Rewiring industrial value creation through AI-driven transformation

Alan Lavery, Director Applied Intelligence – GenAI Lead, KPMG in Ireland

Artificial intelligence (AI) continues to grab our attention in headlines, newsletters and podcasts, and with good reason. The past year has seen a significant shift, not just in the continued development of more advanced models and capabilities, but also the uptake and adoption within global businesses who strive to benefit from this game changing technology. AI is no longer a hot topic or future-forward concept for manufacturers – it’s a decisive force redefining the foundations of industrial value creation. At KPMG, we work at the intersection of advanced technology and industrial strategy and our latest global insights point to a clear trend: manufacturers who embed AI across the enterprise are setting the pace for competitiveness, resilience and growth.

In a KPMG global survey of senior AI leaders in manufacturing, 93% affirmed that full integration of AI across business functions provides a significant competitive edge. And yet, on the factory floors and in boardrooms around the world, we continue to observe a common challenge: AI adoption is often fragmented, isolated within functional silos and misaligned with overarching business goals.

This paradox defines the current state of AI in manufacturing. On one side are the digitally mature ‘smart industrials’ embedding AI into core operations – from predictive maintenance to intelligent scheduling. On the other, the traditional manufacturers who remain stuck in experimentation mode, piloting isolated use cases without connecting the dots across the value chain. The result? Missed opportunities, technical debt, suboptimal returns on investment and a growing divide between industry leaders and laggards.

AI must not be viewed merely as a tool to optimise discrete processes, and switching on one isolated technology will not solve all issues. Its true power lies in enabling a systemic transformation – reengineering how intelligence is applied across business functions including R&D, production, supply chain, customer engagement and enterprise support functions. The most successful manufacturers are those treating AI not as an initiative, but as a strategic operating model, with clear value pathways tied to core business outcomes. This is further enhanced by a renewed focus on data across the enterprise, where strategic focus and integration serves as a core foundation for value creation.

Through our advisory work with global manufacturers, we’ve identified four pivotal domains where AI is driving enterprise-wide impact.

1. Smart Production and Supply Chain Integration
   AI is redefining how manufacturers respond to volatility and demand shifts. By combining real-time market data with internal operations intelligence, AI enables dynamic scheduling, precision logistics and proactive risk mitigation. The benefits are substantial: improved forecast accuracy, leaner inventories, faster cycle times, improved storage and logistics, and enhanced supply chain resilience.
2. Augmenting the Industrial Workforce
   Contrary to automation fears, AI is enhancing – not replacing – the manufacturing workforce. Advanced AI is supporting frontline workers with new access to vast volumes of documents, contextual training, intelligent task guidance and greater adaptability on decision-making. This collaborative model empowers workers to shift from repetitive and lengthy tasks to higher-value responsibilities, driving both productivity and job satisfaction.
3. Digitising the Back Office
   Historically overlooked in digital transformation, administrative and support functions are now being reinvented through AI. In finance, procurement and HR, intelligent automation is streamlining transactional processes, enabling greater focus on forward looking insights and freeing up resources for strategic initiatives. These productivity gains extend the impact of AI well beyond the production floor.
4. Driving Sustainable Manufacturing
   AI is increasingly central to sustainability goals. From energy optimisation and emissions tracking to circular design and waste minimisation, AI-powered solutions are helping manufacturers meet business and regulatory targets while reducing operational costs. Sustainability and profitability are no longer mutually exclusive – they are now aligned through intelligent operations.

Despite these advances, many organisations remain stuck in the so-called ‘pilot purgatory’ – testing isolated AI applications without scaling them into enterprise capabilities and aligning them with business and data strategies. In our experience, manufacturers that succeed in scaling AI share several distinctive traits.

• They understand and invest in connected technology infrastructure. By unifying data across business functions, e.g. R&D, operations, marketing and customer – leveraging cloud infrastructure and modern data platforms – they create the conditions for real-time intelligence and system-wide optimisation.
• They prioritise business-aligned AI. Successful AI strategies are grounded in core business need, e.g. cost reduction, customer retention, acquisition, logistics improvements, asset management and stock optimisation, rather than being driven by hype or vendor promises.
• They focus on human-centred change. These organisations engage operators, engineers and business leaders early in the AI journey, addressing concerns about job impact and control. They implement explainable AI and governance frameworks to ensure transparency, trust and ethical use.
• Finally, they foster cross-functional collaboration. Data scientists, domain experts and frontline workers co-create solutions, embedding operational insight into algorithmic design. Crucially, they invest in continuous learning and upskilling to enable sustainable transformation.

As the sector evolves, we see a new frontier emerging through ‘Agentic AI’. These next-generation systems move beyond the sometimes-transactional nature of current AI solutions. They don’t simply automate – they support workflows, help with end-to-end tasks and become decision making agents, trained in specialist areas of our business. Imagine self-optimising production lines, autonomous procurement networks and AI agents that orchestrate real-time decisions across global value chains. This is no longer science fiction – it is the next phase of digital industrialisation.

To prepare, manufacturers should act on four strategic imperatives:

1. Align AI to enterprise value streams, not just isolated functions.
2. Embed trust by design, through transparent models and robust governance.
3. Invest in scalable, secure technology foundations that support rapid innovation.
4. Cultivate a human-AI culture, where people and machines enhance each other’s strengths.

The manufacturing sector stands at a critical juncture. What was once defined by physical assets and process efficiency is now being reshaped by digital intelligence and adaptive systems. The winners will be those who can break down legacy silos, orchestrate AI across the value chain and embed intelligence at every level of the organisation.

At KPMG, our global Manufacturing and AI practice brings together deep sector knowledge and advanced technical capabilities to help manufacturers navigate this transformation. We support organisations in developing integrated AI strategies, building the right partnerships and realising measurable business outcomes.

AI is no longer a future consideration – it is today’s imperative. The question is not whether to adopt it, but how to test quickly and scale it effectively. By rethinking operating models, empowering people and embedding intelligence across the enterprise, manufacturers can unlock the next era of industrial value creation.