The Apple of Your AI: Solving Food and Beverage Pain Points

The appeal of artificial intelligence (AI) lies in its ability to generate useful insights from data, which Food & Beverage Service Providers can leverage to create value.

For example, the hashtag #Food is the most popular hashtag on Instagram, with over 250 million posts on the platform. Food & Beverage Service Providers (and Instagram itself) use AI tools to analyze user data, resulting in insights that enable better marketing and, by extension, more revenue.

This blog post will explore AI use cases in the Food & Beverage industry. We’ll focus on three pain points faced in the Food & Beverage sector: shifting consumer demographics, accelerating trend cycles, and evolving regulatory expectations.

1. Shifting Consumer Demographics

The global population is growing. Fifty years ago, it was less than four billion; today, it’s over eight. By 2050, Food & Beverage providers could serve more than 10 billion people worldwide.

To prepare for this shift, Food & Beverage companies must continue to scale. That means automating processes, reducing waste, and increasing efficiency — tasks at which AI excels. For example, the start-up Wasteless uses machine learning (an AI application that enables tools, systems, and other software products to “learn” from data) to help supermarkets reduce waste by "dynamically pricing items" based on expiration dates.

Synaptiq leveraged machine vision to help an American foodservice distributor scale to meet the needs of more than 10 thousand restaurants. This solution automated the process of extracting and analyzing restaurant menu data, which allowed our client to expand its reach without increasing its labor costs.

2. Accelerating Trend Cycles

Algorithmic social media has accelerated trend cycles across industries, including Food & Beverage. Products can “go viral” at any moment, creating a meteoric spike in demand that can pose logistical challenges, only to fade into obscurity a short time later.

Predictive analytics: an AI application that anticipates future events based on past data can help Food & Beverage service providers act proactively and respond to these sudden changes in consumer demand. Starbucks, for instance, uses predictive analytics to inform its product development. The multinational chain analyzed customer data and found that 43 percent of tea drinkers do not add sugar to their tea. This insight led Starbucks to develop two unsweetened iced tea K-cups for at-home beverage enjoyment: Mango Green Iced Tea and Peachy Black Tea.

Predictive analytics can also help Food service organizations respond to accelerating trend cycles by preventing equipment breakdown, which leads to supply-chain congestion. Manufacturing software provider L2L used AI-enabled predictive maintenance tools to help specialty food maker Lakeview Farms reduce line downtime (34 percent), equipment repair costs (15 percent), and worker overtime ratio (17 percent).

3. Evolving Regulatory Expectations

Food & Beverage service providers face mounting responsibility and pressure from climate-conscious regulators to track and improve their environmental, social, and governance (ESG) scores.

In the United States, ESG reporting currently combines voluntary guidelines with emerging mandatory regulations. The European Union, the United Kingdom, Australia, Asia-Pacific (APAC), and many other world powers either enforce or are progressing toward enforcing similar requirements. Countries such as Canada are strongly considering them.

Tracking ESG requires large-scale data collection and analysis: a time-consuming and costly process for human workers, but not for AI. Consequently, many Food & Beverage organizations are turning to AI-powered tools to ensure compliance with ESG disclosure regulations.

Singaporean digital solutions company Magellan X, for instance, offers an AI-powered tool called ecoMax to track greenhouse gas emissions and fuel consumption.

AI-powered tracking tools also help Food & Beverage organizations improve their ESG metrics by generating actionable insights. For example, the startup Winnow has helped commercial kitchens reduce food waste by up to 50 percent with a smart scale that enables sustainable inventory management by tracking what ingredients are wasted.

Looking to the Future

AI applications within demand forecasting, product development, and predictive maintenance can help organizations across Food & Beverage increase efficiency, reduce waste, respond to sudden changes in consumer demand, and improve ESG scores. The future is bright for those who embrace this transformative technology sustainably.

Photo by Karla Hernandez on Unsplash

About Synaptiq

Synaptiq is an AI and data science consultancy based in Portland, Oregon. We collaborate with our clients to develop human-centered products and solutions. We uphold a strong commitment to ethics and innovation. 

Contact us if you have a problem to solve, a process to refine, or a question to ask.

You can learn more about our story through our past projects, blog, or podcast.