The global AI market is expected to reach $407 billion by 2027, making AI as a service valuable for businesses across diverse industries.
Updated 18 January 2024
VP - Delivery at Appventurez
From autonomous driving to smart chatbots, AI has permeated our lives gradually. The next-gen technology has impacted the world, making companies leverage AI app development services substantially in their business processes.
The AI market is estimated to have an annual growth rate of 37.3% in the next seven years. This considerable growth hints that AI will no longer be used just as a technology for improving services but as a service itself.
The current progress in the development of AI offers a wake-up call for businesses — either adopt AI as a service or risk falling behind in the competitive landscape.
Artificial Intelligence as a Service (or AIaaS) is a third-party offering of AI that makes advanced solutions readily accessible to businesses with the help of cloud computing. Simply put, it refers to the off-shore tools with which businesses could make the best use of AI techniques economically.
The primary objective of utilizing artificial intelligence as a service is to mitigate human intervention and make tasks faster with better accuracy.
Last year, the global AI as a service market was valued at $6.4 billion and this figure is estimated to touch the $9 billion mark by the end of 2023.
Here are a few insights related to AIaaS as per recent AI market research studies:
Different types of AI-based platforms offer different forms of ML and AI as services. These variations are primarily based on the organization’s business requirements and the industries they serve. Here are some popular types of AIaaS:
Today, almost all businesses across industries are developing and integrating bots and digital assistants for enhanced consumer services. The major role of chatbots in enterprises is to implement advanced functionalities such as automated email responses, personalizing customer experiences, and providing a digital outlook of the business.
These bots use technologies such as natural language processing to comprehend human speech and offer relevant information to users. This mode of AI as a service is highly prevalent, with 62% of customers seeking online bots for assistance instead of customer support executives.
Users rely on machine learning frameworks to develop their own AI models. However, such models are complex to test and deploy, and ML-based frameworks may not perform this task alone. In such situations, additional tools are required, and that’s where artificial intelligence as a service comes in.
AIaaS solutions provided as a Platform-as-a-service (PaaS) model help offer end-to-end machine learning operations (MLOps). With this service, developers can easily build AI models, assemble datasets in them, test them, and deploy them for further production on the cloud servers.
An application programming interface, or API is a software program that bridges the communication between two different applications. With a few lines of code, users can gain access to powerful AI features upturning the performance and functionalities of an app.
Several AI-as-service-based APIs provide natural language processing capabilities, such as knowledge mapping, sentiment analysis, and translation. However, to get hold of innovative solutions like these, integration of excellent NLP solutions is a must.
Other AIaaS APIs offer features like conversational AI and computer vision that provide the user’s image and perform intricate tasks, such as face recognition, in-video search, object detection, etc.
No code or low code machine learning development services enable quick and seamless AI-powered solutions for businesses. With customized templates, pre-built models, and no-code apps and tools, this type of artificial intelligence platform as a service is ideal for enterprises looking for affordable development resources.
One of the most cumbersome tasks is to categorize a huge pile of data and ensure that its quality is maintained in the process. Data labeling is an approach that guarantees efficient categorization of data with AI while keeping data quality in check.
This AI as a service solution leverages the human-in-the-loop method, making both users and machines constantly interact with each other and assisting AI in analyzing the data.
With an efficient utilization of AI as a service, businesses can conveniently create tailored AI solutions that are not only adaptable but scalable, as well. Here are some of the notable benefits of AIaaS, describing the crucial role of AI in businesses.
Using AI-as-a-service is one of the easiest ways to introduce AI to an organization. The use cases of artificial intelligence are not always the same. Due to this, it becomes problematic to develop a feasible solution that works for all businesses.
To cope with this, customizable options are handy, and by deploying AI services, enterprises can quickly tweak them according to their needs and constraints.
Obtaining affordable solutions is one of the primary factors promoting the expansion of AIaaS in the IT industry. Leveraging AI as a service is cost-effective for businesses as it prevents them from making sizable upfront investments.
Also, most AI-as-a-service pricing structures are based on consumption, which means businesses only pay for the specific usage and AI functionalities they use.
Businesses often use AI solutions to manage and optimize extreme data conditions in the production environment, including raw, unstructured data. With the incorporation of integrated AI technologies and expertise, advanced solutions can be developed that help organizations attain stability and robustness.
Using AI as a service is well-suited for enterprises looking to scale. Since this technology employs industrial automation tools and techniques to complete simple tasks, team members get more time to focus on other critical jobs. This process not only enhances the productivity of the organization but also improves the scope of scalability to a large extent.
