Artificial intelligence has moved into the everyday working lives of UK businesses at remarkable speed. Employees are using it to research information, analyse data, summarise documents, automate repetitive tasks and find answers that once involved working through multiple systems or spreadsheets.
The latest data gives some indication of how quickly that shift is happening. According to the Office for National Statistics (ONS), around 35% of UK businesses with 10 or more employees were using at least one AI technology by June 2026. Among businesses with 250 or more employees, that figure reached 49%. Employee adoption is even further ahead, with 55% of employees reporting that they use AI for work or education.
The conversation is now moving on from whether businesses will use AI to where it can make the biggest practical difference. For companies with mobile workforces, travel is an interesting place to look.
Think about everything involved in moving hundreds or thousands of people between projects, sites and locations. There are accommodation searches, hotel rates, rail journeys, approvals, project dates, expenses, invoices, cost codes, traveller preferences, company policies, carbon emissions, cancellations and last-minute changes. Every trip creates another trail of information.
Used properly, AI has the potential to make some of that information much easier to understand and act on. It could help businesses identify spending patterns, forecast requirements, spot unusual activity and find opportunities for savings much faster.
But AI needs something useful to work with.
For businesses whose workforce travel is still spread across personal booking accounts, spreadsheets, emails, expense claims and separate supplier systems, introducing another layer of technology will not automatically create control. The quality of the result depends heavily on the quality and completeness of the underlying travel data.
This is why the rise of AI makes centralised workforce travel management increasingly important.
Roomex brings accommodation, rail, expenses, reporting and travel management into one system, giving businesses greater visibility over how their workforce travels and what it costs. As AI develops, that foundation of connected travel data becomes even more valuable.
This guide looks at where AI in the workforce is heading, what it could mean for travel management and how businesses can prepare for a future in which travel decisions become increasingly data-led.
The speed of AI adoption makes it easy to assume that most businesses have already worked out exactly what they want to do with it. The reality is much less tidy.
The ONS found that around a third of businesses with 10 or more employees were using AI by June 2026, up from approximately 12% in late 2023. Yet only around one in ten AI-using businesses with 10 or more employees said they were using the technology extensively.
A separate 2026 UK Government study paints a similar picture. Among businesses handling digitised data, 41% reported using AI for at least one purpose. However, only 21% of AI users said their tools were integrated into existing business systems.
That gap is important.
Using an AI assistant to summarise a document is one thing, but connecting intelligent technology with the systems a business already uses to manage money, people and operations is considerably more powerful.
What are businesses actually using AI for?
Current use still tends to focus on practical everyday tasks. The UK Business Data Survey 2026 found common applications included:
- researching information
- summarising or collecting internal information
- drafting reports and correspondence
- analysing data or building models
- customer service
- writing computer code
- supporting existing workflow and productivity systems
Larger organisations are already taking some of those uses further. Among large businesses surveyed, 32% reported using AI to analyse data or build models.
That is particularly relevant to workforce travel. Travel teams already generate enormous amounts of structured information. The opportunity lies in using technology to make that information easier to interpret, allowing finance, procurement and travel teams to spend less time assembling reports and more time deciding what to do with them.
A hotel booking can look like a simple transaction. At scale, it becomes part of a much larger operational picture.
A company managing mobile workers may need to understand:
- who is travelling
- where they are working
- when they need to arrive
- how long they are staying
- which accommodation they book
- how far accommodation is from the worksite
- what rates were available when they booked
- whether the booking complied with company policy
- which cost centre or project should pay for it
- what rail travel was required
- what additional expenses were incurred
- whether bookings were changed or cancelled
- how frequently individual locations are visited
- what carbon emissions are associated with that travel
Multiply those decisions across hundreds of employees, multiple projects and an entire financial year and the scale becomes obvious. The challenge is getting that information into a form where it can actually be used.
A hotel booking can look like a simple transaction. At scale, it becomes part of a much larger operational picture.
A company managing mobile workers may need to understand:
- who is travelling
- where they are working
- when they need to arrive
- how long they are staying
- which accommodation they book
- how far accommodation is from the worksite
- what rates were available when they booked
- whether the booking complied with company policy
- which cost centre or project should pay for it
- what rail travel was required
- what additional expenses were incurred
- whether bookings were changed or cancelled
- how frequently individual locations are visited
- what carbon emissions are associated with that travel
Multiply those decisions across hundreds of employees, multiple projects and an entire financial year and the scale becomes obvious. The challenge is getting that information into a form where it can actually be used.
