• Without an AI component, the likelihood of any collected information from various stages of the product lifecycle being utilised to improve efficiency or reduce breakdowns is low.
  • AI algorithms are capable of self-correction and can analyse data to detect incoming challenges before they occur.

The terms artificial intelligence (AI) and digital transformation (DX) are linked. Even when organisations 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.

Also read: How is digital transformation changing the healthcare industry?

Also read: The profound benefits of digital transformation

What is AI in digital transformation?

Most often when AI is discussed in the context of engineering and manufacturing, it is 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 analyse data to detect incoming challenges before they occur.

Why AI is important to digital transformation

If someone lifts up the hood of nearly any PTC product, they’ll find AI powering critical applications, such as the generative design in Creo, or predictive analytics in Thingworx.

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 utilised to improve efficiency or reduce breakdowns is low. In addition, organisations 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.

What are the benefits of AI in digital transformation?

Any technology, AI included, must be considered with an organisation’s profitability in mind. Companies today are already looking to apply DX initiatives in very controlled settings, where the outcome can be weighed against the bottom line. It has identified four key, measurable benefits of AI in DX initiatives:

1. More effective decision-making

Important decisions, contrary to many films and shows, cannot rely solely on gut instinct. Even a seasoned leader needs access to any and all relevant data in order to reach the optimal conclusion. Time is always a factor, so this decision must often be made quickly. AI can help identify and highlight important information regarding product performance, workflow optimization, and predictive outcomes.

2. Increased profitability

AI is not a replacement for human judgment, but it can be a highly effective tool when it comes to optimizing time to value. By fully automating many time-consuming tasks such as these, AI software frees up human resources to be better deployed on the more cognitive aspects of product development, all while reducing the resources needed, thus increasing the profit margins.

3. Enhanced analytics

AI can rapidly streamline every aspect of this process – delivering data results in a fraction of the time. For large manufacturers with numerous assets spread throughout the globe, AI is arguably essential for delivering actionable insights in a timely manner.

4. Holistic view of the customer

The digital world is built on data, and what that data is and where it comes from is constantly changing. In the past, tools like cookies were used to help organisations gain insight into consumer behavior. AI-enhanced software can and likely will be this next iteration, helping decision makers see their customers arguably better and more comprehensively than cookies were able to do.