We recently featured in The AI Journal, where our CEO and Co-Founder, Tom Clayton, spoke about how AI and ML are changing the face of what’s possible in manufacturing.

If you missed the original article, catch up below.

 

The UK’s food and drink manufacturing sector is an economic powerhouse, contributing billions annually and employing thousands across the supply chain, however productivity challenges continue to constrain the sector’s full potential.

In an industry where efficiency is everything, AI and machine learning have the potential to unlock transformation in food and drink manufacturing by optimising production schedules, reducing downtime, and automating quality control.

The UK food and drink manufacturing sector is currently sitting on an opportunity estimated to be worth up to £14 billion in growth to the UK economy, according to the Future Factory Report from the Food and Drink Federation (FDF) and strategic delivery consultancy Newton.

Whilst some of the biggest players in the industry are embracing AI, many remain hesitant to implement new technologies due to perceived barriers.

So why is the adoption of AI and machine learning so slow in what is widely perceived as a creative and innovative sector?

The Future Factory Report estimates that unlocking digital innovation can yield seismic growth, but the report highlights four key areas for concern preventing investment:

• Companies worry they won’t see immediate Return on investment (ROI).
• Concerns persist about having the right talent available to drive digital transformation.
• Leaders assume that modernisation requires costly new equipment.
• Uncertainty exists around how to integrate AI into existing workflows.

In my experience, these perceived obstacles are more mental than material.

By shifting the mindset and leveraging AI strategically, businesses can achieve significant improvements without large capital expenditures.

The reality is that AI and machine learning presents a game-changing opportunity—one that doesn’t require expensive factory overhauls or disruptive machinery replacements.

Through harnessing data from existing equipment, AI can deliver powerful insights that drive measurable productivity gains, optimise operations, and future-proof businesses.

One of the industry’s biggest untapped opportunity lies within the data embedded in plant machinery.

Machine Programmable Logic Controllers (PLCs), drives, and IoT devices capture vast amounts of operational data, but much of this remains under-utilised.

AI-driven analytics can extract and contextualise this information, providing manufacturers with real-time insights into Overall Equipment Effectiveness (OEE), energy consumption, waste reduction, and process optimisation.

AI as a Productivity Enabler

Contrary to common misconceptions, AI doesn’t require replacing legacy machinery. It can seamlessly integrate with existing assets, extracting hundreds of millions of data points monthly—regardless of machine age or make.

The fear that AI will replace human jobs is also misplaced. Instead, AI enhances human expertise by creating new roles in data science, analytics, and productivity advancement.

For AI to be effective, it must work collaboratively with manufacturing experts. Engineering teams play a critical role in tagging, coding, and refining algorithms allowing AI to become self-learning and continuously improve efficiency. This partnership between humans and machines is already proving to be evolutionary.

One FMCG manufacturer recently implemented AI-driven OEE analysis and predictive maintenance, capturing 400 million data points per month. By analysing machine alarms, settings, running parameters, and additional reliability sensor data—including temperature, vibration, and stress wave readings—the company unlocked new levels of operational insight.

The impact was a 6% increase in line performance without investing in new machinery and is just one example of how a different mindset can deliver outstanding results.

Operators and supervisors at this FMCG manufacturer can now detect micro- and macro-stoppages, optimise machine settings, and reduce waste streams, all by using real-time data insights. This demonstrates how AI and machine learning, when applied correctly, yield tangible improvements with minimal disruption.

The Future Factory Report also highlighted how many companies are accessing only 1% of the data available within their facilities. The digital champions they’ve appointed are still, somewhat alarmingly, using Excel spreadsheets and the industry is ripe for overhaul.

It is evident that the industry is just beginning to scratch the surface of AI’s potential.

Junaid Mujaver, a Partner at Newton, says boldly in the report: “There’s no doubt in my mind: this is the moment to harness the full power of AI, automation and digital to create a food system fit for a fast-changing world.”

As global food demand continues to rise, AI will be critical to how we scale production sustainably. Predictive analytics, automated quality control, and intelligent supply chain management will redefine how food is manufactured.

Over the next 25 years, we’ll need to produce more food than humanity has ever produced before. This means food manufacturers will need to embrace technology and innovation to help meet demand and align with world sustainability goals.

Manufacturers face unprecedented challenges as they scale up and continue to meet ever-changing green objectives.

Food waste remains a major challenge, with millions of tons lost each year due to inefficiencies in production and distribution.

AI-powered analytics can identify patterns that lead to waste, allowing manufacturers to implement smarter resource allocation strategies. Additionally, AI can fine-tune energy consumption by adjusting production schedules and machine usage in real-time, helping companies reduce their carbon footprint while cutting costs.

AI and machine learning are no longer futuristic concepts but are instead practical tools that can drive global change.

Ultimately, whether manufacturers are ready or not, technological convergence is coming, and AI and machine learning are redefining what’s possible in the sector.

It’s now widely accepted that manufacturing is shifting from an art to a science, and businesses that embrace AI will lead the next era of food production. The UK has an advanced food and drink industry, and this opportunity exists to strengthen our sector and ensure it’s groundbreaking for all manufacturers, from the largest to the smallest.

By adopting digital transformation now, the industry can build smarter, more agile factories that adapt to consumer demands, improve sustainability, and secure long-term growth.

AI and machine learning is building resilience, preparing the sector for the future, and is the single most important driver to unlock the capacity to feed the world’s expanding population in the years to come.

The AI revolution isn’t just coming—it’s already here. And for those ready to seize the opportunity, the future is full of promise.