How AI Supports Travel Risk Management

Most organizations have some form of travel risk management (TRM) in place, and the goal is clear: Keep business travelers informed, supported, and reachable wherever work takes them. The difference today is speed. When a flight gets canceled, severe weather hits, or the situation in a destination suddenly changes, the organizations that perform best are the ones that can move from policy to action in minutes.

It’s a task tailor-made for AI, which can help compress the time between detection and response. While the technology can’t replace the expert judgment of travel managers or security teams, AI-powered tools can extend the reach of those professionals by monitoring global events, predicting disruptions before they cascade, and helping organizations locate and support travelers when it matters most.

This guide covers what travel risk management involves, where traditional approaches break down, how AI addresses those gaps, and what it takes to build a program with high adoption.

The Expanding Scope of Modern Travel Risk Management

Travel risk management (TRM) is a systematic approach to protecting business travelers from threats to their health, safety, security, and cybersecurity. Proper execution requires organizations to anticipate and assess the potential for events, develop treatments, and communicate anticipated risk exposures to their travelers — a mandate that applies regardless of company size or industry.

Industry frameworks typically organize TRM into five pillars:

• A dedicated health and safety policy
• Pre-trip risk communication
• Restrictions on high-risk destinations
• The ability to locate travelers during incidents
• Crisis management procedures

These pillars interact. A company that can’t locate a traveling employee during a disruption can’t execute its crisis protocol. Similarly, a policy that restricts high-risk travel means little if employees book outside managed channels. When those interdependencies break down, they create coverage gaps.

Three converging trends are exposing those coverage gaps and expanding the scope of TRM, pushing programs beyond traditional crisis response tactics and toward continuous, real-time coverage across the full travel lifecycle.

Managing Blended Travel With Clear Boundaries

Blended travel can increase traveler satisfaction and make trips more flexible, but it works best when programs maintain clear visibility and communication throughout the itinerary. The rise of bleisure travel creates visibility challenges that traditional itinerary-based tracking wasn’t designed to handle. Many corporate travel buyers cite duty of care as a primary concern with blended travel programs, particularly when leisure extensions fall outside the managed booking record. When a traveler adds personal days to a business trip, the organization’s duty of care obligation doesn’t pause, but its tracking capability often does.

Achieving Full Visibility Across All Bookings

Full traveler visibility is more attainable when trips stay in managed channels or are captured fast enough to support real-time outreach. Travelers who book directly with airlines or hotels for better schedules or prices disappear from your corporate tracking systems entirely. In the State of Corporate Travel and Expense 2026, a report from Skift and Navan, 80% of the business travelers surveyed said they sometimes book off-platform. Each off-channel booking represents a potential duty of care blind spot that legacy systems aren’t set up to address.

Extending Coverage to Ground Transportation

Complete duty of care improves when organizations can locate employees not only in the air and at hotels, but also during ground transportation segments of their trips. Yet that doesn’t always happen. And this “last mile” gap is both a common compliance exposure and one of the hardest to close with traditional tools.

Addressing all three gaps — blended travel visibility, off-platform bookings, and ground transportation tracking — requires a platform architecture built for real-time coverage, not one that relies on manual data pulls and disconnected systems.

How Modern TRM Platforms Close Common Gaps

Organizations that modernize their TRM architecture can act faster across the full travel lifecycle because real-time data, policy controls, and traveler communications work together instead of living in separate systems.

The biggest gains typically come from three upgrades: unifying travel data, moving policy enforcement upstream, and building disruption support into day-to-day operations.

Unify Data for Faster Response

Faster response starts with a single, current view of where people are and what they’re doing. Many environments still include multiple regional travel management companies (TMCs), separate booking tools, and manual expense processes. When data passes through multiple disconnected systems before reaching a risk management provider (often through direct feeds or Excel reports), the delay can compromise real-time tracking. Navan, however, consolidates travel bookings and real-time traveler location into a single platform — its live map shows every traveling employee’s current flight and accommodation in real time, so risk teams don’t need to pull reports from separate systems when a situation develops.

Enforce Policy at the Point of Booking

Stronger duty of care coverage is more likely when policy controls show up during the booking decision, not weeks later in a reimbursement audit. Traditional travel policy enforcement relies on post-trip audits and reimbursement reviews. By the time an out-of-policy booking surfaces, your traveler has already arrived, the risk exposure has already occurred, and you’ve already lost visibility. Industry data suggests that even among travelers aware of corporate booking tools, a significant portion still books through unmanaged channels. Platforms that surface policy restrictions and preferred options at the moment of booking can shift that dynamic, making compliant choices the easiest ones, rather than rules employees work around after the fact.

