{"id":24036,"date":"2021-04-09T08:36:53","date_gmt":"2021-04-09T06:36:53","guid":{"rendered":"https:\/\/www.specpage.com\/?p=24036"},"modified":"2021-04-09T08:36:53","modified_gmt":"2021-04-09T06:36:53","slug":"ai-chefs","status":"publish","type":"post","link":"https:\/\/www.specpage.com\/ai-chefs\/","title":{"rendered":"AI Chefs"},"content":{"rendered":"
The most brilliant chefs can suggest flavor pairings that are all at once unexpected and yet effortless. Now, AI technology can do the same. New startups are emerging to help FMCG companies and large restaurant chains meet consumer demands.<\/p>\n
It\u2019s a familiar problem: how can you launch new food products and guarantee that consumers will love them, buy them, and tell their friends about them? Market research can only take you so far. First, food companies need to innovate the right new products to test.<\/p>\n
The question becomes: why send a recipe further into production when (based on real human input and millions of data points) your AI is suggesting a better flavor pairing instead?<\/p>\n
Product teams must keep pace with consumer demands. And AI is here to help.<\/p>\n
We\u2019re not at the point where AI technology is writing complete recipes and product specifications that are guaranteed to have mass appeal.<\/p>\n
Rather, product innovators are simply not alone in their efforts anymore. Coming up with new products is no longer a purely human activity that resides in the power of the human creative brain. So, while AI platforms aren\u2019t spitting out fully blown recipes, they are offering the following:<\/p>\n You probably want to know how this works. So did I. That\u2019s why I did some digging…<\/p>\n How does AI predict consumer preferences? How does it generate advice that is helpful instead of random? The best food AI platforms come loaded with millions of food and food preference related data points, and food companies can also bring their own data to the table.<\/p>\n When you understand where the data is coming from, it\u2019s easy to see how harnessing this data with AI can lead to some big results. Food companies note that their AI is coming up with flavor pairings<\/a> that human product innovators wouldn\u2019t have thought of. More importantly, these AI suggestions are performing better in market research and in the actual market.<\/p>\n McCormick is one such brand that’s relying increasingly on AI to keep their product offerings fresh. They\u2019ve included many AI-driven seasonings in their subscription box<\/a> and even launched their XO sauce<\/a> off the suggestion of their AI.<\/p>\n These are the 3 main ways that AI helps food brands today:<\/p>\n Truthfully, the idea of not having a digital database of flavors, ingredients, and how they combine seems a little crazy when you think about it. Of course food companies should possess this.<\/p>\n At some point not too far in the future, food innovators will have a hard time imagining how they could create a new product recipe without such a database.<\/p>\n
\nHumans are now working with AI products from IBM<\/a> and Spoonshot<\/a> and Gastrograph<\/a>.<\/p>\n\n
Understanding how this technology advancement follows real consumer preferences<\/h2>\n
\nThe best AI food platforms on the market do this by capturing and storing data on real human flavor preferences. These platforms build up their own databases and also pay to access data from other vendors.
\nThis data can be in the form of:<\/p>\n\n
3 main ways that AI helps companies cater to consumer preferences<\/h2>\n
Digital flavor mapping and pairing<\/h3>\n