Many factors have started making businesses anxious and keen to dive into the latest intelligent technologies for Data Management practices. The business operators no longer need to employ tried-and-true talents for cloud infrastructure planning or advanced model development. The idea of “Data Management” has become the priority of all businesses, from finance and healthcare to public utility sectors, smart solutions have overwhelmed all sectors.
“Intelligent technologies” and “Artificial Intelligence” are terms that have become increasingly popular in the past few years. No wonder, as the technology behind AI seems to have limitless possibilities. Add the term “as a service” and that is when things really start to get interesting because a lot of people do not have the time or resources to develop an AI system from scratch.
The AI-as-a-Service (AIaaS) and Artificial Intelligence Platforms-as-a-Service (AIPaaS) are two of the most promising solutions that provide endless opportunities to businesses and organizations in the areas of data mining, data analysis, data visualization, and data discovery.
Factors that Triggered the Development of AI-as-a Service
Some significant developments in the information technology world have taken place in the past few years:
- Data storage technologies became affordable and reliable.
- The cloud platform appeared with a variety of economical options for business Data Management, moving from infrastructure to platform to data-centric services.
- Streaming devices and IoT technologies became the new normal in worldwide businesses.
- The accessibility of Data Management, BI products, and analytics eliminated the need for data experts in day-to-day enterprise tasks.
- AI technologies like Deep Learning (DL), Natural Language Processing (NLP), Machine Learning (ML) grew by a quantum leap.
The Difference between AI-as-a-Service and AI Platforms-as-a-Service
Artificial Intelligence-as-a-service is a system designed to offer AI capabilities as a cloud-based service that enables organizations of any size to leverage AI capabilities to solve their business problems. It is a software platform that makes it easier for companies to implement Artificial Intelligence into their business strategies and day-to-day activities. Since AI is an expensive and new technology, it is still quite rare for organizations to have in-house AI developers. Instead, most businesses are relying on AIaaS solutions that can instantly meet their everyday Data Management needs. Additionally, because AIaaS solutions are priced economically, small or medium businesses can afford them.
On the other hand, AI Platform-as-a-Service indicates an end-to-end solution where enterprises can avail required services on a pay-per-service or pay-per-use basis. These services can be customized for a specific business requirement. The main goal of AI Platform-as-a-Service is to accelerate and simplify the adoption of AI technologies, helping businesses get better insights faster and at a lower cost. It often includes third-party APIs (Application Programming Interface) and managed sub-services. Therefore, providing an intelligent Data Management platform with little human intervention.
Benefits of AI-as-a-Service and AI Platforms-as-a-Service
Here are some benefits of adopting AI-as-a-Service and AI Platforms-as-a-Service solution:
- The solution deployment period is short
- Minimum investment in IT infrastructures
- Minimum dependence on technical personnel
- Cloud service providers offer economical and custom pay structures
- In-house data experts are available to pursue advanced and scrupulous Data Science tasks
- On-demand insights enable enterprises with a competitive edge
- A multi-solution platform such as Google Cloud delivers a variety of advantages like speech recognition, advanced analytics, and translation services
- Pre-built algorithms allow complex Data Management attainable to the average business user
Artificial Intelligence as a Service (AIaaS) Market Discussed in a New Research Report presents an in-depth analysis of “market growth opportunities, share and size, and trends and forecasts” in respect of “product applications, types, key manufacturers, key areas, and countries.”
Bottom Line
The future of Artificial Intelligence service platforms prevails in aligning specific solutions alongside specific use cases. An instance is the implication of AI services for autonomous wheels, where different component manufacturers have achieved AI abilities to develop one integrated and comprehensive autonomous transport.
