The Role of Artificial Intelligence in Digital Transformation | 7wData

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As we stand in 2022, the terms artificial intelligence (AI) and digital transformation (DX) are linked. Even when organizations or thought leaders only name one, they will likely still be referring to both working in tandem. AI, in short, already is and will continue to power the next phase of DX initiatives and software, creating opportunities and improvements not possible previously.

Since AI has myriad definitions, depending on setting and usage, we must first elaborate on its meaning as it relates to the concept of DX.

Most often when AI is discussed in the context of engineering and manufacturing, we are actually referring to artificial narrow intelligence. It is not a matter of machines thinking like people, but rather sophisticated algorithms designed for a pre-defined task with a well understood set of inputs. Artificial narrow intelligence designed for CAD applications, for instance, will never have a “thought” outside those specific, previously outlined parameters.

Unlike standard automation, AI-powered processes can react to new information or unexpected changes. That is its biggest benefit. Unrestricted by predetermined outputs, AI algorithms learn from success and failure. They are capable of self-correction and can analyze data to detect incoming challenges before they occur.

From another perspective, automation provides optimal value when deployed in a pre-existing, well-defined process, such as established manufacturing lines. The user always dictates automation processes within the confines of a set of given inputs. AI, by contrast, is best utilized when trying to overcome challenges that are more complex, or not defined by preset rules. If the user gives an AI a set of inputs, the AI will analyze the data and suggest the optimal course of action, or just execute it automatically (depending on the situation).

At PTC, we believe that the greatest power of digital technology is to transform the physical world – improving productivity, innovation, and impact. To that end, AI is essential for many complex DX applications. Without it the digitization of products and processes would produce amounts of data that no human could be expected to analyze and react to within an acceptable timeframe. As a result, if you lift up the hood of nearly any PTC product, you’ll find AI powering critical applications, such as the generative design in Creo, or predictive analytics in Thingworx.

Let’s use Vuforia for an example. Vuforia is a powerful, scalable enterprise augmented reality (AR) platform – but what makes it so? Well, unlike simpler GPS-based or QR/barcode-based AR programs, which rely on data stored outside the object for AR functionality, Vuforia products increasingly use computer vision to actually identify the hardware components the user is looking at based on shape and other visual features. To do that it needs access to a database, and it needs to be able to read the patterns in the shapes to accurately identify what the user is seeing. This creates a greater level of efficiency for the user.

For another use case, let’s look at how generative design is used in CAD. It is no secret that many of today’s engineers use 3D CAD programs (such as Creo) as essential tools for creating and developing product designs.