The global food and drink manufacturing sector has always been regarded as creative and forward-thinking.
But when it comes to adopting artificial intelligence (AI) and machine learning, progress has historically been frustratingly slow.
That’s finally starting to change.
Across the industry, momentum is building, and the potential of these technologies is beginning to be realised, writes Tom Clayton, CEO and Co-Founder of IntelliAM.
In a sector where efficiency is everything, AI represents an opportunity for genuine transformation. Imagine optimised production schedules, reduced downtime, automated quality control, and smarter supply chains all within reach for those willing to embrace digital tools and new ways of working.
According to a recent Food and Drink Federation study, strategic use of AI, digital technologies, and automation could generate a £14bn growth surge in the UK’s food and drink manufacturing industry alone. That’s not a distant possibility – it’s a near-term opportunity waiting to be seized.
At IntelliAM, we work with half of the world’s top 12 food and drink manufacturers. In the UK, we’re proud to partner with well-known names including Müller, Mars, ADM, Weetabix, Hovis, and Diageo. These collaborations give us a unique vantage point on the productivity challenges the sector faces daily.
What’s clear is that AI doesn’t demand radical factory overhauls or multi-million-pound investments in new equipment. The real breakthrough is that AI can work with existing assets, regardless of age or manufacturer. By integrating seamlessly with current systems, it can collect and interpret millions of data points each month, creating a digital fingerprint for every component and process.
Whether data is coming from machine PLCs, IoT sensors tracking vibration or oil temperature, or cloud-based reliability systems, the insight potential is enormous.
Errors that once seemed random can now be predicted and prevented. By fine-tuning tolerances, optimising speed settings, identifying true bottlenecks, and addressing training gaps, AI helps ensure factories run at their absolute best.
Recently, we worked with a leading FMCG manufacturer to implement AI-driven Overall Equipment Effectiveness (OEE) analysis and predictive maintenance. Together with their engineering team, we captured over 400 million data points every month, spanning machine alarms, operating parameters, and sensor data such as temperature, vibration, and stress waves.
Once contextualised, this information unlocked entirely new levels of insight. The result? A 10% boost in line performance without requiring the company to purchase new machinery. That kind of improvement is a clear signal of what’s possible when manufacturers adopt an AI-first mindset.
Of course, the industry still faces significant challenges, and food waste is one of the biggest. Millions of tons are lost annually due to inefficiencies in production and distribution. Here too, AI offers solutions. By identifying patterns that lead to waste, manufacturers can make smarter decisions around resource allocation, packaging, and scheduling.
Energy efficiency is another pressing issue. Globally, nearly 20% of all industrial energy is lost to friction. This is a staggering figure in a sector already squeezed by tight margins and growing sustainability pressures. AI-powered systems can continuously monitor and reduce friction-related losses, cutting costs and carbon footprints while boosting competitiveness.
The benefits go far beyond the factory floor however. More efficient production means fewer empty supermarket shelves, more affordable groceries, less waste, and greater resilience in times of supply chain disruption. Smarter factories don’t just strengthen manufacturers, they benefit consumers, communities, and the planet.
Some argue that the complexity of food and drink manufacturing, combined with strict safety regulations and a shortage of technical expertise, makes AI adoption more difficult.
Compared with sectors like renewable energy, which already uses AI and satellite data to predict downtime and adjust capacity, food and drink has lagged behind.
But this is changing. Manufacturing is evolving from an art into a science. Those who embrace AI will shape the next chapter of food production. And the UK’s food and drink sector, already advanced in many respects, is particularly well-placed to lead.
The key is mindset. AI adoption cannot rest solely on leadership buy-in. It must extend across entire organisations. Engineering departments and production teams need to feel ownership and confidence in the technology. When they do, the gains, like the 10% productivity increase described earlier, speak for themselves.
AI and machine learning should be central to every modern manufacturer’s strategy. They are not futuristic buzzwords but practical tools for growth, resilience, and sustainability. With the right controls, layered data, and human oversight, the benefits of AI far outweigh the risks of over-reliance or disruption.
By embracing digital transformation now, manufacturers can build agile factories that anticipate consumer demand, cut waste, improve energy efficiency, and strengthen long-term competitiveness. In a world where population growth, climate pressures, and global shocks threaten supply chains, this shift is no longer optional, it’s essential.
The AI revolution isn’t coming. It’s already here. For food and drink manufacturers ready to take the leap, the future looks incredibly bright.
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