What is something common between IBM Watson, Microsoft Azure, and Google Cloud ML?
These companies are the top AIaaS companies around the world. The term ‘AI-as-a-Service’ refers to Artificial Intelligence and Machine Learning systems provided by public cloud providers, on a flexible, pay-as-you-go basis, to third-party users who can employ them to achieve their objectives with AI. They are an economical option compared to developing software in-house.
AIaaS makes AI technology available to all. Through APIs and easy-to-understand tools, users have the power of AI without having to code at all.
Currently, a multitude of AI-as-a-Service products exist. The most popular include:
- Simple cognitive APIs that facilitate speech and vision analytics, text-to-speech translation, and intelligent search. They are straightforward to implement yet bound in application and customization options.
- Bots and Virtual Assistants help businesses improve customer service, diminish response times, and increase productivity.
- Machine Learning frameworks that can be trained with their data.
According to a company’s requirements, resources, and funds, an AI solution is chosen. Less complex products require less integration effort but also present fewer capabilities. The more advanced a tool, the more customization is present.
Off-the-shelf AI enables companies to exploit Artificial Intelligence solutions that are economical instead of attempting to become AI experts.
On the financial side, the agile, scalable, and clearly-defined payment model provides transparency into the AI investment.
AI-as-a-Service will lead to global AI adoption. The reliable solutions make it simpler for businesses to access complex, high-value analytics and Machine Learning services and are prescribed for companies looking for efficient solutions to their problems. So what is your AI strategy?