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Decoding AI for Food & Beverage Manufacturing | 2026 Artificial Intelligence Research

What Does It Take To Build Business-Wide Support for AI? Artificial intelligence (AI) has become a boardroom priority across the food and beverage industry, yet the criteria used to evaluate it vary widely across the business. To explore those differences, Aptean and Vanson Bourne surveyed 300 food and beverage manufacturers across the USA, Canada, UK, France, Germany, and Netherlands. While there was broad recognition that AI will play an important role in the industry, our research shows that functional leaders evaluate it through very different lenses, and there’s not a single “best way” to foster adoption. This field guide focuses on the perspectives of seven departments within a food and beverage organization: supply chain, production, logistics, operations, finance, IT, and business strategy. Each profile reveals how these functions approach and evaluate AI, helping you tailor conversations, address concerns, and build support across your business.

MEET THE PERSONAS

The Frontrunner The Gatekeeper The Evaluator The Pragmatist The Diplomat The Purist The Slow Burner

Decoding AI for Food & Beverage Manufacturing | 2026 Artificial Intelligence Research

SUPPLY CHAIN

Personality: The Frontrunner Their Mindset Supply chain teams are already thinking about AI as a means of enhancing decision-making. They’re closer than anyone else to the daily complexity of sourcing, inventory, forecasting, and fulfillment, so they recognize where intelligent automation can remove friction. They’re also among the strongest advocates for industry-specific AI. They see far more value in AI designed specifically for food and beverage manufacturing than in tools intended to serve every industry.

The Evidence Supply chain professionals are the most likely among food and beverage functional leaders to let AI make strategic decisions autonomously. Our research found 52% of supply chain directors and managers are willing to do so compared with an industry average of 44%. They’re also more inclined to let AI make financial decisions without human intervention. Meanwhile, 89% of supply chain respondents rated industry-specific AI as critical or very important, making this group one of the strongest in terms of support for solutions developed for food and beverage manufacturing. 4

Decoding AI for Food & Beverage Manufacturing | 2026 Artificial Intelligence Research

52% of supply chain leaders are willing to let AI make strategic decisions anonymously, compared to 44% industry average.

How To Discuss AI With Supply Chain Leaders Supply chain teams are already convinced that AI has a role to play. Your conversation should be centered around where it can make the biggest impact. Focus on the decisions that consume time, require constant adjustment, or rely on large volumes of operational data. Explore how AI supports forecasting, inventory planning, supplier management, and demand planning to solve their daily pain points. Generic productivity gains are unlikely to resonate with supply chain stakeholders. Demonstrating a strong understanding of shelf life, supplier variability, demand volatility, and other industry-specific challenges is far more likely to build credibility.

Decoding AI for Food & Beverage Manufacturing | 2026 Artificial Intelligence Research

Personality: The Gatekeeper Their Mindset IT teams tend to see AI differently from the rest of the business. While other departments focus on use cases, IT is thinking about how AI fits into the systems that keep your organization running—from enterprise resource planning (ERP) to warehouse solutions and transportation management software. Every new AI application is another framework to support, another set of permissions to manage, and another source of data to organize. IT wants to understand how new data and ecosystems will fit together and what impact it will have on their scope of work over time.

The Evidence Our research study found that IT professionals place greater emphasis than other business functions on governance, security, and system integration when evaluating AI. They’re also among the strongest supporters of industry-specific AI, reinforcing their preference for solutions that fit within specialized technology environments and operational systems.

Decoding AI for Food & Beverage Manufacturing | 2026 Artificial Intelligence Research

IT leaders are more concerned with AI governance, security, and system integration than any other business stakeholders.

How To Discuss AI With IT Leaders Bring IT into the conversation early and come prepared to answer more than business use case questions. Explain how AI integrates with existing systems, how it supports operational workflows, and what it will require from their department over time. Giving IT teams enough information to understand the wider implications of AI projects—rather than asking them to integrate features or resolve issues further down the line—will help you earn their support.

