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August 21, 2018
Nvidia RTX Announcement Highlights AI Influence on Computer Graphics

August 14, 2018
The Shifting Nature of Technology at Work

August 7, 2018
The Beauty of 4K

July 31, 2018
The Future of End User Computing

July 24, 2018
5G Complexity to Test Standards

July 17, 2018
California Data Privacy Law Highlights Growing Frustration with Tech Industry

July 10, 2018
Dual Geographic Paths to the Tech Future

July 3, 2018
The Changing Relationship Between People and Technology

June 12, 2018
The Business of Business Software

June 5, 2018
Siri Shortcuts Highlights Evolution of Voice-Based Interfaces

May 29, 2018
Virtual Travel and Exploration Apps Are Key to Mainstream VR Adoption

May 22, 2018
The World of AI Is Still Taking Baby Steps

May 15, 2018
Device Independence Becoming Real

May 8, 2018
Bringing Vision to the Edge

May 1, 2018
The Shifting Enterprise Computing Landscape

April 24, 2018
The "Not So" Late, "And Still" Great Desktop PC

April 17, 2018
The Unseen Opportunities of AR and VR

April 10, 2018
The New Security Reality

April 3, 2018
Making AI Real

March 27, 2018
Will IBM Apple Deal Let Watson Replace Siri For Business Apps?

March 20, 2018
Edge Servers Will Redefine the Cloud

March 13, 2018
Is it Too Late for Data Privacy?

March 6, 2018
The Hidden Technology Behind Modern Smartphones

February 27, 2018
The Surprising Highlight of MWC: Audio

February 20, 2018
The Blurring Lines for 5G

February 13, 2018
The Modern State of WiFi

February 6, 2018
Wearables to Benefit from Simplicity

January 30, 2018
Smartphone Market Challenges Raise Major Questions

January 23, 2018
Hardware-Based AI

January 16, 2018
The Tech Industry Needs Functional Safety

January 9, 2018
Will AI Power Too Many Smart Home Devices?

January 2, 2018
Top Tech Predictions for 2018

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TECHnalysis Research Blog

August 28, 2018
Survey: Real World AI Deployments Still Limited

By Bob O'Donnell

You’d be hard pressed to find a topic that’s received more attention, been more closely scrutinized or talked about at greater length recently than Artificial Intelligence, or AI. Alternatively hailed as both the next big thing in technology—despite a multi-decade gestation period—and the biggest threat that the tech industry has ever created, AI and the related field of machine learning are unquestionably now woven into the fabric of modern life and are likely to remain there for some time to come.

Despite all the interest in the topic, however, there’s surprisingly little insight into how it’s actually being used in real-world applications, particularly in business environments. To help address that information gap, TECHnalysis Research recently engaged in an online survey of IT and other tech professionals in medium (100-999 employees) and large (1,000+ employees) US businesses to help determine how AI is being deployed in new applications created by these organizations.

After starting with a sample of over 3,700, the survey respondents were whittled down to a group of just over 500 who provided information on everything from what applications they were creating, the chip architectures they leveraged for inferencing and training, cloud platforms they utilized, the AI frameworks they used to build their applications, where they were deploying the applications now, where they planned to deploy them in the future, and much more. The full analysis of all the detailed data is still being completed, but even with some early topline results, there’s an important story to tell.

First, it’s interesting to note that just under 18% of the total original sample claimed to be either pilot testing or doing full deployments of applications that integrate AI technology. In other words, nearly 1 in 5 US companies with at least 100 employees have started some type of AI efforts. Of that group, 56% are actively deploying these types of applications and 44% are still in the development phase. Among companies in the sample group who are self-proclaimed early adopters of technology, an impressive 72% said they are using AI apps in full production environments. For medium-sized companies in the qualifying group, slightly more than 50% said they were in full production, but the number rises to just under 61% for large companies.

Equally interesting were the reasons that the remaining 82% of the total sample group are not creating AI-enhanced applications. Not surprisingly, cost was a big factor among those who were even considering the technology. In fact, 51% of that group cited the cost of creating and/or running AI applications as the key factor in why they weren’t using the technology. The second largest response, at almost 35%, came from those who were intrigued by the technology, but just weren’t ready to deploy it yet.

The third largest response of nearly 32% (note that respondents were allowed to select multiple factors, so the total adds up to over 100%) related to a real-world concern that many companies have voiced—they don’t have the in-house expertise to build AI apps. This isn’t terribly surprising given the widely reported skills gap and demand for AI programmers. Nevertheless it highlights both a big opportunity for developers and a huge challenge for organizations that do want to move into creating AI-enabled applications. The next most common response from this group, at 29%, was that they didn’t know how AI would be applicable to their organization, and another 26% cited not enough knowledge about the subject.

Both of these last two issues highlight another real-world concern around AI: the general lack of understanding that exists around the topic. Despite all the press coverage and heated online discussions about AI, the truth is, a lot of people don’t really know what AI is, nor what it can do. Of course, it doesn’t help that there are many different definitions of artificial intelligence and a great deal of debate about what really “counts” as AI. Still, it’s clear that the tech industry overall needs to invest a great deal more time and money in explaining what AI and machine learning are, what they can (and cannot) do, and how to create applications that leverage the technologies if they hope to have more than just a limited group of companies participate in the AI revolution.

From an industry perspective, it’s probably not surprising, but still interesting, to observe that almost 27% of respondents who were piloting or deploying AI apps came from the Tech industry. Given that tech workers make up less than 5% of the total workforce, this data point shows how much more the Tech industry is focused on AI technology than other types of businesses. The next largest industry at 13.3% was Manufacturing followed by Professional, Scientific and Technical Services at just under 10% of the respondents.

There’s a great deal more information to be culled from the survey results. In future columns I plan to share additional details, but even from the top-line findings, it’s clear that, while the excitement around AI in the business world is real, there’s still a long ways to go before it hits the mainstream.

Here's a link to the column:

Bob O’Donnell is the president and chief analyst of TECHnalysis Research, LLC a market research firm that provides strategic consulting and market research services to the technology industry and professional financial community. You can follow him on Twitter @bobodtech.

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