Remapping travel with agentic AI

Source: Alex Cosmas, Jules Seeley, Kelly Ungerman, Ryan Mann, Vik Krishnan, Alex Gersovitz, Isabelle Tamburro and Jane Kennedy; McKinsey & Company with Skift · 2025-09-16

Agentic AI is the buzziest new tech tool on the scene, and it offers thrilling capabilities. While gen AI mostly functions as an adviser by providing well-informed counsel, agentic AI can function more as a direct report by accomplishing tasks. It has the agency to make decisions and then autonomously act on them. It can identify problems, find fixes, and apply solutions all on its own. It’s smart and tireless, a self-starter and go-getter, requiring only limited human oversight. Perhaps most important: Agentic AI can serve as an interface that could help companies harness the full power of AI.

A new report, Remapping travel with agentic AI —a collaboration between McKinsey and Skift—examines the potential for agentic AI to unleash the full value of AI in travel. Based on analysis incorporating surveys of 1,002 travelers and 86 travel executives, the report traces the digital prologue that brought the industry to this moment, details agentic AI’s transformative capabilities for both travelers and travel companies, and provides a blueprint for travel and hospitality leaders who are eager to accelerate their organizations’ agentic AI initiatives.

AI has seen accelerating adoption in the travel industry. Only about 4 percent of companies in the Skift Travel 200 (a subset of the largest publicly traded travel companies in the world) mentioned some form of AI in their 2022 annual reports. By 2024, that had risen to 35 percent.

Meanwhile, AI-based travel start-ups are attracting a surge of venture capital interest. In 2023, according to Skift tracking, only about 10 percent of travel-industry-related venture capital funding went to travel start-ups that provided AI-enabled offerings. By the first half of 2025, that figure was 45 percent.

Some travel and hospitality companies seem excited about the opportunities that AI is presenting. In a survey of 86 mostly US-based travel executives conducted for this report, 26 percent of respondents say that introducing AI to their organizations has led to cost reductions in operations, 30 percent say that it’s aiding faster decision-making, 33 percent say that it’s improving customer personalization, 36 percent say that it’s enabling higher-quality outputs, and 59 percent say that it’s increasing employee productivity. A majority of respondents indicate that adopting AI in their organizations has resulted, over the past three years, in more than 6 percent annual revenue growth and more than 6 percent annual cost savings.

Despite all this burgeoning enthusiasm and adoption, however, the travel and hospitality sectors still appear to lag behind others in terms of AI maturity. Travel companies’ AI-based efforts have largely centered on creating enterprise-wide copilots and chatbots, and such efforts have scaled quickly. But for the most part, these more horizontal initiatives have delivered diffuse, hard-to-measure gains. Vertical use cases that are function specific to the travel sector could be more transformative, but the vast majority of these more focused experiments have remained stuck in pilot mode.

Siloed data and incompatible systems make using AI more difficult. The travel industry (and especially hospitality) is highly fragmented, cobbled together in part from countless small to medium-size businesses spread across nearly every country. The lack of centralized data ownership across the travel ecosystem limits the network effects and feedback loops that typically accelerate AI performance. As a result, it can be exceptionally challenging for travel companies to train effective AI models or to deliver personalized, real-time, AI-powered experiences at scale.

Travel companies tend to favor investment in human interconnection instead of tech innovation. Some of the travel sector’s wariness regarding AI might be attributed to the industry’s general view that it specializes in service, not technology. New tech capabilities are often seen as enablers but not as core business components. As a result, tech talent and tech investment can lag behind.

Agentic AI can autonomously make decisions and take the initiative to accomplish goals, using multistep reasoning while undertaking complex actions.

To execute tasks, agentic AI can call on external tools, APIs, and systems.

Agentic AI can store and recall long-term, structured memories that track context, progress, and user preferences, allowing it to deeply personalize its responses and to handle requests spread across multiple sessions.

While gen AI has mostly played a reactive, advisory role—answering research questions and offering helpful suggestions when specifically prompted to do so—agentic AI takes a far more proactive posture. An AI agent can carry out a complicated task end to end and can even direct teams of other AI agents to work together on the project. Agentic can monitor a situation, understand on its own when intervention is necessary, and then develop a responsive plan and enact it with little human involvement. It can also remember who someone is and what they’ve needed in the past and then incorporate that understanding into the present.

As customers have developed greater familiarity with AI-based tools, their trust in those tools has increased. More than 90 percent of customers report some confidence in the accuracy of travel information that they receive through AI. It’s worth noting, however, that consumers tend to express more comfort with using currently available AI tools to brainstorm in open-ended ways (such as finding inspiration or destination ideas) than with using these tools in more high-stakes situations (such as understanding visa requirements and resolving customer service issues).

This wariness is understandable, especially given the pervasive reports of hallucinations occurring in gen AI output.