Since I have a passion for travelling as well as the hospitality industry (having a bachelor in hospitality management), and I believe in the power of Artificial Intelligence (AI), for this week's article I decided to look into what happens when you combine the two. As it seems, Artificial Intelligence is set to be a game-changer for the travel industry. It is helping consumers and companies simplify making travel arrangements and streamlining business processes. AI is also modernising travel by taking it from a complicated, drawn-out experience to one that is more enhanced and customer-focused by improving the overall efficiency for hotels, airlines, and other travel providers. AI's impact on the travel industry is powerful and massive and it has the potential to transform business completely.
Despite common misconceptions, the cruise industry is at the forefront of the travel tech revolution. Here's our pick of the most ground-breaking cruise ship technology developments that are revolutionising the industry. Much has been made of efforts to reduce emissions and improve environmental performance in the cruise sector, but few have gone as far as Hurtigruten. The line recently unveiled Roald Amundsen, the first cruise ship to sail on battery power. Estimates say the ship's hybrid propulsion will reduce CO2 emissions by about 20 per cent.
AI in tourism enables the all-important element of personalization to make customer journeys shorter, and more memorable. We share four examples of Artificial Intelligence (AI) and Machine Learning (ML) in the travel industry, with key takeaways for marketers to get started on implementation. The evolution of digital technologies has transformed customer expectations from every service provider. Whether it's in banking, healthcare, or even travel & tourism, your customers now want a Netflix-like customer experience (CX), no matter the touchpoint. This has also impacted the travel industry, which was quick to adapt and build tools for precisely that level of personalization.
Avis projects to automate the most dreaded part of vehicle rentals: the inspection for car damages. Rather than having an employee spend time to ensure that the procedure goes smoothly, the car rental company intends to utilize artificial intelligence to replace the process. The pilot program would automatically detect maintenance issues and damage, removing the need for idle time. Collaborating with a startup, Ravin, Avis would integrate existing infrastructure to detect damages. CCTV cameras would complement one another to conduct a full scan, using machine learning to analyze the state of the vehicle.
The hype around Chatbots refuses to die down with talk of the town being the unlimited possibilities the Chatbot offers to the end users. Chatbots leverages Artificial Intelligence technology in aiding the firms in solving the myriad issues like prompt answering of visitor queries, engaging users, 24/7 availability among others. Chatbots are rising in its implementation but it's not a fad in passing, it's a crucial innovation. Chatbots simplify Travel plans for the travelers while streamlining business for the travel industry firms. Chatbots is a win-win situation for both- the end consumers who seek swift booking and the firms who would like to engage more visitors and drive revenues.
Trips to other parts of Tokyo's technology centers helped round out the impression that Japan was becoming a major player--albeit quieter than its neighbors--within the global startup ecosystem. Visiting ZMP Inc. demonstrated the future of mobility, as this company is focused on the goal of being the "robot of everything" driving a more convenient lifestyle for everyone. This means level-four completely autonomous self-driving vehicles (a 2020 goal of Prime Minister Abe and Information Technology Minister Hirai), mass deployment of logistics robots (automated delivery) and focus on the needs of the country's aging society. Spending time with Shift Technology, I saw the well-demonstrated results of its partnership with the Tokyo Metropolitan Government to innovate within Japan's second largest insurance market by leveraging technology to make insurance claims more efficient. Peter Haslebacher of Shift said, "If you succeed in Japan, you can make it in any market", referring to the complexity and homogeneity found within the Japanese ecosystem--a great challenge for any ambitious startup.
Natural Language Processing (NLP) is a subfield of machine learning concerned with processing and analyzing natural language data, usually in the form of text or audio. Some common challenges within NLP include speech recognition, text generation, and sentiment analysis, while some high-profile products deploying NLP models include Apple's Siri, Amazon's Alexa, and many of the chatbots one might interact with online. To get started with NLP and introduce some of the core concepts in the field, we're going to build a model that tries to predict the sentiment (positive, neutral, or negative) of tweets relating to US Airlines, using the popular Twitter US Airline Sentiment dataset. Code snippets will be included in this post, but for fully reproducible notebooks and scripts, view all of the notebooks and scripts associated with this project on its Comet project page. Let's start by importing some libraries.
Royal Caribbean International will deliver tens of thousands of meals and other supplies to Bahamas residents affected by Hurricane Dorian, CEO Richard Fain told Fox News Wednesday. The Miami-based vacation giant is used to dealing with tropical systems, but the devastation left by Dorian in the northern Bahamas is breathtaking, Fain told Neil Cavuto on "Your World." "It's hard to appreciate -- those of us in Miami are used to seeing hurricanes. We get them for a few hours," he said. "But on Grand Bahama, that storm just sat over them without moving for 38 hours."
"When you start looking at connecting points, those intersections across the different siloed data collections and siloed departments, you might just be amazed at what you could discover." Most businesses have siloed departments that are pursuing digital transformation independently, creating "islands of innovation" throughout the enterprise. This episode discusses how to unify these efforts into a cohesive strategy to develop an intelligent enterprise. What could your business do if you had total control over your data? In NASA's case, a data transformation is what made the Hubble telescope and countless other amazing discoveries possible. Our guest this episode, Kirk Borne, was there when it happened. He began his career as an astrophysicist, combining datasets from multiple fields in unprecedented ways. Now Kirk's work is more down to earth. In this episode, he shares how businesses can "democratize data" across the enterprise. And he explains how data transparency plus intelligent analytics can lead to new efficiencies, better customer experiences, even entire new business models. "The key is this concept of the culture of experimentation, that you allow people to experiment with data." Kirk Borne is a Principal Data Scientist and Executive Advisor at Booz Allen Hamilton.
This article is part of CMO.com's Industry Spotlight 2019 collection. Digital technology is advancing at breakneck speed--and it's putting pressure on businesses to produce new apps, tools, and technologies as they seek to compete in the digital economy. Not surprisingly, emerging technologies are at the center of this revolution. Artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) are unleashing enormous changes. Ditto for augmented reality (AR) and virtual reality (VR), chatbots, image and voice recognition, advanced GPS, and analytics.