How PepsiCo Is Using AI and ML to Prosper in the Market?

One business who understood that deploying AI and Ml is a business need, no longer competitive advantage is PepsiCo. The food and beverage company behind brands, for example, Pepsi, Gatorade, Tropicana, Lipton, Frito-Lay, and Quaker sells products in over 200 nations and earned $64.7 billion in annual revenue a year ago. From robots to AI, PepsiCo uses AI and ML throughout the company from numerous points of view.

Snackbot, the Snack Delivery Robot

There’s a six-wheeled mobile vending machine robot tooling around the University of the Pacific chockful of PepsiCo snacks and beverages from Hello Goodness—a healthier line-up that includes SunChips, Baked Lay’s and bubbly sparkling water. Named Snackbot, these self-driving robots are a partnership between Robby Technologies and PepsiCo. Students can order their snacks from the Snackbot application, and after that, the robot will deliver it to more than 50 spots over the campus without charging a delivery fee. The bots have a range of 20 miles on a single battery charge, and they can even navigate at night, in rain or up curbs because of onboard headlights and all-wheel drive capabilities.

Snackbot represents the solution to the needs of undergrads and their inclinations identified through PepsiCo’s research. There are three to five Snackbots on campus to keep up with the demands.

Machine Learning and Manufacturing Goes Hand in Hand

The Frito-Lay (a subsidiary of PepsiCo) manufacturing plant is profiting by ML. One project uses lasers to hit chips and afterward tune in to the sounds falling off the chip to determine texture. Algorithms process the sound and determine the chip texture to automate the quality check for Frito-Lay’s chip processing systems.

From this start, Shameer Mirza, senior R&D engineer at PepsiCo, understood a few additional applications of AI could impact process control within the facility. Next, Mirza built up an ML model that could be used with a vision system to have the option to predict the weight of potatoes being processed. This prompted considerable savings for the company since it no longer needed to spend $300,000 per line for weighing elements. Mirza’s systems used just a camera and the ML model and are basically data points gathered with no extra cost.

Another project still being developed would evaluate the “percent peel” of a potato after it had gone through the peeling process. By understanding this data, it can help the Frito-Lay team to optimize the potato peeling system. This venture alone is assessed to save the organization more than $1 million per year just in the United States.

PepsiCo is launching a global training course on advanced AI and computer vision for its internal R&D associates this year to expand its team’s capacities to use these advancements to find insights that will drive efficiencies in its manufacturing facilities.

Robot Vera that Streamlines the Hiring Process

PepsiCo used Robot Vera to call and interview people for open positions in sales, as drivers and to fill factory vacancies in Russia when HR generalists needed to fill 250 jobs in two months. Vera was developed by Russian startup Stafory and is capable of interviewing 1,500 competitors in nine hours, a role that would take people nine weeks.

Advanced speech recognition tools and frameworks from Amazon, Google, Microsoft and Russian tech firm Yandex permit Vera to make calls and screen candidates for open positions, for example, fork-lift administrators, assembly line laborers, and deals staff. Its product can go through CVs to determine whether a potential candidate has the correct understanding for the position, can respond to yes and no answers, ask follow-up inquiries and send up follow-up correspondence. It can likewise send transcripts of a call to a human HR generalist for further survey. Up until this point, the reception from the majority of candidates when dealing with a robot has been positive. There was more hesitation from human HR professionals. It turns out probably the greatest obstacle is “reprogramming people” to feel good with the technology.



  1. Chatbots are like the next evolution in marketing automation that automates personalized interaction between a chatbot and a human in the most natural way possible. Definitely, the wittier and accurate responses are, the better the services it will provide to a customer and lead to better engagement. As AI and NLP become more powerful than ever, the better bots will be at personalizing responses, understanding complex requests, and deliver superior services.


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