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From Unilever to Heineken to Mondelēz, companies in the food and beverage industry have been embracing and promoting AI technology. This technology is being used in manufacturing to help reduce costs, bring products to market, and create new items to meet specific consumer demands. However, companies without a clear strategy for their use within their supply chain are yet to see results after adoption.
A study published by software developer IFS in August found that expectations of what AI can achieve within manufacturing companies are not being met when it is implemented in practice. The survey, comprised of responses from more than 1,700 C-level executives at manufacturing companies, found that despite continued optimism about the positive aspects of AI, barriers remain to seeing tangible benefits through cost savings and innovation.
According to Kevin Miller, CTO at IFS, a huge factor influencing the rapid adoption of AI is pressure from corporate boards. But he cautioned that companies aren’t always looking at which AI components can improve their supply chains in a tangible way.
“Companies are sometimes competing to find solutions,” Miller said. “AI is still in its infancy, and the results it provides may be wrong.”
More than half (55%) of manufacturers surveyed believe that a lack of a strategic approach to technology within their company is hindering their ability to leverage technology to succeed. Limited expertise in technology was cited as the most common challenge facing businesses, with 43% of IFS survey respondents citing technology as a key factor slowing progress.
Miller added that while artificial intelligence has been presented as a magic box to solve the problem, it’s not that simple.
According to Miller, AI can provide holistic benefits to the food and beverage production process. One IFS customer, a snack food manufacturer, noticed that production quality was declining as raw materials expired sooner than expected. The company has installed some sensor devices to detect the temperature of the facility with automated fans. When the temperature rises, the fan operates to circulate cool air, improving food quality.
“This version of AI that they’re using isn’t really about doing things that humans can’t do, it’s about automating them to the point where there are more data collection points that can spot anomalies much more quickly than a human can do,” Miller said. .” he said.
“Companies need to be prepared for this type of change. It’s important to start with the basics: ‘What is the goal or challenge we are trying to solve?’”
