Google Cloud rolls out prepackaged AI services aimed at business functions

Rest assured that cloud giants are going to launch services designed to tackle AI problems that multiple enterprises and industries need to solve.
Written by Larry Dignan, Contributor

Google is planning to use its cloud platform to package artificial intelligence services that are more relevant to multiple industries.

The company outlined more details behind its plans to create prepackaged AI services. At Google Cloud Platform's Next '18 conference last month, the company said it would aim to bundle AI for business use cases.

Google's approach is worth noting because the cloud giants--AWS and Microsoft Azure--are likely to do something similar. The reality around AI is that there are specific industry use cases--think oil and gas, retail and manufacturing--but a broad set of functions that every company will need to use.

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Enter Google's prepackaged AI approach. These prepackaged AI services will be mostly delivered through partners and also come with reference architectures and best practices.

The first batch of these prepackaged AI services include the following:

  • Contact Center AI. This package already has more than 800 customers signed up for alpha access after a month. The aim is to use AI to better use conversation to route a customer to agents instead of a phone tree. The AI will use conversation to surface key data so agents can work quickly. The AI package can also note trends and analyze how often problems arise.
  • Cloud Talent Solution. This AI bundle is designed for recruiting talent and cutting the time to hire. The service used to be call Cloud Job Discovery and is generally available.
  • Recommendation Solution, which is a reference architecture. The effort is designed to allow a developer to leverage Google Cloud's machine learning to enhance marketplaces.

Add it up and AI cloud services may veer from the typical vertical selling approach deployed by enterprise software vendors. AI is also going to be horizontal and cloud vendors may fare better with that approach and leave the customization to enterprises.


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