Tourism-as-a-Service Promises to Streamline Travel Payments

Just as banking-as-a-service (BaaS) and software-as-a-service (SaaS) have reshaped their respective industries, a new “as a service” model is emerging in the travel and tourism sector. 

This tourism-as-a-service concept aims to redefine connected travel, harnessing the potential of advanced technologies such as artificial intelligence (AI) and blockchain to streamline every facet of the journey — from trip bookings and payments to accommodations and transportation.

By consolidating services typically spread across various tools and platforms, such as ticketing for public transport and tourist attractions, route planning, and access to relevant information, this concept streamlines travel experiences, which is highly appealing to today’s consumer seeking convenience and hassle-free experiences.

One of the companies embracing this trend is Addentax, which earlier this month, unveiled a tourism-as-a-service platform with AI and blockchain tools. 

The solution, launched in collaboration with Shenzhen Tamir Cultural Tourism Development, a blockchain service provider, aims to streamline local and international pan-entertainment and tourism services for Chinese travelers. 

“We are more than happy to witness the utilization of our AI and blockchain tools in the tourism-as-a-service pan-entertainment platform,” Hong Zhida, chairman and CEO of Addentax, said in a Feb. 6 press release. “We anticipate more AI technology research and developments translating into real-life applications and utilization.”

This news is occurring within the broader context of increased adoption of advanced technologies as part of efforts to accelerate the travel sector’s digital transformation. 

For example, European hospitality provider Accor recently introduced an AI-powered travel assistant leveraging Amazon Web Services (AWS) machine learning and AI capabilities and incorporating an intuitive conversational interface. 

Essentially, the assistant learns guest preferences to cater to the needs of travelers, including those who blend work and leisure trips, commonly referred to as “multimodal” travelers.

“Accor’s new Travel Assistant will empower guests to find the best experiences according to the style of travel they prefer, transforming the entire booking journey from inspiration to after their stay,” AWS said in a press release at the time, adding that the “the technology will streamline the booking process down to a matter of minutes.” 

AI Turns Apps Into Agents

These initiatives align with insights from PYMNTS Intelligence research that shows a growing interest in AI-driven experiences, including for travel. Notably, nearly 63% of consumers express enthusiasm for AI-enabled travel experiences, further highlighting the demand for innovative tech solutions in the sector.

Further reinforcing this trend, separate PYMNTS Intelligence-Ingo Payments research highlights a 16% surge in consumers seeking online travel information and purchasing airfare digitally over the past year. 

In response to this trend, businesses are increasingly adopting advanced digital travel-planning tools to meet consumers’ needs. For instance, Tripadvisor has embraced OpenAI’s generative AI technology to create customized travel itineraries, and travel marketplace Mondee has announced its integration with a mobile-centric generative AI platform.

This trend has led to investments in AI-driven travel initiatives, such as Airbnb’s recent acquisition of AI startup GamePlanner.AI for $200 million in November last year.

Speaking with investors on the company’s third-quarter earnings on call that same month, Airbnb CEO Brian Chesky expressed optimism about the potential of GenAI to improve the travel experience and transform the app into the “ultimate travel agent” for users.

This includes addressing common challenges in travel, such as language barriers between hosts and guests, differences in policies across borders and the lack of traditional front desk support.

By integrating AI, Chesky said “an agent can supervise a model that can, in seconds, come up with a better resolution and provide front-desk-level support in nearly every community in the world.”

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