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How Food & Beverage Companies Are Using Generative AI

The tool's greatest potential and why the challenges of using generative AI shouldn't be underestimated.

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Thor Olof Philogène is the CEO and founder of Stravito, an AI-powered enterprise insights platform that allows employees at Fortune 2000 organizations to store, discover, share and integrate consumer insights in seconds. The company's clients include brands like McDonalds, Comcast, Electrolux and Danone.

In this exclusive interview with Food Manufacturing, Philogène discusses how food and beverage companies using generative AI tools today, the tool's greatest potential, and why the challenges of using generative AI shouldn't be underestimated

Food Manufacturing: How are food and beverage (F&B) organizations using generative AI tools right now?

Thor Olof Philogène is the CEO and founder of Stravito.Thor Olof Philogène is the CEO and founder of Stravito.StravitoThor Olof Philogène: Many, if not all, F&B companies are exploring generative AI, but we're seeing that many of them are taking a cautious approach. Rather than diving into full-scale production right from the start, they begin with small pilot projects involving generative AI. 

Another notable trend we're seeing is the formation of dedicated generative AI committees within many companies. These committees have a horizontal scope and work to coordinate generative AI initiatives across different parts of the organization. They do not only carefully evaluate the potential benefits and risks of generative AI, but also work to establish security and privacy standards for vendors.

With the rapid evolution in this field, where development is happening at lightning speed, we also see a growing tendency among companies to select long-term partners rather than just vendors.

FM: Where is the greatest potential for the tools?

Philogène: The greatest potential of incorporating generative AI into the F&B industry centers around enhanced efficiency, productivity and creativity for users by removing a large part of the manual work and making it easier for users of the new tools to discover new information through a simplified, conversational interface made possible by generative AI technologies. 

Overall, while the hype is huge and the possibilities seem endless, it's important to remember that generative AI is still in its early stages of development, which is why thoughtful research and education are important. F&B companies need to identify real-life pain points that generative AI tools can effectively address, as implementing generative AI simply for the sake of using the technology without a clear purpose may lead to inefficient resource allocation and limited return on investment. 

FM: What were your thoughts on the Beck's "beer that made itself" experiment? New industry standard or gimmick? 

Philogène: I believe it reflects a perfect snapshot of where we are in terms of experimenting with generative AI, understanding its capabilities and potential applications, albeit in a specific context of the brewing industry. 

Similarly, in other domains such as art, music, literature, and design, generative AI is being experimented with to generate new creative outputs. We're in an exciting phase, crucial for building a deeper understanding of the technology. New industry standard or gimmick, time will tell.

FM: How can companies use generative AI in a more meaningful manner?

Philogène: When we evaluate the success of generative AI implementations, we look at it from two primary angles: efficiency gains and value creation. Efficiency gains are quantified by the time saved in searching for and analyzing information, as generative AI significantly accelerates these processes. As an example, groundwork that would have required hours before can be done in minutes now. Additionally, enhanced discoverability of information helps companies avoid redundant efforts and conserve budgets by leveraging existing research rather than starting from scratch each time. 

However, the true significance of generative AI lies in its capacity to deliver benefits beyond mere time and cost savings. For instance, in the realm of research, the ability to ask the right questions is paramount. While researchers naturally hone this skill over time, generative AI can further refine it for business stakeholders. By helping to generate better questions and challenging biases and assumptions, generative AI has the potential to foster behavioral changes and encourage a more thoughtful approach. 

FM: Do you have any reservations or concerns regarding the use of generative AI? 

Philogène: Implementing generative AI solutions provides companies with incredible power and speed to parse large volumes of data, delivering a great productivity boost, and promoting exploration and inspiration through a seamless interface. 

However, the challenges of incorporating generative AI into systems and processes are multi-dimensional and should not be underestimated: Enterprises need to make sure they only work with trusted vendors for their AI solutions, and that the data that they use in AI-enabled systems is handled in a secure and compliant manner. 

Of course, there is also the risk of hallucinations from some generative AI tools, which is something that has received much media attention over the past year. For F&B companies who are reliant on market and consumer research to make business decisions, it's pivotal that any tool they implement only uses vetted data to generate AI-enabled answers – unlike open AI apps that pull from the public domain. Furthermore, I would stress that you, when it comes time to integrate, ensure that the generative AI tool is complemented by a human-run service layer. Implementing generative AI necessitates a human component to ensure its effectiveness. 

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