Fragmented travel creates fragmented information
When employees arrange accommodation through different websites, book rail separately and submit expenses later, finance teams can end up reconstructing what happened after the money has already been spent.
There may be invoices in one system, booking information in another and project information sitting somewhere else entirely.
That makes seemingly straightforward questions surprisingly difficult to answer.
Which project is generating the highest accommodation spend? Are teams consistently booking above policy in a particular city? Are people staying in the same locations frequently enough to justify negotiated rates? Could longer stays be booked differently? Are travellers choosing considerably more expensive rooms when comparable alternatives are available?
These are exactly the kinds of questions that become easier when travel information is centralised.
Roomex allows businesses to book, manage, pay for and report on workforce accommodation and rail in one place. Its platform provides access to over two million hotels and self-catering apartments, alongside travel policy controls, approvals, payment options and analytics.
That centralisation creates something increasingly important in an AI-enabled workplace: usable data.
The most interesting applications of AI in travel are unlikely to involve replacing the person responsible for travel. They involve helping that person understand a much larger volume of information.
A travel manager may already know that accommodation costs have increased. Smarter analysis could help explain where the increase happened, which booking behaviours contributed to it and which locations deserve attention first.
A finance manager may know that a project exceeded its travel budget. Better forecasting could help identify that risk earlier.
A procurement team may know that employees frequently visit Manchester, Birmingham or Glasgow. Travel data could help establish whether booking patterns are concentrated enough to warrant negotiated rates.
This is where AI and workforce management begin to overlap in useful ways.
Spend pattern analysis
One of AI’s clearest strengths is its ability to process large datasets and identify patterns.
Applied to workforce travel, that could mean analysing:
- average nightly accommodation costs
- changes in rates over time
- spend by project or cost centre
- booking lead times
- cancellation behaviour
- frequently visited locations
- traveller booking behaviour
- policy compliance
- rail expenditure
- differences between available and selected accommodation
Instead of asking finance teams to manually work through thousands of rows, intelligent tools could increasingly help surface the information that deserves investigation.
Predicting future accommodation demand
Workforce travel can fluctuate dramatically.
A construction business might suddenly need 30 workers near a new project. An engineering company may have teams moving between sites for months. A retailer could have temporary demand around store openings, refits or maintenance programmes.
Historical booking information can help businesses understand those patterns.
Over time, AI could make forecasting increasingly sophisticated by combining previous travel behaviour with project schedules, seasonal demand, booking lead times and rate movements.
That could help businesses identify accommodation requirements earlier, giving them additional time to source appropriate properties or negotiate rates.
Identifying unusual spending
Not every expensive booking represents a problem.
A worker may need to stay in a particular location because of a project requirement. Availability may be unusually limited. A late booking might be unavoidable.
What technology can help with is identifying the exceptions worth examining.
For example, an unusually high nightly rate, repeated bookings outside policy or sudden increases in spend within a particular project could be flagged for review.
The final judgement still belongs to the business. AI can make finding the relevant information considerably quicker.
Making reporting easier to interrogate
Traditional dashboards are useful when you know exactly what you are looking for. AI creates the possibility of a more conversational relationship with business data.
Instead of manually filtering several reports, a travel or finance manager could eventually ask questions such as:
- Which five locations produced our highest accommodation spend last quarter?
- Where did we have the greatest opportunity to save?
- Which projects are likely to exceed their travel budgets?
- Which employees regularly book outside policy?
- Where are booking lead times shortest?
- Which locations should we consider for negotiated hotel rates?
The value comes from turning a large body of travel information into answers people can use.
Businesses do not need to wait for some distant version of AI to start making better use of travel data. Advanced travel analytics can already reveal information that would be extremely difficult to identify through manual reporting alone.
Roomex Insights and Insights Pro are particularly relevant here because they help businesses understand the decisions behind their accommodation spend.
Moving beyond the final booking price
Knowing that a room cost £120 tells you what the business paid. It does not tell you whether £120 represented good value at the time.
That requires context.
What other hotels were available? Were they genuinely comparable? How close were they to the required location? Did they have the same star rating? Were the cancellation terms similar?
