NTT Data: How Gen AI Boosts Manufacturing Performance
Rapid adoption of Gen AI is transforming manufacturing operations across the globe.
For decades, industrial automation and traditional artificial intelligence have incrementally improved efficiency and output.
But Gen AI now marks a step change, altering processes from the initial design phase through to final delivery.
This form of AI, which creates new outputs using existing data inputs, is being deployed across factories worldwide. Adoption is rising in response to global supply chain shocks, labour shortages and a growing push for customisation and sustainability.
At the same time, manufacturers are attempting to modernise despite being held back by outdated systems, weak governance structures and a lack of skilled workers.
Smart factories and efficient manufacturing
NTT Data's recent study – Feet on the Floor, Eyes on AI: Do you have a plan or a problem? – explores the impact of Gen AI deployment in manufacturing and other sectors.
Surveying more than 500 manufacturing leaders in 34 countries, the report finds that 95% believe Gen AI is already enhancing efficiency and overall performance.
It also highlights a growing trend for combining Gen AI with Internet of Things (IoT) data to improve the accuracy of AI-generated insights for manufacturers, with 94% of respondents expecting this integration to yield success.
In parallel, digital twins – digital replicas of physical systems – are also being merged with Gen AI to boost asset performance and strengthen supply chain resilience. More than 90% of those surveyed say this pairing is already delivering value.
Gen AI now plays a practical role across several core enterprise functions. These include supply chain and inventory management, knowledge and quality control, research and development and end-to-end process automation.
According to Prasoon Saxena, Co-Lead of Product Industries at NTT Data: “AI is streamlining processes and redefining what's possible across the entire manufacturing value chain, from supply chain predictions to quality control.”
This flexibility is particularly helpful in industries exposed to unpredictable conditions such as shifting tariff rules.
On this, Prasoon notes that Gen AI helps companies respond faster and more effectively: “Gen AI can help organisations achieve flexibility in fast-changing business environments, especially in the face of uncertain tariff policies worldwide.”
A long list of barriers to overcome
Despite growing optimism, NTT Data’s research outlines several major obstacles preventing wider Gen AI adoption among manufacturers.
Legacy systems top this list, with 92% of respondents saying older technologies are standing in the way of progress. Fewer than half have reviewed or upgraded their infrastructure to support Gen AI.
Data is another concern. Only 41% of manufacturing leaders feel confident their organisations have the data storage capacity needed to support Gen AI's demands.
This will become a growing issue as AI models grow larger and require more computing power and storage space to run effectively.
The workforce is also unprepared for projected Gen AI growth, with close to two-thirds of manufacturers admitting their staff lack the necessary skills to use Gen AI tools efficiently.
Without focused upskilling, these gaps could create further complications and widen existing inefficiencies.
Nick Smith, UK Sector Lead for Industry at NTT Data, identifies multiple pressures facing British manufacturers: “The manufacturing sector is under pressure from rising costs, global competition, varying local regulation and increasing complexity across supply chains.
“Gen AI holds enormous potential for UK manufacturers looking to overcome these challenges, upskill their workforce and modernise core systems. Manufacturing organisations who build a strategic, responsible approach to this technology – integrating it with IoT data, digital twins and robust data foundations – will lay the digital foundations for their success over the next decade and set the pace for the next era of British industry.”
Governance gap widens
Despite widespread awareness of AI’s potential, there is limited progress in ethical and strategic implementation.
Only 47% of surveyed leaders say their organisation follows a strong framework that manages risks while aiming for value creation.
This shortfall in policy and oversight is one of the most pressing issues facing manufacturers now engaging with Gen AI.
While technology investment is growing, few have built the governance needed to ensure its long-term, safe use.
“The most successful manufacturing organisations have already integrated GenAI into essential operations,” Prasoon states. “Companies failing to plan, deploy and govern Gen AI strategically will not only have a problem, they may be planning to fail.”
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