The 2018 Interop ITX State of AI report includes some sobering statistics that will sound familiar to many business and IT leaders.
Everyone seems to be talking about AI, but it isn't in production yet at most North American organizations, according to the 2018 Interop ITX AI: Hype or Substance report. The report is based on an April 2018 survey of 182 technology professionals involved in purchasing. Fifty-three percent work in an IT management role; 40% represent enterprises with more than 1,000 employees.
Nearly two-thirds of respondents' organizations are working on AI products or evaluating the technology, but only 12% are using AI in production today. Nearly half plan to increase their AI spending in 2018 while 6% will likely decrease their spending.
The report also showed less interest in cognitive systems, recommendation engines and chatbots than predictive analytics and machine learning, which is consistent with investment patterns.
While AI interest is high, the ability to execute is low.
What's holding AI back?
The current state of AI technology adoption reflects its early stage. IT infrastructure is the biggest barrier, despite the popularity of cloud shown in Interop ITX State of Cloud reports. Interestingly, the AI survey did not question organizations' ability to access and aggregate the data necessary for AI to serve its intended purpose.
Since AI's ROI potential may not be clear, about a third of organizations lack the budget they need to move forward.
As always, talent factors into the equation. Not surprisingly, about one in three said a lack of talent is holding them back, although some organizations are training their employees to fill the gaps.
More than a quarter haven't defined a business case yet and nearly half have no idea what effect AI may have on their businesses.
Organizations need to have a clear vision of how AI can benefit their businesses and what that means in terms of people, processes and tools. All of that takes time to implement, and the path forward isn't always clear. Slightly more than one quarter said they'll seek outside assistance because they need it.
Given the early market nature of AI use in business, it's not surprising that some would prefer to learn from early adopters' successes and failures.
What should you do?
The report focuses on the current state of adoption. A compelling reason to read it is the realization that despite all the clamor about AI, organizations are actually struggling to implement it. What they're struggling with will likely sound familiar, which would indicate that your organization may not be as far behind everyone else as it may seem.
Consultants commonly advise their clients to avoid a major AI transformation that involves the entire organization. Instead, experiment, make mistakes, learn from those mistakes, refine the approach and build on successes.
Lisa Morgan is a freelance writer who covers big data and BI for InformationWeek. She has contributed articles, reports, and other types of content to various publications and sites ranging from SD Times to the Economist Intelligent Unit. Frequent areas of coverage include ... View Full Bio
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