Roomex Insights Pro uses booking and search information captured at the point of booking to help answer those questions.
It distinguishes between:
Actual Savings: instances where a booking delivered savings compared with other available options.
Potential Savings: instances where a lower-cost, like-for-like hotel was available but was not selected.
Comparisons can account for factors including location, hotel rating and cancellation terms. Businesses can then examine the information by city, hotel, policy or individual booker.
This matters because cost reduction becomes specific. Rather than telling a travel manager to “reduce hotel spend”, the data can help show where money is being left on the table and which behaviour is contributing to it.
Turning visibility into action
Travel reporting is most valuable when it leads somewhere.
A city with consistently high spend might justify negotiated rates. Repeated late bookings could indicate that project teams need to provide travel requirements earlier. A particular policy might need adjusting. A group of travellers may benefit from clearer guidance about preferred accommodation.
Roomex also provides spend analysis and works with customers to identify areas where further savings may be possible.
That combination of technology and account expertise is important because information alone does not make a decision. Someone still needs to understand the operational context and decide which action makes sense.
Much of the discussion around the benefits of AI in the workplace focuses on productivity, and there is growing evidence behind that argument.
UK Government AI Adoption Research published in 2026 found that 75% of businesses already using AI reported improved workforce productivity, while 57% said they had developed new or improved processes or operations.
Those figures are self-reported, so they should be treated as businesses’ assessment of the impact rather than an objective measure of productivity. Even so, they show why organisations are looking beyond experimental use.
For travel and finance teams, productivity improvements could come from several areas.
Less time spent assembling information
Reporting can involve a surprising amount of administrative work when information is scattered across systems.
Centralised corporate travel management software already reduces much of that fragmentation. AI could make the next stage of analysis faster by helping people query, summarise and interpret those records.
Faster answers to operational questions
A travel manager may receive a question from finance about hotel spend in a particular region. Procurement may want to understand which properties are used most frequently. A project manager might need an estimate of likely accommodation costs.
When information is properly structured, intelligent tools can reduce the time required to find those answers.
Greater capacity for strategic work
Reducing repetitive analysis gives people additional capacity to focus on areas where human judgement has greater value.
For travel teams, that might include:
- negotiating important supplier relationships;
- reviewing travel policy;
- improving traveller experience;
- planning complex projects;
- working with finance on budgets;
- addressing recurring compliance problems;
- supporting sustainability objectives; and
- helping employees when a journey does not go to plan.
The opportunity is therefore less about removing the travel manager and more about giving that person better information.
Workforce travel has a habit of becoming complicated at exactly the wrong moment.
A hotel cannot find a reservation. A worker reaches a property late at night. A project suddenly needs additional rooms. A group booking changes. Accommodation that looked suitable online turns out to be impractical for the workforce using it. These situations require context, judgement and often a conversation.
Roomex has spent over 20 years building its business around the particular requirements of mobile workforces. According to its current enterprise information, the company has approximately 120 employees, with over 70% of its team focused on Customer Success and Technology.
That balance says a lot about where effective travel management is heading.
Technology handles scale. People handle complexity.
Roomex is designed as a self-booking platform, and approximately 97% of reservations are completed through the portal without human intervention.
For straightforward travel, that efficiency matters. Employees and bookers can search and arrange accommodation without waiting for somebody else to process a reservation.
When travel becomes complicated, support is available.
Roomex’s travel experts can assist with:
- group accommodation
- long-stay bookings
- project requirements
- hotel recommendations in unfamiliar locations
- amendments
- missing confirmations
- check-in issues
- reservation checks
- technical or payment problems
There is a useful lesson here for businesses thinking about AI.
Automation is particularly valuable when it removes repetitive work. Human expertise becomes particularly valuable when something falls outside the normal process.
The strongest travel programmes make room for both.
Travel budgets can be difficult to manage because much of the reporting happens after the decision has already been made.
A hotel is booked. A train ticket is purchased. Expenses are incurred. The invoice arrives. Finance then works out where the money went.
Centralised travel management changes the timing of that visibility.
Roomex allows accommodation, rail and travel spending to be brought into the same environment, with bookings and expenditure matched against internal cost codes. Businesses can also consolidate travel bookings into itemised billing rather than processing a stream of unrelated invoices.
