

In conclusion

One of the many advantages of an AIaaS platform is that you can try different algorithms without spending thousands of dollars on hardware or software. The hundreds of service providers available offer options to get high-quality results with ease.

Imagine the countless possibilities for your small business when you team up with a state-of-the-art AI platform that provides intelligent cognitive functions.

Just be sure to do your due diligence, and keep in mind where your data is being stored and how that might affect your business or the various regulations it operates under before you dive in.

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Source: https://dataconomy.com/2021/05/aiaas-what-who-challenges/