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9 AI trends in FMCG, food & beverages

27 April 2022 Posted by Frederik Aldelhof Digital innovation

Artificial intelligence is being applied more and more in all steps of the food and beverage value chain. From automated research and better planning, to smart devices that monitor product quality and boost sales through personal recommendations.

Banner 9 AI trends in FMCG

At Verhaert, the AI Lab experts picked up the following trends from our customers’ questions and projects. In a previous article, we discussed how AI is on its way to continuously, but radically change our lives and businesses. It’s crucial to start working on an AI vision and roadmap today. Not only to capture the value of new applications, but also to learn, implement the necessary changes and stay relevant in the future. Let’s take a look at these nine trends in our customers’ questions and projects.

Downstream

Personalization & gamification of consumer interaction

Challenge: How to increase customers convenience and personalizing user experience
Solution: Artificial intelligence allows you to personalize user interactions and even identify new parameters for personalization and differentiation. AI can also recognize demographic or behavioral patterns and adapt to them in real time. Personalized recommendations, predictive maintenance, automated additional orders and smart subscriptions, there are so many possibilities. In smart appliances, like kitchen appliances, dispensers, servers and vending machines, natural language processing and computer vision can create attractive user interfaces based on body language, spoken interaction and the user’s tone of voice.

Real time optimization, premiumization

Challenge: How to ensure optimal product quality and the correct use of a device in the field (dispenser/server)
Solution: Smart devices can automatically monitor, control and adjust parameters in real time to ensure the best quality for end users. Systems can detect anomalies and suggest actions. Let’s say you have a fancy juicer and you want to optimize the extraction of juice from some fruit that you put in. By measuring various aspects of the fruit and the environment in real time, we can enable an algorithm to optimize the juicing process.

Sales planning, logistics & stock management

Challenge: How to increase revenue and reduce costs
Solution: According to this McKinsey report, AI could prevent up to 65% of lost sales due to stock-outs, and save between 10 and 50% of warehousing costs within certain industries. By combining historical and current data, specialized AI systems can make more accurate predictions, avoiding errors in the logistics chain and optimizing stock management.

Market analysis & pattern recognition

Challenge: How to leverage on data and derive patterns for valuable insights
Solution: Companies sit on vast collections of data from sales, use of dispensers, machines and vending systems, reviews and other retail data, but fail to recognize hidden patterns in this data. However, these patterns can provide valuable insights to develop winning product and market strategies, because pattern recognition systems go far beyond standard market segmentation analysis. Customers and locations can be classified much more precisely and quickly in terms of location, seasonal cycles, demographics, weather patterns, etc. These same systems can also suggest locations where specific products are always selling well and support and simulate price optimizations.

Customer sentiment analysis

Challenge: How to understand customer appreciation in a less time-consuming way
Solution: Understanding exactly how consumers feel about your products and services is invaluable, but extracting insights from endless lists of reviews or complaints is a time-consuming activity with uncertain results. Artificial intelligence is already able to detect and classify sentiment in written and spoken language, and there are breakthroughs in recognizing emotions in facial expressions. In combination with other systems, these technologies can search through large data streams, classify them and help to escalate important messages, support customer service functions and gain insights into appreciation and hidden problems.

Upstream

Where the previous examples focused more on the end user, there’s also a constant stream of innovations and potential improvements upstream in:

Process automation

Challenge: Production processes might have bottlenecks through steps that can currently not be performed by machines
Solution: Through robotics and AI a lot of processes that could previously only be performed by humans, can now be automated. The enabler here is not necessarily the robotics, as many might believe, but the perception. These are the type of algorithms that give meaning to what they observe. Think of packaging products, gathering the required items for an order or even quality control.

In-line and at-line quality control

Challenge: Improve quality control with less effort
Solution: Quality control is one of the most important reasons that human personnel is still required in automated production lines. Through perception algorithms, quality inspection systems can be created to ensure the quality of the products being produced. Spoiled food, ripped packaging and other defects can all be detected and be dealt with in a fully automized way.

Safe work environments

Challenge: Ensure safety on the work floor
Solution: Perception systems can also be put into use to ensure safety in the workplace. Moving machines can detect when a human is in the vicinity and plan their actions accordingly. Aside from not hitting humans, it is also important to ensure that the machines themselves are operating correctly. For this task we can call upon certain predictive maintenance algorithms to detect when this is not the case.

Minimizing maintenance costs

Challenge: Determine the ideal time to perform maintenance on your machines
Solution: Through predictive maintenance you can get good estimations of the state of your machines and when they are expected to fail. With this knowledge you can determine the ideal time to perform maintenance on these machines, minimizing costs while also ensuring that your machines won’t break down.

How can you apply these nine trends in your products, services or businesses? A 360° innovative product vision of your project helps you to visualize the possibilities of AI for user experience, products and processes. Verhaert can provide development and consulting services in artificial intelligence applications, combining deep knowledge of AI technology with a system engineering approach. Starting from your AI idea or vision, we make AI concrete by building rapid prototypes and demonstrators. We also support companies in creating and fine-tuning a powerful and realistic AI product vision.

Interested in how to identify the AI opportunities for your business and other AI content? Check out our blogs and perspectives!

Tags: Artificial intelligenceDigital transformation
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About Frederik Aldelhof

Manager Innovation Acceleration Solutions 'Smart FMCG & Consumer'

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