David Hughes
Director PTC
Artificial intelligence (AI) promises major transformation for the manufacturing sector. From accelerating design and engineering to improving production efficiency, AI has the potential to reshape how products are developed and delivered.
However, without strong data foundations in place, organisations risk creating technical debt rather than gaining a competitive advantage, according to industry specialist David Hughes. While manufacturers are eager to adopt AI-driven tools, experts warn that the sector must learn from the mistakes of previous technology waves. During the rapid adoption of new systems in the early 2000s, many organisations prioritised speed over sustainability, leading to a proliferation of disconnected custom-built applications. These systems were often difficult to manage, scale or maintain, leaving businesses burdened with long-term complexity. The results were often a plethora of disconnected, inaccessible information silos.
The technical debt challenge
AI carries a similar risk profile today, Hughes cautions. “The relative ease of building AI capability means organisations run the risk of creating ad-hoc capability that is difficult to maintain and scale – and we’ve been here before. Hopefully, we’ve learnt the lessons of the past and can avoid building technical debt.”
With AI, Hughes argues, “organisations today have multiple systems of record that are domain specific. Real value has always been derived by being able to access these different sources of truth and bring that information together in a rational way,” he explained. “AI has the potential to significantly scale value here.”
Why data foundations matter
According to Hughes, the critical factor in any successful AI strategy is the quality of the data organisations have accumulated over time. “Those data foundations need to be rock solid for AI to have any real influence,” he said. “AI on its own won’t deliver scalable value, but the ability to access connected data across engineering, manufacturing and service systems is the real enabler of intelligent decision-making. Without that foundation, organisations risk deploying AI that will deliver negligible value. It will just deliver poor results much faster.”
Turning strategy into execution
This is where experienced technology partners play a critical role. Across UK manufacturing, organisations are working with PTC partners such as PDSVISION to consolidate product data, strengthen governance and ensure core systems are fit for purpose long before AI is introduced. As a Diamond Partner with a strong UK presence and global delivery capability, PDSVISION brings both local industry insight and international best practice to this foundational work.
By addressing data quality, structure and accessibility at the outset, PDSVISION, with the backing of PTC, have helped manufacturers organise their data foundations to deliver business value from the outset. From an AI perspective, this essential groundwork will ultimately determine whether intelligent technologies, when layered on, will deliver long-term value or disappointment.
A more sustainable digital transformation
Hughes continues, ‘Our company brings more than 40 years of experience and, with our continued support to partners such as PDSVISION to help guide manufacturers through digital transformation, we have begun embedding AI capabilities directly into its engineering, manufacturing and service solutions. However, Hughes remains cautious about organisations attempting to build and scale their own external and interactive AI capability without guardrails in place.
“The organisations that succeed with AI won’t be those that move fastest,” he said. “They’ll be those that take a considered, responsible approach, treating AI as a capability layered on strong data foundations.” Preliminary studies conducted by PTC indicate that lifecycle processes spanning multiple enterprise data sources can be completed using AI, with time savings of 80% plus in some cases. When scaled across a business over a year, the efficiency gains are significant.
From an AI perspective, this essential groundwork will ultimately determine whether intelligent technologies, when layered on, will deliver long-term value or disappointment.
Building value, not risk
Ultimately, the ability to access trusted data quickly and confidently is central to the successful adoption of AI. Organisations that prioritise data governance and system coherence are far better positioned to realise AI’s potential, while those that overlook the fundamentals risk creating the next generation of technical debt. “AI can deliver extraordinary benefits,” Hughes concluded. “But only when it’s built responsibly on foundations designed to last.”
