Today's global mobility teams support a much wider range of cross-border activity than traditional assignments alone. Remote work, business travel, equity compensation, cross-border payroll, short-term assignments, and evolving reporting requirements have all expanded mobility's workload, often without a corresponding increase in staff or budget.
This creates both a capacity problem and a coordination challenge. Simply adding another system or automating an isolated task addresses only part of the problem.
The greatest friction often occurs at the handoffs between stakeholders: HR, payroll, tax, immigration, relocation, compensation, finance, business leaders, and external providers. Each one may operate with a different process, system, timeline, and definition of success. The employee, however, experiences it all as one journey. When these moving parts are not connected, the burden of coordination often falls on the mobility team or, worse, the employee.
To scale without proportionally increasing headcount, mobility teams need a more connected way of working—one with clear ownership, coordinated workflows, accessible data, and automation that routes routine work while preserving human judgment.
This article explores what that operating model looks like, where AI can add meaningful value, and what GTN is learning as we rethink how mobility services are delivered.
Over the past two decades, global mobility has become increasingly specialized. Organizations now have access to deeper expertise across tax, immigration, payroll, relocation, compensation, and talent.
While that specialization has improved individual services, it has also created a fragmented experience in which no single stakeholder necessarily sees or manages the full employee journey.
In practice, coordination failures tend to appear in three places:
Information: Employees and internal teams are asked to provide the same data to multiple providers because systems and intake processes are not connected.
Ownership: When an issue crosses functions, such as a policy exception with tax, payroll, and relocation implications, responsibility for the next step may be unclear.
Visibility: Though each stakeholder understands the status of their own work, the mobility team may not have access to a complete view of progress, dependencies, costs, and emerging risks.
These breakdowns create more than administrative inefficiency. Mobility teams spend time tracking updates, reconciling information, and resolving handoff issues instead of advising the business and supporting employees. Problems are often identified only when a deadline is close, a payroll action has been missed, or an employee raises a concern.
Standardization, outsourcing, and automation can reduce effort, but only when they are designed around the end-to-end experience. Applied to disconnected workstreams, they may make individual tasks faster without making the overall program more coordinated.
That distinction matters.
Mobility is not simply a series of transactions. It supports consequential business decisions and significant moments in an employee's career and personal life. Employees need more than completed tasks. They need clear guidance, consistent communication, and confidence that the people supporting them are working from the same information.
The challenge for mobility leaders, therefore, is not simply how to process more activity. It is how to create shared ownership, connected information, and visibility across an increasingly specialized network of teams and providers.
AI can help mobility teams process information, identify patterns, route requests, draft communications, and surface potential issues more quickly. Used well, it can reduce administrative work and give professionals more time to focus on guidance and decision-making.
But AI cannot compensate for a disconnected operating model.
If employee data is duplicated or inconsistent across systems, AI has no reliable source of truth. If responsibility for a decision is unclear, AI cannot create accountability. If providers and internal teams follow separate workflows, adding artificial intelligence to one part of the process will not connect the entire experience.
AI operates within the environment an organization has already created. In a coordinated environment, it can make information easier to access, help work move more efficiently, and alert teams when human attention is needed. In a fragmented environment, it can accelerate individual tasks without actually improving the overall outcome.
This distinction is especially important in mobility, where decisions can affect payroll withholding, tax filings, immigration status, compensation, business costs, and an employee's confidence in the process. AI may support those decisions, but clearly identified professionals must remain responsible for reviewing recommendations, applying judgment, and communicating the outcome.
That is why the first question should not be, "Where can we use AI?"
A better question is, "What coordination problem are we trying to solve?"
From there, mobility leaders can determine what information is required, who owns the outcome, where automation can reduce effort, and where human review must remain part of the process.
AI creates the most value when it is built into a connected service model, where it can help route work and surface information more intelligently without replacing professional accountability.
When people hear the word "platform," they often think of software. But a mobility platform should be understood as an operating model, not a single system.
A mobility platform connects the people, workflows, data, and decisions involved in supporting an employee's cross-border journey. Its purpose is to create a coordinated experience even when multiple internal teams, providers, and technologies are working behind the scenes.