AI could make that information increasingly predictive.
From historical reporting to forward-looking budgets
Imagine a business with several active projects.
Historical travel data might show:
- average accommodation spend per worker
- typical project booking volumes
- seasonal hotel rate changes
- average booking lead time
- rail spend
- recurring project locations
- cancellation patterns
- the difference between budgeted and actual travel costs
AI could potentially use those patterns to help finance teams estimate future requirements and flag projects where costs appear likely to exceed expectations. The objective would be to give teams time to respond.
That might mean negotiating accommodation earlier, adjusting policy, changing booking behaviour or investigating why one project is spending considerably more than another.
Better budget conversations
A useful travel forecast should also make discussions between finance and operational teams easier.
Rather than simply being told that a project is over budget, managers can understand what is driving the increase. Perhaps workers are booking at shorter notice. Perhaps local hotel rates have risen. Maybe teams are staying farther from site because preferred accommodation is unavailable. Perhaps the project has simply required additional people.
Data creates context. AI could make that context faster to uncover.
Cost remains one of the biggest pressures in workforce travel, particularly for companies moving large numbers of employees between projects.
Roomex says customers can save up to 30% on travel costs through its wider platform and services. Its enterprise proposal also reports consistent hotel cost savings averaging 15% across bookings through Roomex.
Those savings come from several parts of the travel programme, including access to broad accommodation supply, exclusive rates, policy controls, analytics and expert support.
AI could add another layer by making potential savings easier to identify.
Finding patterns behind overspend
A single expensive booking tells you very little.
Repeated expensive bookings in the same city tell you considerably more.
Travel data can reveal whether a business repeatedly encounters the same problems:
- employees booking too late
- preferred hotels being unavailable
- teams selecting higher-cost options
- project locations generating unusually high spend
- cancellation charges
- poor policy compliance
- frequent demand in locations where a bespoke rate could be negotiated
The advantage of AI is its ability to examine those patterns at scale.
Supply still matters
There is an important point here that can get lost in discussions about intelligent technology.
AI cannot recommend a better accommodation option if the travel platform does not have access to one. Roomex sources accommodation from over 35 global supply sources and provides access to over two million hotels and self-catering apartments, including exclusive negotiated Roomex rates.
For mobile workforces, breadth of supply matters because the best property is often determined by practical considerations: proximity to site, parking, availability, length of stay and budget.
Better analysis and deeper supply therefore work together.
Workforce travel often looks very different from conventional corporate travel.
A consultant travelling to London for two nights has a relatively simple accommodation requirement. A team of engineers spending eight weeks near an infrastructure project does not.
Longer project stays can involve:
- multiple workers arriving and leaving on different dates
- changing headcounts
- parking requirements
- kitchens and laundry facilities
- proximity to remote sites
- negotiated long-stay rates
- extensions
- cancellations
- changing project schedules
This creates another area where historical data could become valuable.
Predicting recurring project requirements
If a company regularly sends similar teams to comparable projects, previous booking information can help establish likely requirements.
Over time, AI could help identify patterns around stay length, preferred accommodation type, average cost, booking lead time and location.
That could give travel teams a better starting point when the next project begins.
Roomex’s Projects & Meetings team already supports group bookings, meeting requests and long-stay accommodation requirements. Combining that expertise with increasingly intelligent analysis could make future project planning even more proactive.
A travel policy defines the decisions a business wants its workforce to make.
Technology helps turn those decisions into everyday behaviour.
Roomex allows businesses to create custom travel policies, approval processes and compliance controls. Travel managers can therefore establish appropriate rules around booking behaviour rather than relying on employees to remember guidance every time they travel.
AI could make policy management increasingly responsive.
Identifying where policy is breaking down
Rather than looking only at an overall compliance percentage, smarter analysis could help identify patterns such as:
- particular locations with frequent exceptions;
- teams regularly booking above permitted rates;
- recurring late bookings;
- individuals who repeatedly select higher-cost accommodation;
- projects where the existing policy is impractical; or
- accommodation shortages forcing travellers outside normal rules.
Some of those findings may indicate traveller behaviour that needs addressing. Others could reveal that the policy itself needs to change. That distinction is important. A policy that repeatedly fails in one location may be unrealistic for the accommodation market there. Better data gives travel managers the evidence needed to adjust it.
