Smarter Machines, Stronger Businesses: AI's Role in the Next Era of Manufacturing

In this podcast with Keith Smith, Chief Operating Officer and Co-Founder of IntelliAM, we are considering the role of AI in manufacturing – exploring the current challenges facing the industry as well as myth-busting the common barriers to adoption. IntelliAM – which stands for intelligent asset management – is a UK tech company specialising in AI and machine learning for the manufacturing industry. Many of the world's largest manufacturers – including half of the world's top 12 FMCGs – are using IntelliAM's solution to unlock insights from billions of machine asset data points. IntelliAM is on a mission to revolutionise the machine asset management industry – using AI to increase productivity, cut operating costs and drive smarter decision-making on the factory floor.   About Keith Smith: Keith is the Chief Operating Officer and Co-Founder of IntelliAM. He has 27 years of experience in the manufacturing and engineering industry, including extensive expertise in the FMCG sector. He specialises in the development and promotion of Asset Care Standards that help manufacturers unlock the full potential of their operations. In his role at IntelliAM, Keith leads all operational teams, driving the development of the IntelliAM platform to help customers achieve world-class asset care standards.  He's able to speak about AI adoption within the manufacturing sector and how it can help manufacturers to unlock greater productivity, quality, performance, efficiency, and safety, while also reducing waste and increasing throughput in the UK's manufacturing sector. Topics include: What the biggest pressures facing manufacturers today and how rising demands and shrinking resources are reshaping the way they operate. Why traditional predictive maintenance systems are struggling to keep up with modern manufacturing environments Examples of how outdated maintenance methods are leading to costly downtime or inefficiencies on the plant floor Ways AI fundamentally changes the maintenance game, particularly in interpreting asset data and predicting failures before they happen Limitations of traditional condition monitoring tools and human interpretation and how does IntelliAM's approach go beyond them? IntelliAM's six-step AI model: a structured journey rather than a quick fix The importance of industry-specific knowledge in AI deployment and how IntelliAM bridges engineering expertise with technology Common misconceptions about AI adoption in manufacturing, from job loss fears to ROI concerns Shifting mindsets from reactive to proactive maintenance and how AI helps manufacturers lead rather than follow The future of intelligent maintenance and how manufacturers can prepare today