However, there's still widespread uncertainty about what it actually is, how it works and how it can benefit the food and beverage sector.What is AI? What is machine learning?AI is the ability of a computer or machine to mimic or imitate human intelligent behavior and perform human-like tasks. It performs tasks that require human intelligence such as thinking, reasoning, learning from experience, and most importantly, making its own decisions.Machine learning is a subset of AI. It is computer systems that can learn and adapt without being explicitly programmed or helped to. Machine learning uses algorithms and statistical models to intelligently analyze data, drawing inferences from data patterns to inform further action.
Where does AI fit into the food and beverage sector?Put simply, AI (machine learning in particular) has the potential to optimize all areas of food manufacturing, facilitating smart, industry-specific applications to improve every aspect of the supply chain, from farm to fork, helping to build agile supply chains and drive revenue growth.With its ability to factor in an inordinate number of data values, parameters, what-if scenarios and other contributing factors, machine learning can produce accurate and timely recommendations for almost every aspect of the food supply chain. Ultimately, this provides a competitive advantage that it would be impossible to replicate without the application of AI technologies.Where is machine learning being used already?The uses of machine learning for the food and beverage sector are seemingly limitless. Take precision farming, for example, an area where machine learning is delivering new depths of insight. This might be analysis of past harvests in terms of both quantity and quality, in combination with weather forecasts to inform which fields need watering and when, or when to use fertilizer perhaps.
More food and beverage organizations are turning toward AI to help reduce waste and identify inefficiencies within the supply chain.Planning for all eventualitiesRecently, food businesses could be forgiven for thinking that the only thing they can be certain of is uncertainty itself. With more unpredictable variations in weather conditions, what about the role of machine learning where there are potentially no data patterns to be found? What machine learning can do is help better understand the risks of changing weather conditions and how they can impact harvests globally. It's this increased understanding that can inform the strategies needed to mitigate these risks. But, even with all the latest machine learning technologies, to ensure these strategies are effective requires consensus. As the UN's Food and Agriculture Organization (FAO) points out, every party involved in the food supply chain needs to become more resilient, minimizing their use of water, energy and other resources, all changes that can be underpinned by machine learning.
As technology develops and as more businesses discover the benefits that can be realized with the application of AI, so AI capabilities will develop even further still, refined to solve specific industry or business problems. As we're seeing already, the considered application of AI technologies is helping businesses right across the food and beverage industry and supply chain, and this is only set to increase over the next few years. AI is already proving to be a driver of real efficiencies as well as helping businesses to plan for all eventualities, delivering the actionable insight that's needed to stay one step ahead at all times.