Workforce travel management also carries responsibilities that extend well beyond price. Employees need appropriate accommodation, clear booking information and support when something goes wrong.
Technology can improve visibility, but businesses should be cautious about handing sensitive decisions entirely to automated systems.
Where technology can support traveller welfare
Connected travel data can help organisations understand where employees are expected to be and when.
Depending on the systems and policies in place, businesses can use travel information to support:
- booking visibility;
- traveller communications;
- reservation checks;
- accommodation policy;
- project planning;
- disruption management; and
- support for employees travelling alone or arriving late.
Roomex’s mobile app also allows travellers and bookers to manage travel while on the road, while its support teams can assist with check-in problems and complex reservations.
AI could help make relevant information easier to surface, but a traveller facing a real problem may still need a knowledgeable person who can resolve it.
Sustainability adds another layer of information to workforce travel.
Roomex allows customers to track emissions generated by bookings and incorporate carbon reporting into their travel programmes. As organisations collect better travel and emissions data, AI could potentially help identify patterns that are difficult to see through conventional reports.
For example, businesses could examine:
- emissions by project;
- emissions by travel type;
- locations generating the greatest travel footprint;
- changes in travel behaviour over time;
- rail versus other transport choices;
- accommodation patterns; and
- the relationship between cost, traveller requirements and carbon.
The objective would not be to optimise one metric in isolation.
A lower-carbon travel option still needs to be workable for the employee and project. Accommodation still needs to be available, appropriately located and within budget.
Better data can help businesses understand those trade-offs rather than guessing at them.
AI can analyse information at extraordinary speed. It cannot create a complete picture from data a business never captured. This is one of the most important considerations for companies exploring AI in the workforce.
If travel data is fragmented, the intelligence derived from it will be fragmented too.
Consider two businesses
The first allows employees to book hotels independently. Rail tickets are purchased elsewhere. Expenses arrive later. Some project accommodation is arranged through email. Finance receives information at different points from different systems.
The second uses centralised corporate travel management software. Accommodation, rail, approvals, policy, cost codes, invoices and reporting sit within a connected travel process.
The second business has a much stronger foundation for intelligent analysis because the underlying picture is clearer.
Data maturity and AI maturity are closely connected
The UK Business Data Survey 2026 provides some interesting evidence here.
Businesses using AI were more likely to report collecting, analysing and sharing data than businesses that did not use AI. Among businesses whose AI tools were integrated into existing systems, 62% said they analysed data, compared with 30% among businesses whose AI tools were not integrated.²
The direction for travel management is clear.
Businesses preparing for AI should also be improving the quality, consistency and accessibility of their travel information.
The enthusiasm around AI also creates new responsibilities. Businesses need to decide which tools employees can use, what information can be entered into them and where automated recommendations require human review.
The UK Business Data Survey 2026 found that formal governance remains limited. Among businesses using AI, only 17% reported having either a formal or informal policy or guidelines covering AI use and development.
Large businesses were considerably further ahead: 56% reported having a formal written AI policy.²
For companies handling employee, financial and travel information, governance should be part of the conversation from the beginning.
Questions businesses should answer
Before integrating AI deeply into workforce travel, organisations should consider:
- What travel data can AI tools access?
- Does the system contain personal employee information?
- Where is that information processed?
- Can business data be used to train external models?
- Which decisions require human approval?
- How are automated recommendations checked?
- Who is responsible if an AI-generated recommendation is incorrect?
- What guidance have employees received?
- How will access to travel and financial information be controlled?
These questions should sit alongside the commercial opportunities. A faster answer is only useful when the business can trust how it was produced.
Businesses do not necessarily need a system covered in AI labels. They need travel infrastructure capable of supporting increasingly intelligent ways of working.
The fundamentals matter.
Centralised booking
Accommodation and rail information should be captured consistently rather than scattered across multiple personal accounts and suppliers.
Broad accommodation supply
Travel teams need enough choice to find appropriate accommodation close to where employees actually need to work.
Roomex provides access to over two million hotels and self-catering apartments through over 35 accommodation supply sources.
Policy and approval controls
Businesses should be able to define how employees book and establish approval processes where necessary.
Useful analytics
Reporting should help teams understand spend, behaviour and opportunities rather than simply presenting transaction totals.
