Trends
A part of digital transformation: AI
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 softwar…
Headline
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…
Context
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?
Evidence
Pending intelligence enrichment.
Analysis
Also read: The profound benefits of 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. 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.
Key Points
- 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.
Actions
Pending intelligence enrichment.
