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.

Defining AI in Relation to Digital Transformation

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).

Why AI is Important to Digital Transformation

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. While this process is definitely faster than creating paper-based copy, it still is not necessarily optimized. For instance, many engineers are given system design requirements before they begin – and in a non-AI-enhanced program they would have to build the design from scratch. Generative design uses AI to automate this complex process, automatically generating the optimum design with minimal manual input. It’s a powerful behind-the-scenes technology that makes engineers faster and more efficient and results in innovative designs.

It is not enough to collect data from DX initiatives. Without an AI component, the likelihood of any collected information from various stages of the product lifecycle being utilized to improve efficiency or reduce breakdowns is low. In addition, organizations not currently pursuing AI initiatives within a larger DX strategy risk falling to digital laggard status. A 2021 study from PwC found 86% of its respondents identified AI as a mainstream technology. Roughly 33% have already started implementing limited AI use cases, while a quarter of respondents had fully enabled, AI-augmented processes in widespread adoption.

How AI Works with the Cloud to Empower Digital Transformation

Frequent readers or current clients of PTC may have noticed a shift in our messaging as we promote the increasingly cloud-based nature of our software. AI is part of the reason for this shift. AI needs processing power and most organizations do not have the space on-premise for extensive server rooms. Software as a Service (SaaS) products like Onshape and Arena make special use of AI, as the larger the database, the more capable and efficient the AI becomes.

SaaS solutions, which place the vast majority of computer processing in the cloud, give the benefits of AI without so many burdens. AI is key for companies becoming more agile and more reactive – even predictive -- in their problem solving. A traditionally automated solution does not need the cloud the same way AI does, but it also is not utilizing nearly the same amount of computing power to analyze the data in way that will give a competitive edge. For more information on just what impact this will make, please see this highlighted video from LiveWorx 2021:

What is the Future of AI in Digital Transformation?

The effects of AI in DX efforts are already felt today at multiple access points. Engineers designing CAD files with generative AI can see automatic updates in their design parameters, which opens up new design possibilities, including viable alternatives not considered before – but, when used, may be lighter, reduce material cost and save on part construction and deployment.

The executive trying to improve efficiency across her multi-location organization has access to analytics offered by the AI platforms, rather than just a surplus of data. With it, she can better execute an AI enterprise strategy. Improvements include greater visibility into company initiatives (either at the corporate or departmental level), which can accelerate the approval and production processes for new products and solutions, thus shortening time to market without bypassing key steps.

Going forward, PTC expects to see more companies embrace AI in their DX initiatives to maintain a competitive advantage. AI is integral to some of our most exciting products and will continue to power PTC solutions for years to come. This is not about replacing people with computer software. It is about efficiently analyzing and acting upon cloud-based data, giving people the tools they need to succeed today and tomorrow.