Who is really adopting AI in their industry?

• Updated on: 2019-05-31
• Read original article here

During the space race of the 50s, 60s, and 70s, there was a reason so many monkeys and chimpanzees were shot up into space.  Getting into space is relatively easy. Getting back safely, is the hard part (How the Spaceship Got Its Shape, credit starc@) 

One particular difficulty involves atmospheric re-entry.  If a spacecraft’s speed and angle is too steep, the deceleration forces will generate too much heat.  If the angle is too shallow, other unpleasant things can happen.  Contrary to popular opinion that the spaceship will “bounce off the atmosphere like a flat stone skipping off the water surface of a pond,” what typically happens is the craft doesn’t lose enough velocity in the dense atmosphere, may miss its mark, continue on its orbit, or be exposed to heat flux for much longer periods of time.  

Science aside, re-entry has become a commonly used metaphor for all sorts of business activities. Employees will bounce out of companies if they aren’t a good fit.  Technology adoption is the same way.  Rapid uptake of technology can result in what Gartner, calls a “hype cycle,” leading to individuals burning out on new technology due to disappointment of unfulfilled promises and over-reach.  Technology without enough momentum or deep adoption will lose support fairly quickly if it doesn’t help solve enough real problems and “bounce out.”

At Bitvore, we wanted to determine which industries' artificial intelligence as a technology is making a dent.  By querying our production system for artificial intelligence or machine learning projects, implementations, rollouts, deployments, or integrations, we were able to identify around 1.7 million news stories.  Of those, approximately 8,500 were what Bitvore calls precision intelligence.  Translation: the record matches our “AI project” concept criteria, and a high confidence that one of the companies we track is associated with the record, with text that describes a situation where something important happened. In our system, we call this a signal.

A lot of interesting things. First, non-precision news has a lot of AI and machine learning projects described in the media.  Most of those either aren’t associated with a particular company, are simply research summaries, or are experimental recitations of work done with the technology. We characterize these stories as the AI industry talking about AI.  Examples include governments, trade groups, unions, industry associations, or research groups discussing the need for better AI adoption or competitiveness. Most of the world already knows they have to do something with AI, but we are far more interested in actual adoption into an industry. For that reason, the “otherwise unclassified” AI project bubble was excluded from the summary graph below.

Each bubble represents an industry.  The size shows the number of AI projects we found as correlated to the industry. 

The color shows the average sentiment across all projects in that industry.  The range of sentiment is between 0.0614 (weak positive) and 0.6159 (strong positive). Orange represents above average sentiment within their industry. Blue represents below average in their industry compared to other vendors. One thing to note is that we are using NAICS Industry codes for this analysis and they are hierarchical and distinct.  Software Publishers (511210) is a specialization of Software Publishers (Generic) (5112). You can see the full list of specializations for Software Publishers here. 

Obviously there are too many categories to do a full analysis in one blog post, but we wanted to figure out why Waste Management and Remediation Services, and Oil and Gas Field Machinery and Equipment Manufacturing were having such a difficult time with their AI adoption. 

Below is a string of stories on how algorithms and artificial intelligence are taking over the oil fields, including Weatherford International.  One company is perfecting the use of the Internet-of-Things (IoT) and AI in the oil patch.  It appears that it’s not quite perfected yet.

In addition, below is a series about how AI can revolutionize Waste Management, including Covanta Environmental Solutions, WasteExpo’s “Rise of the Robots” and cleaning up nuclear waste, Republic Services Inc., Casella Waste Systems, and companies wanting to be the “Uber of Trash."

At Bitvore, we look at a lot of different topics.  Building an off the cuff concept of an “AI project,” when combined with our years of precision intelligence news data and our reference metadata, allows us to see industry trends, do deep dives on specific companies, and put our fingers on the pulse of an industry.  Artificial intelligence and machine learning are clearly here to stay.  The technology is resulting in a major impact across all the industries in the world, however it’s not being adopted uniformly.  Where it is being adopted, some are doing so with below average alacrity when compared to adoption in other industries.  As the movers and shakers either adopt the technologies more deeply or bounce out, we're going to keep our eye on adoption.

This article was written by Greg Bolcer, CDO Bitvore and originally was published here.