How is Artificial Intelligence Revamping the Food Industry?
Artificial intelligence (AI) is indeed set to transform the future of the food industry. It encourages farmers to produce high-quality yields with accurate weather predictions and enables restaurant owners to reduce waste and assist grocery stores in maximizing sales. Early adopters of this latest and growing technology are sure to become the market leaders of tomorrow. AI (Artificial Intelligence) is overtaking the attention of businesses across many disciplines and sectors, with (FP&H) Food Processing and Handling being one of them.
McKinsey said that the Food Processing and Handling (FP&H) industry is estimated to be worth USD 100 billion, and after 2021, it is expected to continue to increase at a CAGR of 5%. AI is impacting the FP&H industry in both ways — directly and indirectly. For instance, it helps farmers with weather predictions indirectly, which will help farmers produce high-quality raw material for food processing companies and help them save costs on sorting their product. Moreover, Artificial Intelligence also helps transportation companies reduce shipping costs by making food processing companies pay less for transportation. Both ways, it is helping FP&H companies to save revenue.
If you want to unhitch your business growth by potentially leveraging AI, I’ve mentioned here a few top areas that you can optimize. This blog will provide guidance on how Artificial Intelligence is revamping the food industry.
Considerable Points That You Can Optimize
- Automated Food Processing
Nowadays, Food processing has become a fully programmed activity to ensure complete hygiene and high food quality. The facilities are already leveraging AI-powered robots to compete with the skill of human hands. As a result, this has helped them expedite the pace of food production while ensuring safety.
2. Efficient Waste Management
Controlling the potential of artificial intelligence (AI) at the fork end of the farm-to-fork concept helps reduce food waste and increase efficiency. Pantries that use AI (artificial intelligence) can reduce their food waste by 60–80% within the first year. In addition, an AI-enabled camera can help them sort the foods that ultimately end up in the bin and drive sustainability.
3. Accurate Forecasting
In this digital era, many restaurant owners are leveraging AI-enabled algorithms to predict demands accurately. For example, by analyzing how people respond to discounts, social media promotions, seasonal offers, and many more, they make informed decisions about inventory management and fulfill orders without overstocking.
4. Food Safety Compliance
As we all know, safety is the most important part of the food industry. So, implementing AI-based cameras is the best option to ensure that employees follow all hygiene protocols and wear appropriate food protection gear. Also, the AI-enabled cameras help in enforcing discipline and avoiding contamination with careful cleansing of equipment.
5. Customer Support Chatbots
Many restaurants, retailers, and hotels have already deployed chatbots to convert and engage potential customers. Also, artificial intelligence app development companies can enable these interactive bots with machine learning technology to influence buying decisions and buying behaviour of food merchandise, hotel bookings, and many more. Also, buying decisions are based on the consumer’s personal preferences.
6. Using Data for Decision Making
Machine learning (ML) technology can analyze the complicated data of thousands of buyers and deliver actionable insights in a trice. Moreover, this important information can be leveraged to customize marketing campaigns, boost productivity, influence purchase decisions, target customers, price products, and much more.
7. Supply Chain Management
To simplify and streamline supply chain management AI (artificial intelligence) can be used. Also, it allows end-to-end monitoring of raw material procurement, stock levels, production, pricing, and many more. For an optimized supply chain and real-time visibility, predictive analytics can also be applied at every stage of the food chain.
8. Online Food Order Management System
A complete online food order management system gives an unparalleled food ordering experience. Also, it uses data analytics to run a 3-way hyper-connected marketplace by tracking demand, supply, and delivery operations. Connecting customers to restaurants through technologies provides a personalized and convenient experience. Artificial Intelligence (AI) & Machine Learning (ML) foster real-time demand-supply optimization to increase order value and revenue.
9. Sorting Food
Indeed, food sorting is a time-consuming and tedious process fraught with challenges. For example, as we know, the freshness of the product is key, and there are several other sorting steps to determine which type of potatoes should be used for making French fries, chips, or tomatoes for ketchup. Artificial Intelligence (AI) can solve many sorting complexities while saving time, reducing waste, improving quality, and higher productivity.
10. Developing New Products
In this digital era, the food processing industry is highly competitive. For example, Coca-Cola, the global liquor giant, owns more than 500 brands that produce 3000+ types of drinks. Yet when it comes to selecting which flavour is to be launched next, the company uses artificial intelligence (AI). As a result, it helps them identify customer demands and preferences from self-serving soda foundations that create customized drinks.
Challenges of Artificial Intelligence in the food industry
The challenges faced by AI (artificial intelligence) in the food industry are:
- Usually, people misunderstand the idea of Artificial Intelligence (AI) as a tool that will replace humans in the future. This misinterpretation is due to unawareness among people about the features of AI. Hence, this is why they are scared and make their assumptions of AI replacing humans in their jobs.
- The natural language processing (NLP) model needs to be trained efficiently to interpret and analyse data in different languages. But, the NLP model cannot interpret unstructured data present on search engines or social media websites where people use different expressions to write their views like funny attributes and sarcasm, so the NLP model might not accurately understand what humans intend to express.
- Many companies don’t understand how and why AI models should be adopted to achieve their objectives.
- Many companies face the pain of identifying relevant data and feeding the right data to the algorithm to get the expected output in the initial phase of adopting an AI model.
- AI adaptation requires extensive personnel training to work with AI models from top-level management to lower-level management. In addition, Artificial Intelligence models are expensive and not every company can afford them.
Conclusion
Indeed, the implementation of Artificial Intelligence in the food industry has triggered a paradigm shift that has resulted in reduced waste, fewer human errors, personalized products, increased sales, space-saving, faster service, seamless supply chain management, and many more. So, it is no surprise that companies are looking for artificial intelligence application development companies to kick-start their AI journeys for better business outcomes.
