Jeff Cioletti, in the article in Beverage Industry magazine, published on January 2, 2024, “The Present and Future of AI in Beverage Delivery,” explores the transformative role of AI in beverage delivery: current developments and future horizons. Tom Moore, the CEO of ProvisionAi, helped Jeff to dig deeper.
2023 has left an indelible mark as the era when artificial intelligence (AI) seamlessly entered mainstream discourse. Far from the dystopian visions of robotic dominance, AI discussions pervaded various industries, from entertainment to consumer packaged goods.
AI-driven trucks are still in development, but many fleets already use AI without realizing it.
Tom Moore, founder of ProvisionAi, highlights AI’s impact beyond self-driving technology.
In the specific domain of AI in beverage delivery, ongoing research is centering on optimizing load management. ProvisionAi’s study for a beverage company demonstrated that strategic load planning can yield approximately 5% savings. Moore highlights small weight differences between similar cans. Leveraging these nuances boosts efficiency and cuts costs.
AI can also optimize picking when switching from side loaders to rear-load vehicles. Current tech gives basic instructions but fails to build stable pallets with different bottle and can sizes.
This challenge intensifies with the surge in Stock Keeping Units (SKUs), particularly within the beer industry, where distributors manage an extensive array of brands and flavors.
Moore underscores the imperative for AI solutions to facilitate seamless transitions in loading processes. Furthermore, AI holds promise in streamlining inbound deliveries by prioritizing unloading based on the urgency of specific SKUs.
Moore acknowledges the intricacy of this task, noting that AI could enhance decision-making processes, mainly when dealing with a plethora of SKUs on supplier trucks.
AI in beverage delivery is evolving fast. It improves safety and optimizes loads.
As picking and SKU challenges grow, AI boosts efficiency and adapts to supply chain demands.