The vital adoption of AI for the food and beverage industry

Saar Yoskovitz
4 March, 24

Governments came under scrutiny during the Covid pandemic when commercial food supply chains broke completely or slowed to a crawl. And when food costs skyrocketed globally last year, citizens once more urged authorities to step in.

The recent Farm to Fork conference, organised by UK Prime Minister Rishi Sunak, attempted to address the nation’s complex food supply-chain concerns. While it raised awareness of the issues and attracted some investment, it was viewed as either a transparent public relations ploy or a well-intentioned but ineffective first step.

The industry’s safety and transition to Industry 4.0 maturity depend heavily on government oversight and investment, but industrial AI technology may be what eventually delivers a real, measurable impact on everything from food quality to plant-floor efficiencies, with advantages for both manufacturers and consumers.

Governments came under scrutiny during the Covid pandemic when commercial food supply chains broke completely or slowed to a crawl. And when food costs skyrocketed globally last year, citizens once more urged authorities to step in.

The recent Farm to Fork conference, organised by UK Prime Minister Rishi Sunak, attempted to address the nation’s complex food supply-chain concerns. While it raised awareness of the issues and attracted some investment, it was viewed as either a transparent public relations ploy or a well-intentioned but ineffective first step.

The industry’s safety and transition to Industry 4.0 maturity depend heavily on government oversight and investment, but industrial AI technology may be what eventually delivers a real, measurable impact on everything from food quality to plant-floor efficiencies, with advantages for both manufacturers and consumers.

The Potential of AI in the Food and Beverage Industry

Governments came under scrutiny during the Covid pandemic when commercial food supply chains broke completely or slowed to a crawl. And when food costs skyrocketed globally last year, citizens once more urged authorities to step in.

The recent Farm to Fork conference, organised by UK Prime Minister Rishi Sunak, attempted to address the nation’s complex food supply-chain concerns. While it raised awareness of the issues and attracted some investment, it was viewed as either a transparent public relations ploy or a well-intentioned but ineffective first step.

The industry’s safety and transition to Industry 4.0 maturity depend heavily on government oversight and investment, but industrial AI technology may be what eventually delivers a real, measurable impact on everything from food quality to plant-floor efficiencies, with advantages for both manufacturers and consumers.

Within the State of Production Health Survey, it was found that confidence in AI’s capabilities is quite high among food and beverage manufacturing professionals, and that the manufacturing sector generally has begun to embrace the technology. According to the report, the top three AI use cases are  supply chain optimisation, energy consumption tracking, and overall production health.

However, it seems that companies in the food and beverage sector are overlooking one of the most significant AI use cases in the sector: AI-driven machine health.

The percentage of food and beverage manufacturers that indicate they use AI technologies to try to improve machine health and reliability is just 9%, which is much lower than the industry average of 28%.

Considering the success that many food and beverage industries have seen after using machine health solutions, this is an unexpectedly low number.

For example, one of the world’s largest food and beverage manufacturers is documenting less machine downtime and fewer unexpected breakdowns as a result of AI-driven machine health. Moreover, it is also helping them spend less on replacement parts and avoid the loss of more than one million pounds of product.

Even while AI is being used across enterprises, especially on the plant floor, businesses are often either flying blind or drowning in a sea of data they can’t act upon when it comes to knowing how or if the technology is paying off. These kinds of gaps need to be filled if AI is to be used in the industry successfully.

Nevertheless, there are rays of hope when it comes to future AI investment: 74% of food manufacturers say they plan to invest either slightly or significantly more in AI this year.

More good news can be found in workforce issues. While 73% of employers face hiring challenges, 78% say AI, IOT and Machine Learning will positively impact their workforce upskilling efforts, and 29% believe AI and advanced technologies will helpcreate new jobs in the manufacturing industry.

Navigating the Path Forward

When it comes to AI implementation, the industry is making progress in areas where it can benefit both the company and, in the end, consumers. This includes deploying AI for production health, process optimisation, and improving materials and energy efficiency. Moreover, the industry is also integrating AI into initiatives aimed at upskilling the workforce.

However, a lack of insight means they are not able to quantify the full return on investment from their solutions. With the right guidance, they could be lowering costs, reducing more downtime, and reaching Industry 4.0 standards quicker.

So, how can food and beverage manufacturers bridge this gap? Firstly, they need to approach AI strategically, understanding its potential to address specific pain points rather than expecting it to be a one-size-fits-all fix. This involves identifying key production challenges such as machine downtime, food quality, or energy tracking and then seeking out solutions tailored to these specific needs.

Moreover, when selecting an AI solution, it’s crucial for manufacturers to prioritise user-friendliness and compatibility with their workforce. Successful companies treat AI as a collaborative tool, understanding that it is a way to augment employees’ capabilities while also fostering skill development.

Furthermore, AI solutions should be seen as comprehensive packages rather than standalone technologies. This entails access to support services such as analysts, system integration managers, trainers, and change management assistance to ensure adoption and value at scale.

The evolution of AI is reshaping the manufacturing landscape, empowering companies with the information they need to enhance machine reliability, optimise processes, and revolutionise operations. This translates into tangible benefits such as time and cost savings, which can ultimately be passed on to consumers through more affordable products.

The good news is that by embracing or expanding the adoption of AI solutions, manufacturers can expedite the realisation of these benefits for both their businesses and customers.

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