Artificial intelligence is quickly becoming a practical business tool for travel agencies, moving beyond experimentation into everyday operations. From automating itinerary costing to generating market intelligence, experts say agencies that integrate AI into their workflows now will gain a clear operational edge in an increasingly competitive market.
By: Janice Alyosius
Artificial intelligence is steadily entering the operational backbone of the travel trade, transforming how agencies design itineraries, analyse markets and respond to clients. As response speed and efficiency become critical differentiators, agencies that adopt AI-driven tools early could gain a significant competitive advantage.
Industry experts say the shift is already underway. Rather than replacing travel professionals, AI is increasingly being used to automate time-consuming back-end processes—freeing teams to focus on strategy, customer experience and sales. For many agencies, the biggest question is no longer whether AI matters, but how quickly it can be integrated into daily workflows.
According to Matt Gibson, CEO, UpThink, the starting point is simpler than most agencies assume. Instead of chasing complex technology projects, he suggests focusing on everyday tasks that consume the most time. “Start with the work that already eats your week,” he says, emphasising that AI works best when applied to repetitive operational processes.
Automating the work behind itineraries
For most travel agencies and DMCs, a large portion of time is spent managing spreadsheets—whether it is building itineraries, comparing supplier rates, or managing group allocations. Gibson believes this is one of the quickest areas where AI can create immediate efficiency.
“If you’re building complex itinerary costings, group allocation sheets, or multi-supplier rate comparisons, Claude Cowork is a revelation,” he explains. “It doesn’t just crunch numbers—it builds, restructures and explains the logic behind the sheet as it goes. Hours of work, done before lunch.”
This capability can dramatically reduce the time teams spend compiling costing sheets or adjusting proposals for different clients. In a sector where response speed often determines whether a deal is won, automation at the backend could significantly improve competitiveness.
Faster market intelligence
Another area where Gibson sees strong potential is market research. Agencies constantly track competitors, tourism board announcements, and destination updates. Traditionally, compiling such information requires hours of manual research.
AI tools, however, can condense this process into minutes. “NotebookLM’s deep research feature lets you feed it sources—competitor sites, industry reports, tourism board publications—and get back a polished, cited analysis in minutes,” Gibson says. “The kind of report that used to cost a consultant’s day rate now costs a few prompts.”
For travel companies that operate across multiple destinations or markets, this capability can be particularly valuable. It allows teams to track trends, identify emerging opportunities, and respond quickly to changing traveller demand.
Understanding the ideal traveller
One of the more unexpected applications of AI lies in customer profiling. Gibson points to tools that allow travel companies to simulate conversations with their ideal customer profile.
“Tools like Gemini Gems and CustomGPTs let you build a detailed persona of your ideal customer—nationality, travel style, budget sensibility, cultural expectations,” he explains. “Then you have a conversation with them. Ask how they’d react to your proposal. Watch them push back. It’s startlingly realistic.”
For agencies selling to global clients, particularly across multiple cultures, such simulations can reveal blind spots in marketing messages or proposal design. Gibson notes that these insights often challenge assumptions companies didn’t realise they were making.
Where AI creates the biggest ROI
While chatbots often dominate conversations around AI in travel, Gibson believes they represent only a small fraction of the potential. “Think about what a B2B travel operation actually does all day—searching, repackaging, customising, localising, comparing,” he says. “That’s not a criticism. It’s just the nature of the business. And it also happens to be an almost perfect description of what AI does best.”
The real transformation, he argues, comes when AI connects directly with a company’s internal systems—inventory databases, supplier contracts, and booking histories. Once integrated, staff can retrieve and repurpose information dramatically faster.
“Your team can retrieve, reformat and repurpose information at a speed that simply wasn’t possible before. Not faster by 10%. Faster by an order of magnitude,” Gibson adds.
The biggest mistake companies make
Despite growing interest in AI, many organisations fail to unlock its full value. The problem, Gibson believes, is not technology—it is adoption. “The biggest mistake is leaving people to figure it out alone,” he says.
Many companies introduce a tool, conduct a short training session, and expect employees to experiment independently. The result is uneven adoption, with only a few enthusiastic staff members using the technology while others ignore it.
According to Gibson, the organisations that gain the most value from AI take a different approach. “The companies that pull ahead are the ones that build a culture around AI use—not a policy, a culture,” he explains. “People share prompts, talk about what worked, laugh about what didn’t, and get curious together. When that happens, learning compounds quickly.”
AI adoption without big budgets
For smaller agencies and DMCs, concerns around cost and technical complexity often slow down adoption. Gibson argues that these fears are largely misplaced. “Budget is not your barrier. Let’s get that out of the way immediately,” he says.
Many powerful AI tools today are available through simple subscriptions rather than enterprise software packages. Gibson points to Claude Cowork as an example of an AI agent capable of handling complex office tasks while operating directly on a user’s computer. “It costs $20 a month. That’s what I use personally. There’s no enterprise contract, no IT department required, no implementation project,” he explains.
Instead, the real investment lies in learning how to use these tools effectively. Gibson believes targeted training tailored to travel professionals can accelerate adoption far more effectively than generic workshops. “A few hours of the right training beats months of aimless experimentation,” he says.
The question now is readiness
For travel agencies navigating increasing competition, rising client expectations, and complex supplier ecosystems, AI may offer a powerful operational advantage.
But the technology itself is no longer the biggest hurdle. As Gibson puts it succinctly: “The tools are ready. The question is simply whether your team is.”
AI Adoption Roadmap for Travel Agencies
| Stages | What Agents Can Do | Tools / Examples | Time to Implement | Business Impact |
| Stage 1: Quick Start | Use AI to draft itineraries, destination briefs, proposal emails and marketing content | ChatGPT, Claude, Gemini | 1–2 days | Saves 2–3 hours daily on writing and research |
| Stage 2: Itinerary costing automation | Upload Excel sheets and let AI calculate costs, adjust margins and restructure proposals | Claude Cowork, Excel Copilot | 1–2 weeks | Reduces manual spreadsheet work by 60–70% |
| Stage 3: Market intelligence | Feed reports, tourism board updates and competitor websites to AI for quick summaries and insights | NotebookLM, Perplexity | 1 week | Faster strategic decisions and trend tracking |
| Stage 4: Customer profiling | Create AI-based traveler profiles and simulate conversations to refine marketing and packages | CustomGPTs, Gemini Gems | 2–3 weeks | Better targeting of travellers |
| Stage 5: Sales support | Generate customised proposals instantly based on client preferences and budgets | ChatGPT, Claude | 2–4 weeks | Faster response time to clients and higher conversion rates |
| Stage 6: Centralised company information | Train AI on company contracts, supplier data and past itineraries to answer team queries instantly | CustomGPT, enterprise AI tools | 1–2 months | Staff retrieves information much faster |
| Stage 7: Integrated operations | Automate client communication, booking checks, and internal reporting | CRM + AI integrations | 3–6 months | Full workflow automation and operational efficiency |
Janice Alyosius is a travel and MICE journalist focusing on business travel, destination marketing, aviation and industry policy. She leads editorial content at MICEtalk and also writes for TravTalk, covering global trends, trade developments and key industry conversations. With regular reporting from tourism forums, conventions and on-ground industry events, her work blends news-led analysis with strong industry voices, offering clear context and relevance for travel trade professionals and decision-makers.