Decoding AI for Food & Beverage Manufacturing | 2026 Artificial Intelligence Research

FINANCE

Personality: The Evaluator Their Mindset The finance team won’t change their standards because the subject happens to be AI. They expect proposals to make the same rigorous case as any other investment, with enough evidence to show it’s worth the cost, effort, and risk. For finance, AI isn’t a category of its own; it’s another project competing for budget. They’ll want to understand where it can affect the bottom line by improving margins, reducing waste, optimizing inventory, and/or protecting profitability.

The Evidence Our research indicates that finance leaders place greater importance than other business functions on proven outcomes when evaluating AI investments. They’re more likely to be persuaded by successful pilot programs, executive sponsorship, and evidence from other organizations than by internal enthusiasm.

Decoding AI for Food & Beverage Manufacturing | 2026 Artificial Intelligence Research

Finance leaders are more influenced by pilot results, executive backing, and peer success stories than internal advocacy when evaluating AI.

How To Discuss AI With Finance Leaders Lead with evidence. Demonstrate where your AI program has already delivered measurable results, what those results were, and what assumptions underpin your expected return. Where possible, connect those outcomes to the metrics finance already tracks, such as lower inventory holding costs, reduced waste, improved labor efficiency, or stronger operating margins. A well-presented business case, backed by realistic expectations and proven results, is most likely to secure this team’s support.

Decoding AI for Food & Beverage Manufacturing | 2026 Artificial Intelligence Research

OPERATIONS

Personality: The Pragmatist Their Mindset Operations teams are less interested in what AI can do and more whether it can work reliably in the reality of a food and beverage manufacturing environment. Their priority is keeping production on schedule while maintaining quality, managing labor, and minimizing disruption. That means new technology has to fit around existing people, processes, and systems. They tend to judge AI tools by how straightforward they are to implement and manage day to day. If they can solve operational problems such as reducing downtime, improving scheduling, or helping teams respond more quickly to production issues without creating unnecessary complexity, they’re far more likely to see AI’s value and back the initiative.

The Evidence Response to our research suggests operations leaders place greater value on AI that is straightforward to implement and that their teams can run confidently. They also appear more willing to trust AI with forecasting and planning tasks than with customer-facing capabilities or financial decisions.

Decoding AI for Food & Beverage Manufacturing | 2026 Artificial Intelligence Research

Operations leaders are more persuaded by AI tools that are easy to implement than by ROI claims alone.

How To Discuss AI With Operations Leaders Open with how AI will fit into day-to-day workflows. Explain what implementation looks like, how quickly the new tools can be introduced, what training is required, and what ongoing support their team can expect. Focus on outcomes that operations teams are accountable for, like keeping production running smoothly, improving efficiency, and reducing preventable disruption. Avoid leading with ambitious long-term transformation. Operations teams are more likely to support AI when they can clearly see how it improves existing processes and adds value quickly.

Decoding AI for Food & Beverage Manufacturing | 2026 Artificial Intelligence Research

PRODUCTION

Personality: The Purist Their Mindset Production teams judge new technology purely by what happens on the line. If AI can help maintain throughput, deliver more consistent quality, or reduce unnecessary waste, they’ll see its value. They’re also acutely aware that small changes can have knock-on effects across a busy factory. Any new technology has to earn its place by fitting naturally into existing processes; if it adds complexity or disrupts established ways of working, they’ll question whether it’s worth the effort.

The Evidence Our research findings indicate that production teams are most receptive to AI that complements existing processes. They place greater value on solutions that fit naturally into established workflows and support the people responsible for keeping the factory running.

Decoding AI for Food & Beverage Manufacturing | 2026 Artificial Intelligence Research

Production teams are looking for AI tools that fit the factory, not the other way around.