Although there are immense benefits to using AI as a service, integrating it comes with several challenges, as well. Some of the main challenges of AIaaS are listed below.
Using AI as a service is cost-effective. However, the initial investment requires businesses to purchase specific hardware and software components. This budget can further increase if private cloud computing and AI solutions are needed.
To cope with this challenge, it is important to strategically plan your requirements and budget. With the right planning, you can optimize your investment. It’s better to collaborate with an experienced AI consultant to help you manage the overall cost based on the services you want.
Most of the AIaaS platforms offer access to the provider’s services only. No direct access is given to the core AI system where the internal operations take place. Due to this, the customers will have little to no transparency into the inner functionalities, such as utilizing ML algorithms for data analysis.
Artificial intelligence services companies can use open AI model interfaces with comprehensive documentation that at least provides critical insights into internal operations.
Data security is one of the major concerns with AIaaS, as data is the basis of AI and businesses have to share it with outside vendors.
However, businesses can safeguard their crucial data with several privacy-enhancing techniques, such as data masking.
Some highly regulated industries tightly enforce limits on cloud data storage. For instance, organizations in the banking and healthcare sectors might encounter restrictions such as limitations on how data can be stored, shared, and used in the AIaaS platforms.
In such cases, businesses need to focus on the best practices that comply with the data governance policies followed in the respective industry.
If a company’s needs are not fulfilled by one AIaaS provider, switching to another could be a tough nut to crack. This is because various AI services companies employ complex vendor lock-in agreements.
Apart from this, the transition might also be time-consuming for team members as they would need to learn the new program from scratch. Therefore, it’s crucial to read the agreement carefully before collaborating with AI services companies.
To ensure that the AI service you are looking for is beneficial to your business, it is important to choose the right vendor for AIaaS. Here are some popular and credible artificial intelligence services companies offering AI-as-a-service solutions.
Being one of the emerging AI development services providers, Appventurez offers a multitude of AI-powered solutions, such as NLP services, machine learning development, chatbot development services, 3D visualization, and generative AI integration.
AWS is known for providing over 200 AI- and cloud-based services. Amazon SageMaker and Amazon Alexa are some of the notable products offered by the company to be used as AI and ML use cases.
IBM Watson offers users a wide range of pre-built apps and AI services to create virtual assistants using Watson Assistant and perform complex text analysis tasks with Watson’s Natural Language.
The leading tech giant provides users with several AI and machine learning as a service solution to automate tasks and accelerate AI model training. Some of the popular tools and technologies include Tensor Processing Unit and Google Lending DocAI.
AIOps is one of the most popular AI-based platforms offered by ServiceNow which is designed to simplify IT operations. Apart from this, the company also provides AI Contact Center and AI Customer Care, two incredible choices focused on digital security.
As one of the prominent companies in the realm of generative AI, Open AI is renowned for its highly smart and efficient AI models, like GPT-3, DALL-E, etc. It provides AI as a service in the form of APIs that are capable of drafting emails, creating content, and generating graphics.
H2O.ai or H2O Driverless AI is an automated ML platform for organizations that want to automate model development processes, data visualization, ML interpretability, and feature engineering. Besides, it’s an ideal choice to perform highly complex computations in minutes.
By using artificial intelligence as a service, the technology can be made easily accessible for different segments and purposes. However, a professional AI app development company is needed to make the best use of AI as a service.
At Appventurez, we are developing AI-powered solutions focused on simplifying the most complicated problems. Our team of AI experts automates resource management and strives to build a robust AI infrastructure for better efficiency.
Here are some advanced capabilities you gain by using our effective AI services:
With the right implementation of AIaaS solutions, you can easily get a head start on this highly impactful technological trend.
Q. What is AI Service Management?
AI service management (or AISM) is one of the emerging applications of artificial intelligence that aims to focus on and resolve the increasing challenges of traditional IT infrastructure.
Q. What is the future of AI as a service?
Considering the benefits of artificial intelligence as a service to a multitude of industries, the future of this domain seems bright. The AIaaS solutions hold the potential to harness technologies like NLP, computer vision, and deep learning, making them as significant as other service products.
Q. What are the main verticals adopting an artificial intelligence platform as a service?
The prominent industries adopting AI as a service include healthcare, consumer goods and retail, travel and hospitality, media and entertainment, IT and telecommunications, government and defense, manufacturing, and automotive.
VP - Delivery at Appventurez
Expert in the Communications and Enterprise Software Development domain, Omji Mehrotra co-founded Appventurez and took the role of VP of Delivery. He specializes in React Native mobile app development and has worked on end-to-end development platforms for various industry sectors.
Posted : 30 May 2020
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