Embracing AI: Why Food & Beverage Companies Are Hesitant
Artificial Intelligence (AI) is transforming industries across the globe, and the Food & Beverage (F&B) sector is no exception. From predictive analytics to automated quality control, AI promises to revolutionise how food is produced, packaged, and delivered. In our discussions, we find many companies remain hesitant to take the plunge. With the AI in Food & Beverage market projected to explode from $8.45 billion in 2023 to over $67 billion by 2030 – a staggering 39.1% compound annual growth rate – the question isn’t whether AI will transform the industry, but how to gain the most advantage.
Yet despite the compelling numbers, significant barriers continue to slow down AI adoption across the sector. Understanding these obstacles, particularly in the context of ERP systems, is crucial for food and beverage companies looking to maintain competitive advantage in an increasingly digital marketplace.
Why some Food & Beverage companies are holding back
The Trust Deficit
One of the most significant barriers to AI adoption in the food and beverage industry is a fundamental trust issue. Unlike other sectors that have embraced digital transformation more readily, food and beverage companies often operate in highly regulated environments where safety and compliance are paramount. The idea of handing over critical decisions to algorithms can feel risky when consumer health and regulatory compliance are at stake.
It’s vital to have honest discussions with consultants like Evolve4 about risk and the benefits of increased efficiency and cost savings.
Time and resource constraints
A recent industry survey reveals that 50% of food companies are prioritizing AI investments in 2025, driven by goals of boosting production efficiency and cutting costs. However, this statistic also means that half the industry is still on the sidelines. One major reason is the significant time investment required to properly evaluate, implement, and optimise AI solutions.
Food and beverage companies, particularly smaller and mid-sized operations, may lack a dedicated AI team with the expertise to assess technologies effectively. The learning curve is steep, and the pressure to maintain daily operations leaves little bandwidth for exploring new technologies. This creates a chicken-and-egg scenario: companies need time to investigate AI benefits, but they don’t have time because they haven’t yet realised the efficiency gains that AI could provide.
Legacy infrastructure challenges
Many food and beverage companies operate on legacy ERP systems that weren’t designed with AI integration in mind. The implementation of AI is a significant change, but with a modern ERP like Evolve4 working in tandem, it will be a huge, transformative step forwards from legacy systems.
Regulatory uncertainty
The food and beverage industry operates under stringent regulatory frameworks that vary by region and product type. Companies worry about how AI implementation might affect compliance with FDA regulations, HACCP standards, or other food safety protocols. The lack of clear regulatory guidance on AI use in food production and processing creates additional hesitation among risk-averse organisations. This is a topic that comes up in almost every recent discussion between F&B industry professionals. But, the solutions are available today and are built into the ERP – by maintaining its central position in the ecosystem the ERP seeks to maintain compliance and keep pace with regulatory changes.
ERP systems: the perfect AI testing ground
Despite these barriers, ERP systems represent one of the most promising areas for AI implementation in the food and beverage industry. ERP platforms already serve as the central nervous system for most operations, making them natural candidates for AI enhancement. Our team are ready to discuss the benefits of our modern ERP and of AI, so why not get in contact to tell us about the challenges you face?
We’ll continue to look in-depth at AI over the next weeks, so please check back or follow us on LinkedIn.