In practice, that requires four connected capabilities:
Workflow coordination: Tasks, approvals, deadlines, handoffs, and escalations move through a defined process with clear ownership.
Connected information: Relevant employee, assignment, payroll, tax, and service data is available to the people who need it, subject to appropriate privacy and security controls.
Useful intelligence: Reporting and analytics turn that information into actionable insights, helping teams understand status, costs, trends, and potential risks.
Targeted automation and AI: Technology routes work, supports repeatable processes, and brings exceptions to the attention of the right professional.
These capabilities create value when they work together. A dashboard without connected data may provide an incomplete view. Automation without a clear purpose may move a task faster without solving an underlying need. AI without a defined workflow may generate an answer without establishing who is responsible for acting on it.
Technology enables the platform; it is not the objective. The objective is an operating model in which employees receive a more consistent experience, mobility teams have greater visibility, and professionals can spend more time providing guidance.
Productivity, efficiency, and cost control are valid reasons to invest in workflow automation, data, and AI. But they do not fully capture the value of a connected mobility platform.
The more important question is what that efficiency makes possible. Four outcomes offer a more complete measure of success.
Employees should receive clear guidance, consistent communication, and fewer duplicate requests, regardless of how many teams or providers are involved behind the scenes. The goal is not to remove every human interaction. It is to reduce avoidable friction so those interactions can focus on questions and decisions that matter.
Connected data can help employees, mobility teams, and business leaders better understand the tax, cost, compliance, payroll, and talent implications of a move before decisions are finalized. Improved visibility also helps teams identify exceptions and emerging risks earlier, when there are more options available.
When professionals spend less time gathering information, checking status, and manually routing work, they have more time to explain tradeoffs, resolve exceptions, and guide employees and business leaders through complex decisions. Technology should extend the reach of professional judgment, not remove it from the process.
The completion of a move is not the ultimate business objective. The objective is to place the right person in the right role at the right time and support that person throughout the experience. Over time, mobility data can also provide useful insights into workforce planning, talent development, internal mobility, and succession decisions.
These outcomes shift the conversation from how quickly a mobility team completes individual tasks to how effectively the program supports employees and the business. They also provide a clearer standard for evaluating technology: not by the number of capabilities introduced, but by the experiences and decisions those capabilities improve.
While every organization will approach this challenge differently, we believe mobility providers should apply the same principles to their own service delivery models. This belief is shaping how GTN continues to enhance our technology platform and bring expertise, workflows, and data together across the mobile employee journey.
We are putting this approach into practice through several connected initiatives that build on GTN’s existing technology and service delivery capabilities.
Together, these initiatives are intended to connect expertise, workflows, and data so our professionals can spend less time on administrative coordination and more time applying judgment.
GTN’s professionals have long coordinated complex mobility services across tax, payroll, immigration, relocation, and other stakeholders. As we enhance our technology platform, we are focused on making information more connected, improving visibility into service progress, and reducing the administrative effort associated with routine activities.
The knowledge and experience are already there. Our focus is on making them easier to access, share, and apply at the right moment across the employee journey.
We are moving toward a model in which a shared data foundation supports coordinated workflows, routine requests are directed to the appropriate process and professional, and employees and mobility teams have clearer visibility into what has been completed and what comes next.
The change is already visible in our enhanced My GTN Portal. Employees can securely exchange documents, view service status, and maintain travel and workday information in one place. Mobility teams can access consolidated reporting, monitor service progress, and submit service requests, reducing reliance on separate status trackers. These capabilities do not represent the finished platform, but they provide practical proof of the direction we’re heading: bringing information, activity, and visibility closer together around the service experience.
In simple terms, GTN’s technology transformation is a shift from professionals acting as the connection between fragmented information and processes to a platform that handles more of that coordination automatically. The proof points we are watching are similarly practical: fewer manual handoffs and duplicate requests, less time spent gathering status updates, earlier identification of exceptions, and more professional time available for guidance. As these capabilities expand, we will measure progress against those operating outcomes rather than the number of technologies introduced.
