t could be argued that the past year was somewhat experimental in nature, with much anticipation about the potential
use of artificial intelligence (AI) and ‘smart’ manufacturing. While the final technology is not yet in place, many sought to break new ground and drive the industry forward. The potential for change over the coming years
is significant, and it comes at a time when broader geopolitical uncertainty is at a recent high. With that in mind, 2026 is shaping up to be a critical turning point for the manufacturing sector, where those embracing AI and smart technologies establish these systems and leverage their advantage.
There is a strong push towards digitalisation spurred by the rise of AI. In fact, around 80% of manufacturing executives plan to allocate at least 20% of their improvement budgets to smart manufacturing initiatives. It’s anticipated that smart manufacturing will transform how products are made, improve competitiveness and increase agility for just-in-time production. This is supported by the view from 82% of manufacturing executives that AI will be a key growth driver for their businesses.
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With its ability to independently set goals,
plan, reason and act with minimal human input or intervention, ‘agentic AI’ could completely alter the manufacturing and engineering sectors. This could then translate into automation with increased autonomy, known as ‘physical AI’. However, the majority of manufacturing AI currently in use is in vision systems and machine learning, particularly in process manufacturing, discrete manufacturing, engineering and maintenance. A major beneficiary of advancing AI and machine learning is digital twin technology. With increasing amounts of data available, cloud storage and the processing capabilities of AI, digital twins have become a true necessity.
The global trade environment and economic uncertainty are seeing many manufacturers seek greater agility and sovereignty. Agility is identified by many C-suite executives as a primary business challenge, with established or legacy operational models and systems generally unfit for modern manufacturing businesses. According to HSO, self-reported agility among manufacturers is at a five-year
low, and 60% are looking to improve their agility in the next 12 to 24 months. This need for greater control and localisation
also means moremanufacturers are reshoring and nearshoring. It’s clear thatmanufacturers are seeking to regain control of variables and minimise the impact of external, uncontrollable factors. Given the political and economic climate, this will certainly continue throughout 2026.
Cost competitiveness and the drive for greater efficiency have seen the need for quality management rise to unprecedented levels. With extended supply chains and complex data, more than a third of manufacturers are said to be unable to trace the root cause of quality issues. At the same time, 50% of manufacturers believe quality and reliability are significant challenges, and 40% believe it takes too long to improve product quality. One route that G&P is taking to address
clients’ quality concerns is through AI and automation. Using state-of-the-art AI-supported vision inspection system technology, we have been able to increase inspection speed, accuracy and reliability throughout the quality
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