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How AI is Revolutionizing the Travel Industry: From AI-Curious to AI-Native

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Saturday, July 12, 2025

The travel industry is experiencing a technological change as artificial intelligence (AI) reshapes how businesses function, connect with customers, and drive progress. AI is redefining the tourism landscape, offering personalized travel suggestions and improving booking systems. However, many travel companies are still figuring out how to fully adopt AI in their operations for long-term growth.

At the 2025 Skift Data + AI Summit in New York, experts Vivek Bhogaraju and Mayank Gandhi discussed the challenges and opportunities that come with adopting AI in the travel sector. They highlighted how travel companies can shift from being AI-curious to AI-native, transforming the tourism experience for everyone involved.

The Shift Towards AI in Travel
The tourism sector is fast-paced, influenced by changes in consumer behavior, global travel disruptions, and evolving digital technologies. As the world becomes more connected, travelers expect more personalized, efficient, and intuitive experiences. For travel companies to remain competitive, embracing AI is now essential.

AI has the potential to change the game in various areas. It can improve operational efficiency and enhance customer service, opening new paths for growth. However, implementing AI fully demands dedication, not only in terms of spending but also in changing company culture and infrastructure.

Building an AI Culture: Starting from the Ground Up
According to Bhogaraju and Gandhi, the first step to becoming AI-native is fostering a culture of experimentation within the organization. Travel companies should promote a mindset that welcomes risk-taking and innovation. Instead of fixating on immediate returns, companies ought to focus on learning and testing to establish a strong base for integrating AI.

Starting small is key—initiate AI-driven projects that tackle specific challenges or take advantage of opportunities in the organization. For instance, chatbots and AI-powered customer support can enhance service by providing quick assistance, while data analytics can help identify traveler behavior, enabling businesses to anticipate customer needs.

These AI-driven solutions are not one-size-fits-all. It’s essential to understand that implementing AI takes time, careful thought, and a strategic approach. Bhogaraju underscores the importance of evaluating the existing technology landscape, pinpointing shortcomings, and laying out a plan for AI adoption. Travel companies must recognize the foundations of AI and partner with long-term technology providers to achieve successful integration.

AI’s Role in Tourism Innovation
AI can revolutionize tourism by personalizing each traveler’s journey. AI solutions can optimize everything from flight bookings and hotel reservations to customized travel itineraries. By analyzing large datasets, AI can anticipate traveler preferences and offer tailored suggestions for destinations, activities, and services, improving the overall travel experience.

For example, personalized AI apps can track what a traveler likes and recommend attractions or dining options that match their tastes. Additionally, AI can enhance the booking experience by providing real-time updates on flight availability, pricing, and potential delays, helping customers make well-informed decisions.

Moreover, AI can streamline travel operations and boost industry efficiency. Automated systems can handle customer queries, manage payments, and provide real-time updates on services like check-ins, room availability, and baggage tracking. As AI use increases, these efficiencies will lead to better customer experiences and cost savings for companies.

Investment in AI Ecosystem and Long-Term Transformation
One critical lesson from Bhogaraju and Gandhi is that adopting AI is not a rapid solution. Companies must invest in a solid AI ecosystem, which includes not just the right technology but also the people and framework to support it. Implementing AI will require significant investment in upgrading technology and hiring skilled personnel to drive AI innovation.

AI solutions often need refining and revising. Travel companies must be patient and willing to try different approaches until they find the right combination that delivers lasting results. The benefits of this transformation are clear. Companies that invest in AI now will position themselves to lead the market in the coming years with more efficient operations and stronger customer relationships.

As companies develop their AI ecosystem, it’s vital to create diverse teams to ensure that the AI strategy matches business goals. This means not only involving technical specialists but also coordinating marketing, operations, and customer service teams to integrate AI effectively.

Challenges of AI Integration
Despite its advantages, adopting AI in the travel industry comes with challenges. The complexity of AI technology, the need for large amounts of data, and the pressure to show concrete returns can make the transition intimidating for many companies. There is also the issue of data privacy, as customers seek greater transparency and control over their personal information.

Resistance to change is another hurdle. Many employees may feel threatened by the increasing presence of AI at work, fearing job loss or diminished roles. This is why Bhogaraju and Gandhi stress the importance of a collaborative environment where AI is viewed as a tool that supports human roles rather than replaces them.

Looking Toward the Future: AI-Native Travel Companies
In the future, the companies that embrace AI will shape the travel industry. The focus of AI adoption should be on long-term transformation rather than immediate returns. As AI continues to advance, it will allow travel companies to offer increasingly personalized experiences, streamline operations, and achieve efficiencies that were once considered impossible.

To truly embed AI in tourism, travel companies must see it as a long-term investment rather than a quick fix. AI will change every aspect of the travel experience, from how companies connect with customers to how travelers enjoy various destinations. It’s about creating a smarter, more efficient, and personalized travel system that benefits both businesses and customers.

Conclusion: The Path to AI-Native Tourism
The journey from being AI-curious to AI-native requires a commitment to innovation, teamwork, and investment. As the travel industry evolves, AI will play a vital role in shaping its future. Companies that adopt this technology will discover new opportunities, enhancing the travel experience for consumers while promoting growth and efficiency for businesses.

In the words of Bhogaraju and Gandhi, “AI is not just a tool—it’s the future of the industry.” The travel companies that successfully transition from AI-curious to AI-native will pave the way for the next era in tourism, one that is smarter, more connected, and focused on the customer.