Roomex Analytics and Insights Pro provide businesses with deeper visibility into travel spend and booking decisions.
Cost-code visibility
Travel expenditure needs to connect with the projects, departments or cost centres responsible for it.
Integrated payments and invoicing
Centralised billing reduces the work involved in reconciling travel expenditure and gives finance teams a clearer picture of overall spend.
Mobile access
Field workers and mobile employees need to manage travel when they are away from a desk.
Carbon reporting
Travel programmes increasingly need to consider emissions alongside cost and operational requirements.
Integrations
APIs and integrations make it easier for travel information to work alongside the other systems a business relies on.
Roomex, for example, integrates with Trainline for rail booking and works with partners including Allstar and Weston Analytics.
Human support
Complex project travel will always create exceptions.
Technology should make routine travel easier while giving employees and travel managers access to expertise when they need it.
Businesses do not need to redesign their entire travel programme around AI tomorrow.
A better approach is to build the foundations first and introduce intelligent tools where they solve a genuine problem.
Step 1: Centralise your travel activity
Start by understanding where bookings currently happen.
Bring accommodation, rail, expenses and relevant travel information into as few systems as possible. The clearer the dataset, the easier it becomes to analyse.
Step 2: Improve the information you capture
Decide which fields matter to your business.
That could include project numbers, cost centres, traveller teams, booking reasons, locations or departments.
Consistent information creates better reporting.
Step 3: Establish your baseline
Before trying to optimise travel, understand current performance.
Measure areas such as:
- total travel spend
- average hotel rate
- booking lead time
- policy compliance
- cancellation costs
- frequently visited locations
- savings achieved
- potential savings
- rail spend
- carbon emissions
Step 4: Choose a problem worth solving
Avoid adopting AI simply because it is available. A useful starting question is: what travel decision currently takes too long or relies on incomplete information?
The answer might be budget forecasting, hotel spend, policy compliance, project planning or reporting.
Start there.
Step 5: Set governance before scaling
Define how AI tools can access business information and which decisions require human review.
Employees should understand what they can and cannot share with external AI systems.
Step 6: Keep people involved
Travel includes financial, operational and human considerations.
Use technology to surface information and reduce administration while keeping appropriate human oversight over decisions that affect employees, budgets and projects.
Step 7: Measure the outcome
If AI is introduced to reduce administration, measure the time saved.
If the goal is lower travel costs, track savings.
If the objective is better compliance, compare behaviour before and after implementation.
The technology should earn its place in the travel programme.
The most interesting development may be how we interact with travel information.
Today’s travel platforms already allow businesses to search accommodation, establish policies, manage bookings and analyse spend.
Tomorrow’s systems could make much of that information easier to interrogate through natural language and predictive analysis.
A finance manager might ask which projects are likely to exceed their accommodation budgets during the next quarter.
A procurement manager could identify cities where booking volume makes a negotiated rate worthwhile.
A sustainability lead could explore which parts of the travel programme contribute most heavily to reported emissions.
A travel manager could identify teams whose booking behaviour consistently creates avoidable cost.
A project manager could estimate likely accommodation requirements based on previous projects with similar workforce profiles.
None of these possibilities removes the need for accommodation supply, booking infrastructure, payment processes, company policy or experienced travel support.
They make those foundations even more important.
AI is changing how businesses interact with information. For workforce travel, the biggest opportunity lies in turning a large volume of booking and spending data into clearer, faster decisions.
Roomex already gives businesses the infrastructure required to manage that information in one place.
Founded in Dublin in 2004, Roomex has spent over 20 years building travel technology specifically around mobile and project-based workforces. Today, businesses can use the platform to manage accommodation, rail, expenses, payments, policies, analytics and carbon reporting across their travel programme.
Customers can access:
- over two million hotels and self-catering apartments
- inventory from over 35 accommodation supply sources
- exclusive negotiated Roomex rates
- custom travel policies and approvals
- Roomex Analytics and Insights Pro
- rail booking through its Trainline integration
- consolidated payment and invoicing
- carbon reporting
- mobile booking and travel management
- project, group and long-stay accommodation support
- reservation checks
- dedicated account management
- support for complex travel requirements
Roomex’s current website reports that over 2,000 companies across the UK and Ireland use the platform, with customers including Musgrave, Huws Gray, Cairn Cross, Toolstation, Circet and Wickes.
