The next time you dine at a restaurant, you might end up choosing a dish recommended completely by a software – the cuisine, colour and flavour -without any intervention from a human attendant. And you would not realise it. The first set of these digital restaurants went live with at-Digital Menu four months ago. This counts as a significant leap for Artificial Intelligence in hospitality industry.
For customers, buying online might seem simple- click, pay and collect. But it’s a different ballgame for hotel industry. Behind the scenes, from the kitchen to the guests table, artificial intelligence plays a huge role in automating processes.
Online retailers are employing AI to solve complex problems and make online shopping a smoother experience. This could involve getting software to understand and process voice queries, recommend products based on a person’s buying history, or forecast demand whereas in hospitality industry buying history is not specific to an individual on a usual side an order is placed for plus one or more.
So what’s the big shift?
In terms of industry trends, people are going towards fast decision making driven buy targeted marketing campaigns using AI to process data and predict trends. The new AI-prompted dishes are presented as today’s special dish, so hotels can genuinely test how well these sell when set against regular menu items. Till now, hospitality industry could look at statistics for inputs. But when you need to scale, we are limited by the depth of customer profile available at hand.The next step for anyone before implementing AI is to digitalise the ordering process and get to know more about your customer not just his eating habits but also insight into their daily likes and dislikes. It acts as a gold mine, our AI algorithm gets better with every additional info we capture and sell ratio for proposed dishes goes high.
Digital sales which has a treasure trove of data collected over the last few years is ripe for disruption from AI. Companies are betting big on AI and pouring in funds to push the boundaries of what can be done with data.
We are applying AI to a number of problems such as medical condition diets, native origin diets, question answering about menu items, age & ethnic group choices, product recommendations, product search, forecasting product demand based on climate/festivities, etc.
An example of how AI is used in recommendations could be this: if you started your search on at-Digital Menu with, say, a cheese sandwich with veggies and your next search is for an espresso and muffin, the algorithm understands what is motivating you.
We start with personalisation based on search pattern clubbed with body type (Kapha, Pita & Vayu), it is key. If you have multiple cuisines with hundred of items then it is an issuer your customer get to the product that he wants? We step in here to give your customers precisely what they are looking for.
A related focus area for AI is recommending the right spices as this can vary across cuisines.
A number of AI-focused startups are also working on automating manual tasks in ecommerce. For example cataloging, If not done properly, searching for the right product becomes cumbersome and shoppers might log out.
Few AI companies also offers a host of other services such as sending personalised emails to their clients’ customers, automating warehouse operations and providing analysis and forecasting.
The other big use of AI is to provide business intelligence. AI deliver insights using computer vision, meaning visual intelligence, for example, a dark red shirt now dark red is subjective,You cannot translate dark red, so AI pulls information from the internet and show it visually.
Few are also trying to use AI to predict for customers the exact time of product delivery. However, its not that simple it depends on what time somebody placed an order, what was happening in the rest of the supply chain at that time. It is a complicated thing to solve but organisations are trying to make it simpler using AI.
The next big challenge for AT Ventures
One of our next focus is to offer a 24×7 virtual assistant that can talk in common language and recommend what to eat, when to eat, how much to eat (ha ha ha, myself being a foodie) and where to eat. But realtime mood predictions are difficult to solve. It is very early to even comment on the feasibility of such assistant, for now first step would be to offer support, where a user ask questions like where is my order, how much calories in this item and is it good for my medical condition etc, or instruct like add some more cheese to my burger etc.
Technology giants like Google and Amazon are pushing forward research on artificial intelligence. Already many organisations have shifted customer care on bot agents responding to customers. The next stage is where a customer can connect to bot agent as he connects to Alexa or Siri.
While speech is one crucial area in AI research, vision is another.Any opportunity to improve efficiency and cut cost is of supreme importance. There are a lot of diverse experiments going on, We will certainly see a lot of innovative tech in near future.