Artificial intelligence (AI) is assisting organizations in improving products and customer experiences, making data-driven decisions, and automating time-consuming procedures. Almost every organization nowadays employs at least one type of service offering to focus on their core business while outsourcing other tasks to third-party professionals and partners.
Despite the fact that software as a service has the greatest global spend ($105 million in 2020 alone), IaaS is expected to grow faster in the next years. The worldwide artificial intelligence (AI) market is expanding.
The same ‘as a service’ methodology is now being applied to a new field: AIaaS. AIaaS is an abbreviation for Artificial Intelligence-as-a-Service. The phrase and the product are becoming more popular, and in this post, we’ll look at what AIaaS entails.
What is AIaaS?
While ‘as a service’ goods such as software and infrastructure are ubiquitous in the technology sector, the notion of Artificial Intelligence as a service, or AIaaS, is still relatively new. Artificial Intelligence as a service is similar to any other out-of-the-box solution.
It is artificial intelligence software that is provided as a service to a customer by a third-party provider, and it includes a variety of AI-powered features. These third-party capabilities are housed in the cloud and made available to end-users through the internet, therefore making AI more accessible.
AI as a Service refers to a third party that delivers sophisticated AI features to businesses in exchange for a one-time payment or monthly charge. It is not an exaggeration to suggest that it is a game-changer for many small-to-medium-sized enterprises.
Until recently, many businesses were priced out of adopting Artificial Intelligence for their operations since it would have required in-house creation of systems with human-like characteristics such as reasoning, thinking, and learning. With AIaaS, it is now more accessible than ever before, allowing businesses to use Artificial Intelligence for things like customer care, data analysis, and production automation.
Types of AIaaS
If you’re here, you’re presumably looking for a certain tool, so let’s have a look at the most prevalent ones on the market.
1. Computing API’s
A software “intermediary” that connects two applications is known as an API (Application Programming Interface). A third-party airline booking website, such as Tripadvisor or eBay, gathers data from many airline databases in order to provide all of their options in one convenient place. Developers may utilize an AIaaS solution to add a certain technology or service to a project without having to write code from start. Prominent API services include linguistics (NLP), machine vision, smart search, translations, and emotion detection.
2. Chatbots and Digital Assistants
Nowadays, whether you explore the web for anything from government websites to clothes retailers, you are bound to run across bots — specifically, their most prevalent form, chatbots. Chatbots imitate human conversations by utilizing AI algorithms. They utilize natural language processing (NLP) and machine learning to interpret user inquiries and offer appropriate replies. Because they react 24 hours a day, seven days a week, they save time and money, allowing staff to focus on more complicated duties.
3. Machine Learning (ML)
Machine learning algorithms are used by businesses to identify patterns in vast quantities of data, make predictions, and simplify operations. AIaaS makes machine learning technology adoption simple for organizations. Pre-trained models can be used, or tools can be customized to meet unique business objectives. All of this is possible without any prior knowledge of machine learning.
Advantages & Disadvantages of AIaaS
If you’re contemplating AI as a service for your company, you should assess the benefits and drawbacks. This might help you determine whether or not it would be a good investment for your organization.
It will take a substantial amount of money and experience to develop in-house AI capabilities. It also takes a long time to create and test AI models before they can be deployed. However, AIaaS solutions allow you to avoid this expense and the dangers that come with it while still gaining access to the AI capabilities you want.
2. Transparent fees
You just pay for what you receive when you pick an AI as a service solution. This means you won’t be paying for AI features your company doesn’t require, and you’ll only be charged when you’re really utilizing it.
3. Flexible and Scalable
AIaaS allows you to scale up or down your artificial intelligence capabilities based on the needs of your business or projects. This adaptability makes it perfect for those just getting their feet wet in AI as well as organizations that may see substantial growth in the future. It also allows you to see what is working before making a commitment.
1. Security Issues
You’ll have to disclose your sensitive corporate data with a third-party vendor in order to use your AIaaS service. This may raise worries about security and privacy. Your data storage, access, and transit must be appropriately protected to guarantee that it is not unlawfully accessed, shared, or disseminated.
2. Third-Party Reliance
You are depending on third parties to support you with accurate information when you need it since you are paying for a service. However, if a software fault produces mistakes or a delay, this will become a problem.
3. Selecting Vendors
Switching to a different AIaaS supplier may appear simple. However, each utilizes a distinct response format, which requires some work to change. End-to-end ML services or components are more difficult to switch since they require your staff to become familiar with them in order to be productive.
Top AIaaS Companies
It’s critical to evaluate your goals, business size, and available budget when choosing an AI solution. You’ll also need to consider your team’s technological capabilities as well as the amount of data you’ll need to handle. Here’s a brief summary of the best AIaaS firms to assist you to make your decision:
- IBM Watson
- Microsoft Azure
1. IBM Watson
IBM Watson includes a set of AI technologies aimed at assisting major businesses in making the most of their data. Watson Assistant (for building virtual assistants) and Watson Natural Language Understand are two examples of pre-built apps (to perform advanced text analysis tasks). IBM Watson Studio allows developers to create, train, and deploy machine learning models across any cloud. It is not necessary to have any prior knowledge of machine learning or data science.
Pre-trained AI Services from AWS delivers ready-made intelligence for your apps and workflows. AI Services connect seamlessly with your apps to handle typical use cases like customized recommendations, updating your contact center, enhancing safety and security, and increasing consumer engagement. You receive quality and accuracy from continuously learning APIs because we employ the same deep learning technology that drives Amazon.com and other ML Services. And, best of all, AWS AI Services do not necessitate prior machine learning knowledge.
Azure is a Microsoft-developed public cloud-based platform. It covers a diverse range of AI and machine learning solutions to developers as one of the major AIaaS providers. With Azure Cognitive Services APIs, you may add various AI capabilities (such as machine learning or text extraction) to your apps. You may also utilize Azure Bot Service to create any sort of bot, from a Q&A bot to your own branded virtual assistant, in a matter of minutes.
AIaaS provides a lot of advantages that attract early adopters because it is a fast expanding area. It enables companies to use their data to solve difficult issues and to get faster, more accurate insights into their consumers and markets, allowing them to make better business and marketing decisions.
It also helps them to improve the client experience by automating and customizing messages and enhancing customer service. Further, AIaaS solutions may assist organizations in increasing earnings and gaining a competitive advantage. However, its flaws indicate that there is still an opportunity for development.
It’s important to remember that employing AIaaS in a production system comes with significant costs and dangers. So, make sure you evaluate all the pros and cons before choosing an AIaaS.