All the signs point to AI implementation across industries, but the practical implementation differs wildly depending on which industry we’re talking about. The most significant message of the industry study from McKinsey and Company, which asked representatives of different industries to respond to a survey about both the area and type of AI usage, is that AI has broad, far-reaching potential to transform the structure of business.
AI Implementation Across the World
Even from 2018, there’s been a significant jump in implementation. Global usage overall has increased, with 58% of respondents using AI for at least one business function (47% in 2018) and 30% use it for multiple purposes, as opposed to 21% in 2018.
North America has the biggest piece of the pie at 63% for single-function AI, but that gap has rapidly closed between the 2018 and 2019 year. Countries are realizing the potential of AI to enhance competitiveness, with much of the growth concentrated in Developed Asia and the Pacific.
Multiple-functions are a different story. Developing markets, including China, have embraced AI as a multifunctional tool with the largest share of the pie in 2018. In 2019, India, North America, Developed Asia, Europe, and Latin America all surpassed investments for multi-function AI, but the overall picture is a neck and neck race for implementation.
So what does this look like in the real world? Industries are embracing AI overall, but the implementation looks a bit different depending on where you’re standing. The Automotive Industry has surpassed all other industries in manufacturing implementation, with 53% of respondents stating AI is an essential factor. The next closest is Pharma with 41% and Consumer Packaged Goods (CPG) at 32%.
On the Service and Operations Side, Telecom leads that area with 74%. Considering the massive maintenance needs and the drain on labor to monitor the miles of cables, for example, this is no surprise. Financial Services occupies the next space at just 55% with Travel and Logistics right behind at 52%.
Product Service and Development has a few neck and neck with High Tech at 55% and Telecom at 48%. Infrastructure and Automotive tie at 43% and Power and Natural Gas come in right behind at 42%. This sector, however, seems to be the most even implementation aspect with quite a few industries using AI in this regard. This may be the most visible way to implement AI in a digital transformation.
Financial Services is ahead of the pack in both Risk and Marketing and Sales, and no wonder. Financial institutions have taken massive hits in recent years both for the inability to protect consumers against cyberattacks and fraud while also weathering changing public perception. The upheaval across the board in the Finance Industry could be a big reason Financial Services has taken the reins here.
AI’s Specific Capabilities
As Data Sciences and AI Engineers, you’re probably wondering what capabilities companies are using to transform each of these aspects of business operations. For all industries, Robots/Automation comes in first while computer vision and machine learning tie for second.
The biggest area for Automotive is Robotics/Automation, by far, and again, they remain way ahead of the pack at 46%. For machine learning, High Tech is the biggest implementor at 54%, with Telecom catching up at 45%. Although it gets a lot of press, machine learning isn’t a huge factor in many other industries—the next highest implementation is happening in Automotive at 31%.
Computer vision seems to be a larger part of the puzzle for the Automotive industry, with 42% of respondents citing its importance. Telecom, High Tech, and Healthcare occupy a close race for the next three spots, respectively. As we begin to use computer vision for everything from maintenance to analytics to planning, we could see those gaps close.
Natural Language occupies a good chunk of the pie, but broken up on the survey sees it fall behind the first three areas. NL text understanding is currently at 24% across industries, while speech and generation come in at 16% and 15%.
If you’re planning to work in Natural Language of any kind, the most prominent industries are in Telecom, High Tech, and Financial Services across the board. Surprisingly, Automotive is also a big contender in these areas, potentially due to declining sales, higher labor costs, and interior tech features for consumers.
Physical robotics and autonomous vehicles occupy much smaller pieces of the pie, but if you’re in specific industries, these could both be viable career areas. Obviously, the automotive industry has a considerable stake in autonomous vehicles, but CPG is getting in on the action as well. For Physical Robotics, the best industries for your career are going to be the same.
AI’s Impact on Industry
The biggest takeaway from the study is that AI is transforming business operations across all fields. The specific business operation and the specific AI capability varies wildly as companies consider how best to revolutionize traditional obstacles and bottlenecks while providing consumers with more efficient service.
AI is going to continue to transform the industry, even as the hype cycle moves up and down. As companies begin to understand the ways that AI augments human labor and decision making, we could see even bigger jumps in implementation in the coming years. Curious about careers in AI Engineering or want to see the demos of the latest industry solutions? Check out the ODSC East Virtual Conference this April 14-17 and see how different industries are using AI in unique ways.