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Opinion: Balancing data security with artificial intelligence solutions in food and beverage
Guest contributor

Guest contributor

1 August 2024

Opinion: Balancing data security with artificial intelligence solutions in food and beverage

Five years ago, AI was a novel tool in the food and beverage industry. Today, with the market valued at $9.7 billion, artificial intelligence has become essential, driving efficiency and innovation across the sector. In this article, Michel Spruijt, president of autonomous technology company Brain Corp International explores how AI is redefining the industry, addresses challenges in data privacy and security, and highlights key trends that will shape its future.

Five years ago, AI was considered a 'nice to have' in the food and beverage industry. Early adopters experimented with basic applications in quality control, sorting and supply chain management to improve operational efficiency. Today, the landscape has changed dramatically.


AI’s usage in the food and beverage market has grown substantially, reaching a $9.7 billion valuation in 2024 – up $4 billion since 2019. The technology is now deeply integrated across the entire value chain, from manufacturing to logistics, operations and customer experience. What was once a promising innovation is now an essential tool for driving competitiveness and progress in the sector.


Yet, many food and beverage leaders struggle with implementing an AI strategy effectively. Barriers such as reluctance to change, unclear ROI and a shortage of skilled workers hinder its full adoption.


One of the biggest concerns? Data privacy and security. According to a survey by Retail Economics, 46.9% of food retailers identified legal and regulatory issues as a major barrier to investing in AI.


The benefits of using AI are clear: greater data integration for improved decision-making, more sophisticated applications that delight customers and enhanced efficiency across the whole supply chain. But without a strategy to navigate evolving data safety issues, many leaders may find themselves sitting on the sidelines, or worse – fumbling their way through a complex landmine of legal and customer compliance.


Leaders need to take the time to investigate the best way forward, as the gap between organisations choosing to leverage AI and those who don’t, is only growing wider.



Autonomous opportunities abound


Three key areas where AI is significantly reshaping how food and beverage companies operate are inventory management, logistics and in-store operations. In each case, the old ways have been dramatically disrupted, and the new ways require careful consideration of data capture and management.


For example, AI-powered autonomous cleaning robots have significantly changed how retail store managers can approach facility management. Rather than struggling with a lack of available workers, staff churn and limited abilities to track productivity, AI-powered robots are enabling trackable cleaning at any time of day or night. This helps retailers consistently maintain clear stores and free up workers to do more valuable tasks.


The same goes for inventory management. The impact of improving accuracy here is significant. Data from NeilsenIQ shows that out-of-stock items cost retailers $82 billion in 2021 alone. Rather than having staff manually verify stock, pricing and product placements, AI-powered robots can also perform the same actions with more speed, accuracy and reliability, whether operating in a warehouse or retail environment.


While these innovations create massive returns in efficiency over time, teams also need a plan to manage their data and be compliant in the face of strict data privacy laws that vary by country.



Data safety challenges and strategies


As companies start to collect and analyse vast amounts of customer and operational data with AI tech, teams need to stay on top of the risks and implications that come alongside the opportunity.


GDPR plays an important role if you’re operating in the EU, as does identity data laws that vary by country. Ensuring compliance with various data protection laws across different regions can be complex, but these protocols are fixed – signalling opportunities for ambitious leaders who choose to work through technology-specific implications and arrive at a solution to create a competitive edge.


Maintaining consumer trust while collecting data for AI applications is also key, as is developing a policy regarding how you interact with suppliers, distributors and any other third parties while maintaining confidentiality.


Across all these issues, what can leaders do to move forward in the face of uncertainty?


Start by putting protocols in place that satisfy GDPR rules relating to personal data. This includes creating a clear data strategy and outlining how data is collected, stored, used and protected throughout the supply chain.


Make sure to evaluate all third-party vendors with a set of criteria so you can confidently move forward with trusted, reliable partners that can help you navigate the data landscape.


Another key is to invest in employee training. You need to educate your staff about data privacy, security best practices and the responsible use of AI technologies.


As your team experiments with new AI approaches, you want everyone on the same page around standards for data anonymisation, encryption, and vendor integration to protect sensitive information while getting the benefit of AI capabilities.


A good rule of thumb is to practice ‘data minimisation’ – meaning, only collect and retain the data necessary for powering your AI applications, reducing your risk of exposure.


By addressing challenges proactively and putting robust data management protocols in place, late adopters can begin to dip their toes into AI implementation in a way that appropriately manages the risks.



Future trends


As AI continues to reshape the food and beverage industry, several key trends are emerging that will likely come to define the future of the sector.


Hyper-personalisation will continue to drive purchases for consumers. AI is enabling unprecedented levels of personalisation in its ability to analyse vast amounts of consumer data. This includes dietary preferences, as well as past purchase behaviour.


This ability has implications for demand forecasting, inventory management and product development. Food and beverage companies that invest in AI-powered intelligence here will be able to create highly tailored products and experiences for customers.


Autonomous operations is another large trend that I believe we will only continue to see more of. From fully autonomous manufacturing to inventory management and cleaning, AI-powered robots will be able to handle the day-to-day tasks that previously required a large workforce.


With minimal human intervention required for repetitive tasks, I expect we will see more jobs created that centre around ‘co-botics’ – positions where humans and robots work together in defined roles.


The food and beverage industry is at a pivotal point where AI innovation and data responsibility must coexist. Leaders who successfully strike this delicate balance will reap significant rewards: improved efficiency, business intelligence and a competitive edge.


By embracing AI thoughtfully and prioritising data security, teams from across the food and beverage value chain can unlock significant potential, creating better experiences for staff and customers alike.

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