ITIC Americas 2026 | How can artificial intelligence enhance the travel insurance customer experience?

The ITIJ team have been reporting live from ITIC Americas in Mexico this week (31 May–2 June 2026), sharing the discussions that take place at the conference. Read all reports.

Brandon Bates, Senior Director of Global Strategy and Partner Relations, AirMed International, and President, the United States Travel Insurance Association (USTIA)

Bates began his presentation by saying there were three spectrums of artificial intelligence (AI) adoption:

• Productivity tools – general-purpose AI assistants like ChatGPT and Copilot that enhance employee efficiency across routine tasks and workflows
• Agentic AI – custom-built AI agents designed for specific business functions
• Customer-facing agentic AI – advanced agents that directly interact with consumers, handle transactions, and deliver personalised service experiences.

He said the strongest AI adoption was concentrated in agentic AI – transforming critical operational areas:

• Claims management and processing
• Travel agent training and administration
• Phone agent support tools
• Data analytics and business intelligence.

He added that these applications combined power with practicality – delivering measurable results while maintaining industry standards.

Bates continued by saying that AI-powered claim analysers extract responses to audit questions and key data points with unprecedented speed and precision, and the results include a significant reduction in manual effort, increased accuracy in compliance testing, enhanced support with SOX compliance (with US federal law the Sarbanes-Oxley Act), and better adherence to best practices.

He said that AI-driven contract risk analysis had transformed how organisations evaluate agreements and partnerships – that they save 85% of time, that volume is increased three times when it comes to processing, and there is a 40% faster turnaround.

“Enhanced fraud detection capabilities protect both the industry’s financial health and policyholder value – central tenets of the USTIA mission,” Bates said, adding that AI continuously learns from new fraud patterns, adapting to emerging threats in real time and staying ahead of sophisticated schemes.

He posed the question of whether there could be smarter underwriting through AI, and said that predictive modelling – AI-supported data pipelines – could enable more precise risk selection and dynamic pricing strategies. He added that broader data integration – historical travel patterns combined with real-time regional risk data – could support improved responsive decisions, and that product innovation – enhanced underwriting capabilities – could drive better product design aligned with traveller needs.

Bates said customers still prefer human interaction for critical decisions, but added that this is shifting with younger travellers.

He said USTIA’s vision for responsible AI included operational excellence, ethical standards, and collaborative leadership.

He finished by saying that as AI evolution accelerates, USTIA will serve as a collaborative leader – helping the industry navigate emerging technologies responsibly, strengthen public confidence, and ensure AI elevates the long-term health and integrity of the travel insurance ecosystem.

Dr Flavio Ortolano, Chief Information Officer, TuGo

Dr Ortolano started his presentation by saying: “We still treat AI like a smarter search engine: type a question. Get an answer. Move on.” He said that was the problem. “This is exactly what most companies have built for their customers and employees. If your AI strategy is a chatbot, you have not built an AI strategy. You’ve just rebuilt the search box.”

Dr Ortolano said: “When a customer asks, ‘Can you file my claim?’, this is where the chat conversation hits a wall. Because answering a question is one job; doing the work is a completely different job. The customer ends up calling a human anyway, and now they’re frustrated.”

He said there were three phases in a real AI strategy for three different problems: pre-trip, during trip, post-trip.

Dr Ortolano said there were two winning strategies. “Efficiency AI is the bet on people: build fluency, judgement, and confidence so the workforce can use AI well. Growth AI is the bet on work: redesign the workflows, decisions, and customer journeys themselves.” Both are real strategies, he said, and neither is wrong. But between them sits the missing middle: the place where AI assists, humans decide, and workflows adapt. Growth AI rebuilds the work so humans and AI both have a role inside it, he said.

Most companies pick one side or the other. They either treat AI as a tool the human uses, or they try to replace the human entirely. Both fail. The value is in the active collaboration between them.

Every customer journey has predictable points of failure, Dr Ortolano said. “In our world, it’s coverage confusion before the trip, urgent disruption during the trip, claim anxiety after. Find them. Instrument them. And put your best collaboration there.”

He finished by saying: “AI absorbs the repetitive volume, the paperwork that nobody took the job for. That work is what drains your best people. Give it to the machine. Your agents return to the work that drew them in: judgement, empathy, and the moments only a human can hold. See AI as a teammate, where you design for it.”

Federico Tarling, Chief Service Officer, Assist Card

The final speaker on the topic, Tarling started by talking about applying AI appropriately in a people-first industry. He said it was important to preserve empathy and human judgement while boosting speed, efficiency, and decision support for both travellers and assistance teams.

He advised deciding carefully where to invest to unlock value, recognise the risks, and remember that AI complements people.

Tarling then talked about using AI across the travel journey, and said before the trip, bring AI into sales channels to help assemble the right product for each traveller; during the trip, when empathy is paramount, use AI to accelerate access to a human; after the trip, streamline claims with low friction for the traveller.

Tarling then went on to talk about empathy versus automation. He said when empathy and creative problem-solving are needed – even bending the rules in true emergencies – AI should not replace the human; it should fast-track access to the human who is the solution. He added: “When empathy is not the answer, the traveller seeks minimal friction and speed (e.g., a reimbursement). Here, AI should replace the human and autonomously complete the task.” He also said it was important to design hybrid flows – instant human handoff for high-emotion cases; end-to-end automation for well-defined, low-risk tasks.

Tarling then advised on what to invest in (beyond tools) and said training, integration, data foundation, and operating models were most vital.

He spoke about managing risks in the AI era, and said to be aware of cybersecurity and sensitive-data risk, and to decide what to build versus what to buy. He said to avoid vendor dependency, and “always keep a human ‘kill switch’ for safety-critical flows and high-risk decisions”.