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How to safely harness generative AI for productivity gains in food and beverage businesses

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The potential opportunity that generative AI offers food and beverage businesses is unparalleled. Increasingly, the breakthrough technology is offering businesses the opportunity to streamline operations by transforming efficiency and productivity. Already, generative AI is helping to drastically reduce the time spent on internal tasks like research and analysis, among many other benefits.

Though the opportunity is great, leaders and decision-makers are justified to approach the implementation of generative AI with caution. When selecting a generative AI-powered solution to implement, it’s critical that product development is done responsibly and methodically. When done so, it can save food and beverage businesses significant time, enhancing both efficiency and productivity. By freeing up time, it allows us to do more creative work. With many tasks automated by generative AI, human capability can be augmented – meaning that more time can be put towards crafting the future.

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Implementing AI without a clear purpose or business case can lead to inefficient resource allocation and limited returns on investment. First and foremost, F&B organizations should focus on identifying tangible backend pain points within their businesses that generative AI tools can effectively address. The goal is to pinpoint where and how generative AI applications can be used most optimally to streamline efficiency. 

Employers should consider tasks in which employees spend the most time that they no longer need to, and how can generative AI eliminate time spent on tedious tasks, elevating employee workload to focus more on higher level thinking and creativity. By seeking answers to these questions, leaders will truly understand where it can be useful to elevate productivity.

When incorporating generative AI technologies throughout your F&B organization, a clear purpose is crucial to successful enforcement. Without a firm goal, a food and beverage business risks creating confusion and inefficiently allocating resources. 

The best way to come up with a goal is for decision-makers to educate themselves so they have an intimate understanding of how generative AI functions. What are its benefits and what are its pitfalls? Combining these two factors – workflow goals and understanding – will enable leaders to clearly outline how the technology should be applied within the organization (when it can and should be used, versus when it shouldn’t be used)  to ensure responsible and efficient use.

Make sure the AI is trustworthy

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ChatGPT is known both for its innovation but also for its ability to derive false insights by pulling facts from unverified sources, which will simply not work for food and beverage businesses relying on data to advise on strategic business decisions. It’s simply too risky to rely on potentially faulty data. That’s why using trustworthy and traceable data is a pivotal step toward successful implementation.

When assessing a product’s ability to pull verifiable data using generative AI, transparency is key. Users should be provided not only with answers but also with the sources from which those answers were derived.

Last, but not least, make it user-friendly

Once a goal is established and the technology is deeply understood, it becomes vital that it’s easy to use. Despite working with powerfully automated technology, a successful generative AI product must be user-friendly at its core to ensure that your employees use it – and that your investment in it is worth it.

Any generative AI-powered product you use should be human-centric, and offer seamless integration with existing platforms and workflows. It should naturally aid in human thinking, not run contradictory to it. Striving for a human-centric experience fosters symbiosis between humans and AI, leading to substantial productivity gains. 

Much like how the iPhone revolutionized how we interacted with technology despite leveraging components that we already were familiar with (a touch display, the internet, the ability to text, etc.), generative AI’s potential hinges on not the technology itself, but an innovative interface that will streamline how humans interface with it. The true catalyst for transformation relies on if humans enjoy using it or not. If a process or function is too complex, or does not feel natural to use, mass implementation is likely to be unsuccessful.

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It’s no secret that generative AI’s impact will extend beyond today, and it’s important to keep this in mind when selecting a solution for your business. Generative AI is already altering the pace at which we can complete organizational tasks, and it will have a long term impact on business operations in years to come. 

But before that happens, the journey towards successful and responsible generative AI integration in enterprise demands meticulous planning, a clear sense of purpose, responsible education, and verifiable outputs. As the landscape of enterprise evolves, understanding its strengths – and utilizing them effectively – will unlock unprecedented efficiency and productivity gains.

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