How AI can help your food and beverage business

Rising costs, tariffs, supply chain pressures, labour shortages and climate change: the food and beverage sector is under stress. 

But artificial intelligence (AI) can be a great way to increase productivity, reduce losses and innovate faster to meet to consumer demands.  

“AI is driving quality, accuracy and productivity for SMEs in the food and beverage sector, where inputs have a limited lifespan and where errors can have an impact on public health,” says Dr. Martin Coulombe. President of Osedea, a Montreal-based consulting firm specializing in digital and AI solutions.

8 smart ways to use AI to create value

1. Quality control

With computer vision, high-speed cameras capture real-time images of your sorting, packaging or production line.

Then using machine learning, these images are analyzed to detect anomalies in the size, shape or colour of your products—differences that may indicate a quality defect, faulty packaging, or the presence of foreign objects, such as a piece of wood or an insect.

Computer vision requires good imaging conditions (lighting, contrast, camera position) as well as good initial definition of what is considered good and what is defective. 

“These conditions are essential for the artificial intelligence model to learn properly. Computer vision also requires large volumes of data to be effective,” says Steven Bucaille, a machine learning engineer at Osedea.

Real life use case:

An SME that manufactures food could use computer vision to identify faulty packaging and mislabelling. Once anomalies are detected, the AI can trigger alerts or automated actions to prevent defects.

2. Forecasting demand and production

AI can help predict demand and fine-tune supply chain and production management. 

It will analyze data on past sales, consumption trends, seasonality, weather and other variables so that you can adjust the volumes of ingredients you purchase, keep a close watch on inventory, anticipate product life and absorb seasonal variations.

Real life case:

A dairy company using AI can spot trends like a preference for protein-rich products among younger consumers. 

With this information in hand, the company could boost production of protein-rich yogurts and beverages.

3. Innovate and accelerate research and development

Generative AI can be used as an assistant to design new products, test combinations of flavours, suggest ingredient substitutions and accelerate recipe development.

“For companies that often launch new products, this can save time and shorten time to market,” says Coulombe.

Real life case:

A restaurant chain could use AI to update their menu and test new recipes. By analyzing sales, customer preferences and market trends, AI can identify such things as higher demand for vegetarian menus in some locations and then propose new recipes. 

4. Perform predictive maintenance

It can cost a lot when mechanical failure brings production to a grinding halt. 

AI can analyze sensor data to identify problems before they cause havoc.

“It could be an engine showing signs of weakness, a ventilation system deteriorating, or equipment requiring specific maintenance. All of this helps increase efficiency and productivity,” says Coulombe.

Real life case:

In a frozen vegetable plant, AI can detect that a conveyor motor is vibrating more and consuming more energy than usual. The crew will be alerted prior to outage, so they can take quick action, make any necessary repairs and prevent production delays.

5. Ensure regulatory compliance and prepare for audits

Agri-food businesses must follow strict standards and hold certain certifications such as HACCP, GMP or GFSI.

AI can quickly gather all the documentation you need for these certifications and prepare your company for audits. 

But remember to always go over the AI analysis with a member of your team. 

Real life case:

A poultry business could use AI to prepare for a compliance audit to prove it is raising its birds without the use of antibiotics. AI will collect all the required documents, review the regulations to identify requirements and automatically generate checklists, saving you the effort of doing it manually.

6. Improve the traceability of your products

More and more people want to know where their food comes from, how long it has travelled before arriving on their plate, and whether the businesses in the agri-food chain have acted responsibly towards the environment, their communities, and their staff. 

AI allows you to answer all these questions through automated data collection and analysis. However, this is more within the scope of larger companies.

Real life case:

A meat-processing business could use AI to automatically read lot numbers on delivery, record the suppliers and date of receipt, and monitor meat storage temperature. This helps to trace the affected lots in case of food quality or safety issues.

7. Optimizing customer service 

Several platforms offer chatbots that can integrate with existing customer relationship management (CRM) solutions, websites or other marketing systems. These chatbots can help you respond more quickly to frequent questions and requests from customers and free you up for more strategic work.

Real life case:

Restaurants could include chatbots on their websites to handle bookings, track online orders or answer questions about ingredients, allergens or hours of operation.

8. Administrative tasks

You can use artificial intelligence to extract information from purchase orders received by email, automate invoice processing or schedule staff based on your production needs.  

Real life case:

In the case of a craft brewery, when a restaurant places an order for 20 cases of beer, an AI agent could read the email, enter the order into the system, create the invoice and notify the team. 

What are the benefits of AI for the food and beverage sector?

1. Operational efficiency

AI makes you faster and more efficient. Automation frees up workers for value-added tasks. 

2. Revenue growth

AI helps to better anticipate demand and meet customer expectations.

3. Margin protection

AI helps reduce costs, waste and errors. 

4. Quality control and food safety 

By detecting errors or anomalies, AI lets you monitor risk automatically, improve product quality and safety, and prevent errors before they happen.

5. Customer experience

AI can provide a more enjoyable buying experience for your customers. 

Where do I begin?

Before you pick a technology, define what challenges your company is facing. Here are some questions to ask:

• Where do we make mistakes?
• Where are we wasting time?
• What creates customer dissatisfaction?

Once a problem is well defined, you can search for the AI tool that best addresses it. 

Another good practice is to audit current systems and processes, then check to see whether your data is sufficient, reliable and suited to AI tools. 

Steven Bucaille, a machine learning engineer at Osedea, says that between 60% and 80% of AI projects fail due to poor problem definition or lack of data.

Getting started

Start by identifying a recurring, high impact process that can be automated using AI. Test the solution on a small scale before deploying it more widely and be sure to communicate your goals to your teams. 

“The best AI project is rarely the most ambitious one, but rather the one that addresses a well-defined problem and whose gains can be measured quickly,” concludes Dr. Coulombe.

Next step

Get advice and preferential-rate financing to adopt AI, digital tools, and state-of-the-art equipment.