Why AI Matters to Industrial Markets – Part 1/7

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Industries like manufacturing, mining and construction are sometimes characterized as digital Luddites, with an odd attachment to business relics like fax machines, paper catalogs, clipboards and Post-it Notes.

In reality, of course, industrial companies have been at the forefront of technological innovation for decades, with sophisticated robots and other complex, highly-automated machinery widely deployed on the shop floor and in the field.

Nonetheless, it is true that there is a real, widely-acknowledged gap between this operational technology and business-centered information technology (IT). Industrial markets have long trailed others in their level of IT investment. This, however, is about to change.

Industrial companies are now expected to outspend their B2C counterparts on digital transformation solutions. Will this investment yield the same kind of disruption and transformation seen in industries like retail, banking, insurance and health care? This remains to be seen.

Digital Transformation is More Than Simple Digitalization

Global market intelligence firm IDC has found that most (70%) manufacturers’ digital transformation investments will not yield the results they seek. Why? For some, it will be because their efforts are not really geared toward “digital transformation” but rather “digitalization”, which is focused primarily on improving efficiency.

While efficiencies are desirable (who doesn’t want to save time, lower costs, or reduce waste?), the changes are not transformational, and the yields are likely to be minimal: industrial companies have already spent years using dozens of strategies to squeeze out every ounce of production and supply chain efficiency they can.

Digital transformation, on the other hand, goes far beyond efficiency. It is a strategy that encompasses digitalization, yes; but it also enables continuous and substantive process improvement, increased agility and, most importantly, breakthrough innovation.

What is Digital Transformation?

IT analyst firm Gartner, Inc., defines “digital business transformation” as “the process of exploiting digital technologies and supporting capabilities to create a robust new digital business model.” It’s an important definition in that it places “business” literally in the middle of “digital transformation,” and it foregrounds the development of a new business model that is data-centered (“a new digital business model”).

It is the kind of definition Jeffrey Immelt, former Chairman and CEO of General Electric, had in mind as he mused on the impact of the Internet of Things (IoT) on industrial companies. His advice to his peers? Digital transformation is going to reshape your market more profoundly and more rapidly than you can imagine: “If you went to bed last night as an industrial company, you’re going to wake up today as a software and analytics company.”

Specifically, digital transformation involves using data, analytics, and connectivity to rethink everything you do from the perspective of your customer, and using these same tools as the backbone of new products and services for a compelling, personalized customer experience. Let‘s see how this kind of deep transformation can be achieved via advanced technologies like artificial intelligence and machine learning.

Part 1: Why AI Matters to Industrial Markets

Part 2: Industrial applications of Artificial Intelligence and Machine Learning

Part 3: Differentiating Between Artificial Intelligence, Machine Learning and Deep Learning

Part 4: Benefits of Machine Learning in Industrial Contexts

Part 5: Key Challenges of Artificial Intelligence in Industrial Sectors

Part 6: Realizing the Value of Artificial Intelligence in Industrial Sectors

Part 7: Artificial Intelligence and Machine Learning at Dassault Systèmes

 

 

 

 

Read our White Paper on Artificial Intelligence In Industrial Markets

 

 

 

 

 

 

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