How to prove the value of AI in global mobility
A K2 Thinking Paper, November 2026
So where does AI fit into a bespoke mobility programme? And how can you tell whether it's adding value or quietly eroding the personal service that makes bespoke programmes work?
Download the full thinking paper
So where does AI fit into a bespoke mobility programme? And how can you tell whether it's adding value or quietly eroding the personal service that makes bespoke programmes work?
Download the full thinking paper
The reasons for FastTrack
Rob McFarland, Group CCO, discusses how FastTrack by K2 streamlines mobility transition, faster, offering companies a more efficient way to manage their program. He explains that the service was developed to address the growing need for agility in business operations, enabling organisations to quickly adapt to changing market demands.
Our latest thinking paper, How to prove the value of AI in global mobility, addresses these questions directly. A central theme is an observation from Deloitte's 2026 Global Human Capital Trends: "Technology – especially something as increasingly ubiquitous as AI – is replicable. People aren't."
If every programme can access the same policy assistant or case-tracking agent, the technology alone is not a competitive advantage. The advantage lies with the "humans in the loop". These are the mobility professionals who know when an AI-generated answer looks right but isn't, and the relocation managers who can calm a family's escalating worries or guide an employee through an unexpected tax outcome. Skills like these come in countless permutations, which makes them extraordinarily difficult to automate.
The paper also challenges the way trust in AI is often measured. Drafting a routine acknowledgement may achieve a trustworthiness value close to 100%, while interpreting an immigration position might achieve only 50%. Averaging the two to claim 75% would be dangerously misleading, because the risk tolerance for each process is entirely different. In a bespoke programme, where many cases sit at the complex end of the spectrum, this distinction matters enormously.
Inside the paper, you'll find:
- Why the different dimensions of value don't always dovetail, so a gain in efficiency may come at the cost of risk or employee experience
- Four pillars for measuring AI value: efficiency, risk reduction, strategic value and trustworthiness
- Guidance on ISO/IEC 42001 and the NIST AI Risk Management Framework, including their relevance to AI provided by third parties
- A practical six-stage framework for testing AI against clear objectives before scaling it
The paper doesn't conclude that AI has no place in tailored mobility. It concludes that AI should be judged by whether it frees people to do more of what only people can do, and that this has to be proven, not assumed.
Download the full thinking paper
Frequently asked questions
Straight answers to the questions we hear most about private relocation.
Can AI replace human support in complex relocations?
+
The K2 thinking paper argues that it can't. AI can support tasks such as information retrieval and drafting, but complex moves depend on human judgement, empathy and expertise. These skills are extremely difficult to automate.
How should trust in AI be measured for complex mobility cases?
+
Trust shouldn't be expressed as a single, universal metric. Each process should be measured separately, with its own improvement plan, because routine tasks and high-risk tasks such as immigration interpretation carry very different levels of risk tolerance.
What frameworks can help govern AI in global mobility?
+
The paper highlights ISO/IEC 42001, the first international standard for AI management systems, and the NIST AI Risk Management Framework. ISO/IEC 42001 also applies to AI provided by third parties, which is relevant because many mobility tools come from suppliers.
