What is the Voice of the Enterprise saying about AI & Machine Learning?

Today marks the official launch of 451 Research’s new survey products focused on AI & Machine Learning, called Voice of the Enterprise (VotE) AI & Machine Learning: Adoption, Drivers and Stakeholders 2018.

I made a video explaining more about it, which you can see via Twitter here

I’m very excited about this launch because while it’s great to be doing research on a daily basis in this space – talking to end users, technology vendors, service providers and investors about what’s happening – having data that demonstrates what enterprises are actually doing and plan to do in the future gives us a foundation for all the other research to build upon. 

VotE AI & Machine Learning is currently a semi-annual survey – so two per year – but if it proves successful (and it already has done with forward-thinking 451 Research clients) I’m hoping we can expand it to a quarterly survey, focusing on different themes. Right now the themes are use cases and business benefits across multiple vertical markets, including financial services, retail, healthcare, and manufacturing in one survey and then a deep dive into the changes happening in infrastructure, platforms and tools to enable the adoption of AI and machine learning, both on-premises and in the cloud.

So what is the Voice of the Enterprise telling us? Well, among other things, the following:

  • Although 17% of respondents say they have already implemented machine learning (ML), we are still at the very early stages of ML deployment.
  • Analytics of various types compose the technology’s primary use case, though security is close behind.
  • Larger enterprises are further ahead in terms of adoption; having resources matters in ML.
  • The biggest barrier to adoption is a shortage of skills. I wrote about that recently and what some vendors are doing about it. 
  • Data gathering and preparation is often also cited as a barrier to adoption. Therefore, organizations are focusing initially on customer data as their primary input, as that’s where they can have the most direct, positive impact using ML. 
  • There is plenty of support from senior management in terms of both influence and ultimate spending decisions, which reflects the strategic nature of ML. 
  • Large cloud vendors have a major ML foothold, though Google and IBM have a much stronger presence in ML than they do in overall cloud adoption.

You can find out more about VotE AI & Machine Learning here

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