Build Proactive Disruption Support Into Operations

Crisis response works best when it’s treated as a core operating capability, not a bolt-on. The COVID-19 pandemic made the limitations of reactive crisis management impossible to ignore. Organizations that depended on manual processes to locate, contact, and rebook travelers found themselves overwhelmed. This pattern exposed the cost of treating TRM as an add-on rather than a core platform capability. Organizations that build disruption support into their standard operating model — with real-time traveler visibility, proactive alerts, and automated rebooking — can respond in minutes rather than hours when a situation develops.

What makes that operating model achievable — without adding headcount — is AI running continuously across all three upgrade areas.

How AI Strengthens Each Stage of Travel Risk Management

AI can help address the gaps in legacy TRM by operating continuously across the travel lifecycle — before the trip, during travel, and during active disruptions. Rather than replacing travel managers and security teams, AI can handle the high-volume monitoring and routine responses that would otherwise require around-the-clock manual effort. Four capability areas show the most measurable impact.

1. Pre-Trip Risk Assessment and Destination Intelligence

AI-powered platforms can assess destination risk before your employee ever books a flight. By cross-referencing geopolitical intelligence feeds, health advisories, weather data, and security reports, these systems surface risk ratings and travel advisories at the point of booking, not in a separate portal the traveler has to remember to check. This “push” model of risk disclosure, where relevant information meets the traveler in the booking flow, tends to drive higher engagement than requiring employees to seek out risk data on their own.

2. Real-Time Traveler Location Tracking

Knowing where employees are during an incident is the foundation of any crisis response. Modern platforms combine itinerary data with geolocation from traveler apps to create a real-time picture of workforce distribution. Itinerary tracking shows where a traveler is scheduled to be; geolocation shows where they are right now.

Navan, for example, provides real-time risk assessments, emergency support, and visibility into traveler locations, capabilities that helped HelloFresh improve disruption support and overall safety.

3. Predictive Disruption Alerts

Instead of notifying travelers after a flight cancels, AI systems can predict disruptions before they cascade. By analyzing satellite data, radar, atmospheric conditions, and airline operational patterns, these tools can identify at-risk flights and connections early enough for proactive rebooking. In production systems, proactive AI interventions can also include monitoring when airlines issue waivers during major disruptions and notifying impacted travelers early, so teams can change itineraries within the waiver window instead of after the situation worsens. Industry implementations of AI-driven weather forecasting have yielded millions in annual cost savings for airlines through proactive schedule adjustments, and the same predictive capability is now available to corporate travel programs.

4. Automated Crisis Communication

When an incident affects a destination, AI-powered systems can automatically:

• Identify which travelers are in the area
• Send targeted alerts through multiple channels (SMS, email, push notifications)
• Initiate check-in protocols within minutes

This replaces the manual process of pulling booking reports, cross-referencing employee lists, and sending individual messages that may characterize crisis response in your current environment.

Some platforms also use proactive automation beyond messaging. For example, they can confirm hotel check-in and payment details ahead of arrival so travelers are less likely to get stranded at the front desk during a late-night disruption.

Taken together, these four capability areas represent more than a set of features — they reflect a structural change in how AI-enabled programs handle risk across the full travel lifecycle.

From Reactive Response to Proactive Disruption Management

The most significant shift AI allows in TRM is architectural: moving from systems that respond to problems toward systems that anticipate and prevent them.

This shift is already reshaping how the industry thinks about disruption management, though with an important caveat about where human judgment remains essential.

Agentic AI Goes Beyond Chatbots

The technology has evolved from simple chatbots to agentic AI: systems that can independently execute tasks like rebooking flights, adjusting hotel reservations, and rerouting ground transportation based on corporate policy constraints, traveler preferences, and real-time availability. These systems simultaneously evaluate aircraft load, passenger itineraries, customer value scoring, and travel compliance rules to generate recovery options.

Navan’s AI, for instance, can help automate complex logistics such as flight rebookings, hotel changes, and expense categorization. Automated workflows can resolve routine inquiries while escalating complex situations to in-house support agents who already have full traveler context. Under the hood, Navan Cognition (Navan’s enterprise-grade agentic AI platform) is designed with guardrails for reliability in high-stakes workflows, and it supports tens of thousands of monthly interactions. That continuity — AI handling routine resolution, humans stepping in for complex situations, with no hand-offs between disconnected third-party providers — matters most during disruptions, when every delay compounds.