As AI becomes increasingly embedded in business operations, the companies best placed to use it will be those that already understand their data.
For workforce travel, that means knowing where people are travelling, what they are booking, what it costs, whether it complies with policy and where opportunities exist to improve.
That is the foundation smarter technology needs.
Take the work out of workforce travel
If your teams regularly travel for projects, site work or longer assignments, Roomex can help you bring accommodation, rail, expenses and travel data into one place.
Give finance teams greater visibility, make booking easier for employees and uncover new opportunities to control travel costs with a platform built specifically for the mobile workforce.
Discover how Roomex can simplify your workforce travel management.
AI is already becoming part of everyday business operations, but deeper integration is still developing. For workforce travel, the opportunity lies in using increasingly intelligent technology to understand booking, spend and traveller data faster.
The businesses best positioned to benefit will have strong foundations in place:
- centralised travel information;
- consistent booking data;
- clear travel policies;
- useful analytics;
- reliable accommodation supply;
- integrated financial information;
- appropriate AI governance; and
- experienced human support.
AI can help identify the question. Good travel management still provides the context required to answer it.
How is AI used in workforce travel management?
AI can be used to analyse large volumes of travel information, identify spending and booking patterns, support forecasting, highlight unusual activity and make reporting easier to interrogate. Future applications could include predicting project accommodation requirements, identifying potential policy issues and helping finance teams forecast travel budgets.
Businesses should distinguish between existing functionality and future AI possibilities. Many of the foundations required for intelligent travel management, including centralised data, analytics, policy controls and automated booking processes, are already available through modern travel platforms.
What are the benefits of AI in the workplace for travel teams?
AI needs reliable information to produce useful analysis.
When accommodation, rail, expenses and project information are spread across different systems, businesses have an incomplete view of travel activity. Centralised corporate travel management software creates a stronger dataset for reporting, forecasting and future AI applications.
Will AI replace corporate travel managers?
AI is better suited to supporting travel managers than replacing them.
Technology can process data, automate repetitive activity and highlight patterns. Travel professionals still provide judgement, supplier expertise, traveller support and assistance with complex requirements such as project accommodation, long stays, group bookings and disruption.
Why does centralised travel data matter for AI?
Duty of care refers to an employer’s responsibility to take reasonable steps to protect employees from foreseeable risks associated with their work. For corporate travels, this can include assessing relevant risks, planning work-related journeys appropriately, providing suitable information and establishing processes for employees to report problems or seek help.
How can AI help reduce business travel costs?
AI can potentially help identify patterns associated with overspending, including late bookings, frequent policy exceptions, high-cost locations and repeated selection of expensive accommodation.
Businesses can then investigate the cause and take appropriate action, such as changing policy, booking earlier or negotiating rates.
What is Roomex Insights Pro?
Roomex Insights Pro is a premium analytics service that helps businesses understand accommodation spend and booking behaviour.
It uses search and booking data to identify Actual Savings and Potential Savings, including situations where a lower-cost like-for-like property was available but was not selected. Comparisons can consider factors including location, hotel rating and cancellation terms.
Can AI improve travel budget forecasting?
Potentially, yes.
Historical booking volumes, hotel rates, project patterns, booking lead times and other travel information could be analysed to estimate future requirements. This could help finance teams identify projects at risk of exceeding their travel budgets earlier.
What should businesses consider before using AI with travel data?
Businesses should consider data security, privacy, governance, access permissions and human oversight. They should understand which information an AI system can access, where it is processed and whether business information could be used to train external models.
The UK Business Data Survey 2026 found that formal AI governance is still developing, making internal policies particularly important as adoption grows.²
How does Roomex support workforce travel management?
Roomex allows businesses to search, book, manage, pay for and report on workforce travel from one platform. It covers accommodation, rail, expenses, analytics, policy controls, carbon reporting and project travel support, with access to over two million hotels and self-catering apartments.
Is AI already widely integrated into UK business systems?
Adoption is growing quickly, but deep integration is less common. The UK Business Data Survey 2026 found that 41% of businesses handling digitised data used AI for at least one purpose, while 21% of AI-using businesses reported that their AI tools were integrated with existing business systems.² This suggests that many businesses are still in the process of moving from individual AI tools towards more integrated operational use.
