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How TMCs Can Optimize Clients’ Corporate Travel Programs With Data and AI

July 14, 2026
Three practical plays for turning the traveler data you already have into better client outcomes, without adding headcount or replacing your tech stack.
AI data playbook

Most TMCs already hold the data needed to improve every client travel program. Booking behavior, fare changes, policy compliance, preferred routes, and hotel preferences all reveal how travelers actually behave.

The challenge isn’t collecting more data. It’s turning the information spread across multiple systems into actionable insights. Corporate buyers increasingly expect their TMC to proactively improve program performance, not simply report on it.

That expectation is growing while data remains fragmented. BCD Travel’s April 2025 buyer survey found that 57% of buyers say their travel data is spread across too many systems, and only 43% feel confident using it to make decisions.

The answer isn’t another dashboard or another technology project. It’s using the data already flowing through your operation as an ongoing source of intelligence. Our latest playbook outlines three practical ways to do exactly that.

Play #1: Turn reshopping into a source of insight

Reshopping touches nearly every PNR across your client portfolio, making it one of the richest sources of traveler behavior a TMC owns. Yet most organizations only measure the savings generated on each booking.

The same data can reveal much more. It highlights where clients consistently miss savings opportunities, where policy compliance begins to slip, and which markets experience enough price movement to justify different sourcing strategies.

Instead of treating reshopping as a standalone service, leading TMCs use it as a continuous feedback loop that improves client programs over time. Our playbook breaks this approach into five practical actions, complete with effort ratings to help teams identify quick wins.

Play #2: Make sourcing an ongoing service

Travel sourcing doesn’t end when a contract is signed. Negotiated rates are loaded, but whether those agreements consistently deliver value often isn’t reviewed until the next QBR.

Booking and reshopping data can answer those questions continuously. Are negotiated rates appearing at the point of sale? Do supplier agreements reflect where travelers actually book? Which contracts are delivering less value than expected?

This helps TMCs become more strategic advisors while strengthening their own supplier negotiations through portfolio-wide insights.

The opportunity is significant. During GBTA’s 2025 air sourcing panel in Denver, a live poll found only 15% of buyers felt confident managing their sourcing programs, while one-third described the process as frustratingly complex. TMCs that bring data-backed recommendations can fill a gap many buyers struggle to address themselves.

Play #3: Use agentic AI to personalize service at scale

Most discussions around agentic AI focus on booking faster. The bigger opportunity is improving the service experience after the booking is made.

Traveler profiles already contain valuable behavioral signals, including preferred hotel brands, favorite airlines, common routes, and loyalty memberships. When AI can use that information, every interaction becomes more relevant.

It can recommend the hotel chain a traveler consistently chooses, prioritize the airline they’re most likely to book, or surface in-policy options that match their preferences. These are personalized experiences that are difficult for human agents to deliver consistently across thousands of travelers.

For TMCs, agentic AI becomes more than a cost-saving tool. It improves traveler satisfaction, reduces program leakage, and helps deliver a higher level of service across every client account.

From data collection to better outcomes

Most TMCs aren’t short on data. They’re short on time and practical ways to turn that data into measurable value for clients.

The strongest travel programs connect these three capabilities. Reshopping generates behavioral insights. Those insights improve sourcing decisions. Agentic AI uses both to deliver more personalized traveler experiences.

Together, they create a continuous cycle of improvement without replacing existing systems or increasing operational overhead.

Our playbook explores each of these plays in detail, including practical implementation steps, effort ratings, and five questions every TMC should ask before its next client QBR.

Download the TMC Travel Intelligence Playbook β†’

Want to see how these approaches work within your own operation? Book a demo and we’ll show you how they fit into your existing GDS and technology stack