Reducing those delays also changes where travel managers and travelers spend their time. When rebooking, tracking, and expense categorization run in the background, teams can focus on decisions that actually require judgment. The Forrester TEI study commissioned by Navan found that travelers using Navan can save up to 70% of the time previously spent on booking tasks (with travel booked in less than five minutes), and it identified additional time savings in expense submission and finance processes. This can free employees to focus on strategic program decisions rather than manual rebooking and tracking.

Human Judgment Still Governs High-Stakes Decisions

Despite these advances, the industry is not moving toward full automation of disruption management. Industry polling shows that fewer TMCs and suppliers plan to deploy autonomous AI for risk management, reflecting a broader view that disruption decisions are too consequential for full automation. AI can handle the monitoring, detection, and routine response. Humans handle the judgment calls, such as:

• When to evacuate a team
• How to prioritize competing needs
• Whether a destination risk warrants canceling a trip entirely

For travel managers evaluating AI tools, the right question isn’t “will AI replace my role?” It’s “which tasks should AI handle so I can focus on the decisions that require my experience and judgment?” Getting that balance right depends on whether the people in your organization actually use the platform — which brings the conversation back to adoption.

Best Practices for Driving Adoption of AI-Powered TRM

Adoption of AI-powered TRM is more likely when organizations push safety information to travelers and embed risk checkpoints directly into the booking workflow. Adoption is the multiplier that turns technology capability into operational coverage.

Research and practitioner experience point to several levers that consistently drive higher adoption.

Push Information to Travelers, Don’t Wait for Them to Pull It

When you proactively push risk disclosures to your employees through alerts in the booking flow, pre-trip notifications, and real-time disruption messages, you tend to see better engagement than when relying on portal-based resources. Many traveling employees still don’t know who to contact during an emergency, representing a direct legal exposure that proactive push communication can close quickly.

Embed Safety Checkpoints in the Booking Flow

Your compliance efforts are most effective when they’re part of the path of least resistance. Platforms that surface destination risk ratings, travel advisories, and policy restrictions at the point of booking can help make safe behavior the default, not a separate step travelers have to remember.

In Skift and Navan’s report, 76% of the respondents surveyed said they trust AI for straightforward travel and expense (T&E) tasks. That growing trust makes it easier to introduce AI-powered safety features without adoption friction.

Build Cross-Functional Governance

Effective TRM typically requires collaboration across multiple functions:

• Travel management
• HR
• Legal
• Risk management
• Sustainability

Siloed program ownership leaves gaps: a travel policy that doesn’t account for your HR team’s duty of care requirements, or a security protocol that doesn’t connect to the booking platform. Cross-functional governance helps maintain consistent TRM standards across the entire travel lifecycle.

Make Mobile Strategy a Priority

Mobile is the primary channel for reaching travelers on the road, yet roughly one in five business travelers either lack mobile access to their company’s safety information or aren't sure whether they have it. That gap matters most during disruptions, when travelers need to reach safety resources immediately and aren't near a laptop.

Your mobile travel strategy should go beyond offering an app. It requires examining how all your program components, from risk alerts to booking to expense capture, work in the mobile environment. When those components work together across every channel, your program can shift from reacting to disruptions to anticipating them.

Building a Travel Risk Program That Works Before It’s Tested

AI can support a clear shift in travel risk management: from reactive to proactive. That means fewer scramble moments to locate employees during a crisis, because you can see where they are in real time. It also means less reliance on after-the-fact audits, because compliance controls can sit directly in the booking flow.

Those controls only matter, though, when they’re tested. Your TRM program’s effectiveness isn’t measured during quiet periods — it’s measured in the first minutes after a disruption, when every second of delay in locating, contacting, and supporting your travelers represents real risk. AI doesn’t eliminate the need for experienced travel managers and security professionals. In fact, it can extend their reach, handle the high-volume monitoring work, and give them the real-time data they need to make better decisions faster.

The organizations seeing the strongest results are those that treat AI as the operational layer beneath their existing TRM framework: pushing safety information to travelers, predicting disruptions before they cascade, and maintaining the kind of real-time visibility that duty of care obligations demand. Start by closing your biggest visibility gaps, including off-channel bookings, ground transportation tracking, and mobile communication, and build from there.