How To Discuss AI With Production Start with the challenges that production teams deal with every shift. Show how AI can reduce unplanned stoppages, improve consistency between batches, and give operators earlier visibility of issues. Production leaders are far more likely to engage when they can picture AI solving problems they already recognize. Don’t position AI as something that changes the way people work overnight. Instead, explain how it supports established processes, helps teams make betterinformed decisions, and delivers more consistent outcomes without adding complexity. Finally, focus on steady improvement. Factory teams are used to refining processes over time, so they’re more likely to trust AI tools that prove their value on one line, one process, or one site before being introduced more widely.

Decoding AI for Food & Beverage Manufacturing | 2026 Artificial Intelligence Research

LOGISTICS

Personality: The Slow Burner Their Mindset Logistics teams understand that AI has the potential to improve planning, scheduling, and fulfillment. They’re not resistant to change, but they are responsible for keeping products moving while meeting delivery windows, managing shelf life, and maintaining service levels. They’ll only trust technology they can monitor, analyze, and intervene to control when needed. They’re comfortable using AI to support tactical decisions, provided the reasoning is clear and people remain accountable for the outcome. The less transparent the technology feels, the harder it is to earn their confidence.

The Evidence Every logistics respondent we surveyed agreed that failing to implement AI successfully risks leaving the business behind. But, at the same time, they expressed greater concern than average about losing control of AI systems and being unable to explain how they reach their decisions.

Decoding AI for Food & Beverage Manufacturing | 2026 Artificial Intelligence Research

Logistics teams believe AI is essential, but they want to stay in control of decision-making.

How To Discuss AI With Logistics Focus on how AI supports, rather than replaces, human judgment. Logistics teams are more likely to embrace AI when they can understand why it’s made a recommendation and retain the ability to override it when human judgment informs a different action, operational priorities change, or exceptions arise. Emphasize the tactical applications that support dayto-day decision-making, such as routing, scheduling, warehouse planning, and fulfillment. Show how AI can help protect shelf life, improve on-time delivery rate, and respond more effectively when plans change—all while leaving the final decision with the people responsible for keeping goods moving. Avoid presenting AI as something that replaces operational expertise. Instead, position it as another source of insight that helps logistics teams make informed decisions.

Decoding AI for Food & Beverage Manufacturing | 2026 Artificial Intelligence Research

Turn AI Ambition Into Business-Wide Action One of the clearest findings from our research is that there is no single conversation that wins support for AI across a food and beverage organization’s different functional areas. Supply chain teams think differently from finance. Production leaders evaluate AI differently from IT. Strategy teams are looking for different answers than logistics. It follows that successful AI initiatives depend on more than selecting the right technology. They require organizations to engage multiple stakeholders, address specific priorities, and make the case for AI in terms that resonate with each function. At Aptean, we believe AI delivers the greatest value when it’s purpose-built for the food and beverage industry and supports the needs of every function across the business. Through Aptean AppCentral, our unified AI platform, manufacturers can access industry-specific AI capabilities embedded across our software portfolio, helping teams automate routine activities, improve decision-making, and make better use of operational data within the workflows they already use every day. Whether you’re looking to strengthen planning, optimize production, improve supply chain performance, or make better business decisions, our solutions’ AI capabilities are designed to solve critical operational challenges for food and beverage manufacturers. Empathetic conversations, combined with tailored technology, create the alignment needed to translate AI ambition into meaningful business outcomes.

Decoding AI for Food & Beverage Manufacturing | 2026 Artificial Intelligence Research

To learn how Aptean’s AI-enabled food and beverage solutions can support your organization, get in touch with our team. You can also learn more about AppCentral and our purpose-built AI, Aptean Intelligence.

Aptean is a global provider of industry-specific software that helps manufacturers and distributors effectively run and grow their businesses. Aptean’s solutions and services help businesses of all sizes to be Ready for What’s Next, Now®. Aptean is headquartered in Alpharetta, Georgia and has offices in North America, Europe and Asia-Pacific. To learn more about Aptean and the markets we serve, visit www.aptean.com.

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