It’s tempting to begin by asking where AI can be used. We are finding it more useful to begin with the experience we want to create and the friction preventing it from happening today.
For a mobile employee, that might mean clearer next steps, fewer repeated requests, or faster access to guidance. For a mobility leader, it might mean better status visibility or earlier awareness of an exception. Defining that experience helps determine whether the answer is AI, workflow automation, better data, and/or a process change.
AI cannot produce dependable support from information that is incomplete, inconsistent, inaccessible, or poorly governed. Before expanding an AI use case, teams need to understand where the relevant data resides, which source is authoritative, who may access it, and how it should be maintained.
Our work with the Microsoft Fabric Lakehouse reflects this need to establish a stronger data foundation. The objective is not simply to consolidate information. It is to make relevant information more accessible and useful within appropriate privacy and security controls.
Automating an individual task can save time, but it does not necessarily improve the end-to-end experience. We first need to understand how work moves between people, where decisions occur, and which exceptions require professional attention.
That foundation allows automation to support the full workflow rather than accelerate one disconnected step.
AI can help find information, initiate workflows, summarize activity, and bring exceptions forward. It should not obscure who is ultimately accountable for reviewing the information, making a consequential decision, or guiding the employee.
This is especially important in mobility, where facts and circumstances can change the appropriate tax, payroll, or compliance response. Our objective is to use technology to give professionals better information and more time for judgment, not to remove responsibility from the process.
Together, these lessons have changed how we think about GTN’s technology transformation. The platform is not a technology project with a fixed endpoint. It is an ongoing effort to improve how people, information, and decisions come together across the service experience.
Mobility leaders do not need to wait for a large transformation initiative to improve coordination. A focused review of one employee journey can reveal where time, information, and accountability are being lost.
Choose a representative move or cross-border scenario and trace it from the initial business request through completion. Include every internal team, external provider, system, approval, and employee interaction.
Do not map only the formal process. Compare the intended workflow with what actually happens.
For every point where work moved between people or systems, ask:
This helps distinguish a coordination problem from an isolated performance issue.
The most time-consuming step is not always the best place to start. Give priority to a gap that repeatedly affects employees, delays downstream work, creates compliance or payroll risk, or consumes significant mobility-team time.
Then define what a better outcome would look like. That might mean one clear owner, a common intake process, an automated status notification, or an earlier escalation point.
Measure the current experience before changing it. Relevant measures may include:
A baseline makes it possible to determine whether a process change or technology investment produced a meaningful improvement.
Start with one defined workflow rather than attempting to redesign the entire program. Clarify ownership, remove an unnecessary handoff, connect an existing source of information, or automate a repeatable administrative step.
If AI is part of the test, document what information it may use, what task it will support, who will review its output, and how the team will evaluate the result.
After the test, compare the outcome with the baseline and gather feedback from the people who experienced the process. Use what you learn to refine the workflow before applying the approach elsewhere.
The objective is not to transform everything at once. It is to demonstrate that better coordination can reduce friction, improve visibility, and return time to mobile employees and mobility professionals.
As workflows become more connected and information becomes easier to access, mobility professionals will spend less time chasing updates, reconciling spreadsheets, and routing requests. That creates more capacity for work requiring context, judgment, and consultation.
The role of the mobility team could increasingly include helping the business answer questions such as:
These questions move mobility upstream. Instead of becoming involved only after a move has been approved, mobility professionals can help leaders evaluate options before decisions are made.
The traditional needs and responsibilities of mobility will remain important. Organizations will still need to execute moves, manage providers, meet tax and reporting obligations, and support employees through significant transitions. The opportunity is to build on those responsibilities rather than replace them.
Technology can make information and routine support more accessible. Human professionals remain essential when facts are ambiguous, priorities conflict, or a decision carries significant personal or business consequences.
In the end, the goal is not to automate people. It is to reduce administrative friction so mobility professionals can contribute earlier, provide better guidance, and help the organization make more informed workforce decisions.
Interested in how connected workflows, data, and AI could support your mobility program? Contact us to learn more about GTN’s transformation and discuss the coordination challenges your team is working to solve.