References:

Skift, Vivek Bhogaraju, Mayank Gandhi, New York Tourism Office, U.S. Travel Association



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AI in Travel

India’s Travel Revolution: How Map My Tour is Transforming Tourism with AI-Powered Personalization in New Delhi and Beyond – Travel And Tour World

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India’s Travel Revolution: How Map My Tour is Transforming Tourism with AI-Powered Personalization in New Delhi and Beyond  Travel And Tour World



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OpenAI Rolls Out ChatGPT Agent Combining Deep Research and Operator 

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OpenAI has launched the ChatGPT agent, a new feature that allows ChatGPT to act independently using its own virtual computer. The agent can navigate websites, run code, analyse data, and complete tasks such as planning meetings, building slideshows, and updating spreadsheets. 

The feature is now rolling out to Pro, Plus, and Team users, with access for Enterprise and Education users expected in the coming weeks.

The agent integrates previously separate features like Operator and Deep Research, combining their capabilities into a single system. Operator allowed web interaction through clicks and inputs, while deep research focused on synthesis and summarisation. 

The new system allows fluid transition between reasoning and action in a single conversation.

“You can use it to effortlessly plan and book travel itineraries, design and book entire dinner parties, or find specialists and schedule appointments,” OpenAI said in a statement. “ChatGPT requests permission before taking actions of consequence, and you can easily interrupt, take over the browser, or stop tasks at any point.”

Users can activate agent mode via the tools dropdown in ChatGPT’s composer window. The agent uses a suite of tools, including a visual browser, a text-based browser, terminal access, and API integration. It can also work with connectors like Gmail and GitHub, provided users log in via a secure takeover mode.

All tasks are carried out on a virtual machine that preserves state across tool switches. This allows ChatGPT to browse the web, download files, run commands, and review outputs, all within a single session. Users can interrupt or redirect tasks at any time without losing progress.

ChatGPT agent is currently limited to 400 messages per month for Pro users and 40 for Plus and Team users. Additional usage is available through credit-based options. Support for the European Economic Area and Switzerland is in progress.

The standalone Operator research preview will be phased out in the coming weeks. Users who prefer longer-form, slower responses can still access deep research mode via the dropdown menu.

While slideshow generation is available, OpenAI noted that formatting may be inconsistent, and export issues remain. Improvements to this capability are under development.

The system showed strong performance across benchmarks. On Humanity’s Last Exam, it scored a new state-of-the-art pass@1 rate of 41.6%, increasing to 44.4% when using parallel attempts. On DSBench, which tests data science workflows, it reached 89.9% on analysis tasks and 85.5% on modelling, significantly higher than human baselines.

In investment banking modelling tasks, the agent achieved a 71.3% mean accuracy, outperforming OpenAI’s o3 model and the earlier deep research tool. It also scored 68.9% on BrowseComp and 65.4% on WebArena, both benchmarks measuring real-world web navigation and task completion.

However, OpenAI acknowledged new risks with this capability. “This is the first time users can ask ChatGPT to take actions on the live web,” the company said. “We’ve placed a particular emphasis on safeguarding ChatGPT agent against adversarial manipulation through prompt injection.”

To counter these risks, ChatGPT requires explicit confirmation before high-impact actions like purchases, restricts actions such as bank transfers, and offers settings to delete browsing data and log out of sessions. Sensitive inputs entered during takeover sessions are not collected or stored.

The new system is classified under OpenAI’s “High Biological and Chemical” capability tier, triggering additional safeguards. The company has worked with external biosecurity experts and introduced monitoring tools, dual-use refusal training, and threat modelling to prevent misuse.



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Lovable Becomes AI Unicorn with $200 Million Series A Led by Accel in Less than 8 Months

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Stockholm-based AI startup Lovable has raised $200 million in a Series A funding round led by Accel, pushing its valuation to $1.8 billion. The announcement comes just eight months after the company’s launch.

Lovable allows users to build websites and apps using natural language prompts, similar to platforms like Cursor. The company claims over 2.3 million active users, with more than 180,000 of them now paying subscribers. 

CEO Anton Osika said the company has reached $75 million in annual recurring revenue within seven months.

“Today, there are 47M developers worldwide. Lovable is going to produce 1B potential builders,” he said in a post on X.

The latest round saw participation from existing backers, including 20VC, byFounders, Creandum, Hummingbird, and Visionaries Club. In February, Creandum led a $15 million pre-Series A investment when Lovable had 30,000 paying customers and $17 million in ARR, having spent only $2 million.

The company currently operates with a team of 45 full-time employees. The Series A round also attracted a long list of angel investors, including Klarna CEO Sebastian Siemiatkowski, Remote CEO Job van der Voort, Slack co-founder Stewart Butterfield, and HubSpot co-founder Dharmesh Shah.

Most of Lovable’s users are non-technical individuals building prototypes that are later developed further with engineering support. According to a press release, more than 10 million projects have been created on the platform to date.

Osika said the company is not targeting existing developers but a new category of users entirely. “99% of the world’s best ideas are trapped in the heads of people who can’t code. They have problems. They know the solutions. They just can’t build them.”

Lovable is also being used by enterprises such as Klarna and HubSpot, and its leadership sees the platform evolving into a tool for building full-scale production applications. 

“Every day, brilliant founders and operators with game-changing ideas hit the same wall: they don’t have a developer to realise their vision quickly and easily,” Osika said in a statement.

Osika also said on X that he has become an angel investor in a software startup built using Lovable. 

In another recent example, Osika noted that a Brazilian edtech company built an app using Lovable that generated $3 million in 48 hours.

Lovable’s growth trajectory suggests increased adoption among both individual users and enterprise customers, positioning it as a significant player in the growing AI-powered software creation market.



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