With 2025 now in the rearview window, the business side of AI in consumer packaged goods (CPG) looks less like a sudden technological disruption and more like a gradual cultural shift—one that has revealed surprising attitudes, persistent challenges, and emerging best practices that will shape how teams adopt AI in 2026.
Curiosity high, confidence lagged
One of the year’s biggest surprises was how curious CPG teams were about AI.
Whether in R&D, marketing, operations, or supply chain, people wanted to understand how AI could fit into their work. But hesitation often eclipsed that curiosity. Many weren’t afraid of job loss—at least not primarily. Instead, teams worried about using AI incorrectly or not knowing where to begin.
Another unexpected signal: how many people wished AI would simply “do everything.”
That impulse wasn’t naïve—it was a reflection of overload. Teams stretched across compliance, retailer deadlines, endless documentation, and rising product complexity were desperate for relief. Their desire for full automation was really a desire for oxygen.
The challenges that persist
From fundraising conversations to day-to-day product work with customers, one challenge kept resurfacing: the fundamental mis-framing of AI. Too many teams treated AI as a task-elimination machine rather than a collaborative partner. When someone expects AI to remove 100% of their to-dos, disappointment is usually inevitable.
Another persistent challenge is the lack of experimentation muscle. AI adoption requires new habits—new workflows, new input strategies, new feedback cycles—and not everyone is comfortable forming them. Even teams excited about AI often struggled to carve out the time or the psychological space to test, iterate, and play. Yet a small upfront investment in defining a new way of working can result in dramatic long-term payoffs.
New best practices that will make an impact
Three best practices stand out as the CPG industry becomes more AI-fluent:
Decide when to use AI and when not to. Not every task benefits from automation. AI does its best work when provided with rich context, but generic tools require too much coaxing. Purpose-built tools remove that friction by embedding CPG-specific knowledge into the system, making outputs accurate without heavy prompt engineering.
Let AI handle information orchestration while humans handle nuance and decision making. AI can synthesize manufacturing constraints, regulatory guidelines, supply timelines, cost structures, and formulation logic, but it can’t feel the room temperature on a manufacturing floor or smell a shifted ingredient profile. Humans remain the arbiters of sensory and contextual nuance. AI becomes the score; the team becomes the conductor.
Grow AI fluency the way we once grew digital fluency. People who embed more data and context into AI systems quickly see exponential returns. Less searching. Less recalling. More clarity. More momentum. Over time, AI literacy will resemble the moment companies learned to use the internet as a strategic advantage rather than a novelty.
As these lessons pile up, a picture of the road ahead comes into view. The companies that will benefit most from AI in 2025 won’t be the ones chasing complete automation or treating AI as a shortcut—they’ll be the ones building the habits, norms, and fluency that allow technology to amplify human judgment rather than replace it.
Curiosity, structured experimentation, and a willingness to rethink long-standing workflows will matter more than any single tool or model. And for a CPG industry under constant pressure to move faster, respond smarter, and deliver with greater precision, this shift toward collaborative, context-rich AI isn’t just an operational improvement—it’s the foundation for a more resilient, more trust-empowered way of working.
