星巴克最终可以让你看到一个个性化的数字菜单当你拉到驱动器。 在星巴克首席执行官Brian Niccol 称星期四的一次收入呼吁中，公司将探索“在他们到达时承认参与客户的经验，呈现个性化的数字菜单，并让支付更加无费，”如更完美联盟早些时候所发现的那样。
星巴克想用人工智能在驱动器上展示“个性化数字菜单”。
咖啡连锁店的目的是在客户到来时
这听起来类似于Taco Bell正在试验的技术，它可以改变数字菜单板上“逐车”的布局、内容和视觉。 麦当劳最近还展示了一个AI的功能，它正在少数驱动推力上进行试飞，允许它的“ArchIQ”聊天机识别重复的客户
从2027年开始，星巴克公司还将开始在驱动器-thru测试背景AI模型，帮助巴istas“更准确和高效地输入订单”，根据尼科尔的说法。 公司还计划将AI整合到星巴克应用的搜索和发现功能中，并可能允许未来"对话和代理"订购。
星巴克已经开始允许客户通过ChatGPT发布订单，同时也推出AI动力的绿点Asistance，员工可以用来询问食谱和服务标准等事项。
但Nicol 称仍「很早」，并补充说：「我们会测试、学习和衡量什么是可行的。
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Starbucks could eventually show you a personalized digital menu when you pull up to the drive-thru. During an earnings call on Thursday, Starbucks CEO Brian Niccol said the company is going to explore “experiences that recognize participating customers as they arrive, present personalized digital menus, and make payment more effortless,” as spotted earlier by More Perfect Union.
Starbucks wants to use AI to show you a ‘personalized digital menu’ at the drive-thru
The coffee chain aims to ‘recognize’ customers as they arrive.
It sounds similar to the technology that Taco Bell is experimenting with, which could change the layout, content, and visuals on a digital menu board “on a car-by-car basis.” McDonald’s also recently showed off an AI-powered feature it’s piloting at a handful of drive-thrus, allowing its “ArchIQ” chatbot to identify repeat customers and let them order their “usual.”
Starting in 2027, Starbucks will also begin testing background AI models at the drive-thru to help baristas “input orders more accurately and efficiently,” according to Niccol. The company also plans to integrate AI into the Starbucks app’s search and discovery features, and may allow “conversational and agentic” ordering in the future.
Starbucks has already started allowing customers to place orders through ChatGPT, and also rolled out an AI-powered Green Dot Assist that employees can use to ask questions about things like recipes and service standards.
It’s still not clear how soon we can expect to see personalized digital menu boards at Starbucks, but Niccol says it’s still “early,” adding that “we’ll test, learn, and scale what works.”
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