A practical guide / Hotel finance tools
What is the best AI for a hotel finance team?
Choose the business AI tool that works well on your hotel’s finance tasks and fits your data rules. Test Microsoft Copilot, ChatGPT and Claude with the same work. Use a budget gap, a spreadsheet task and a short report for the general manager.
Start with the files your team uses and the result they need. A team working in Excel has different needs from someone pulling comments from several reports. The trial below helps you choose a tool and teach staff how to use it.
Run your finance tool comparisonChoose through finance tasks, then build the team’s confidence.
Microsoft Copilot: test the work inside Excel
Microsoft documents data insights in Copilot in Excel. These include charts, trends and formulas from the columns you name. If your pack lives in Microsoft 365, try a task there. Give it a clean cost schedule and ask it to show the largest budget gaps.
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Check the result against your formulas and pack layout. Can the user inspect the source cells, change the view and save it for next month? Ask IT which licence and features your hotel has. Include any extra licence cost in the trial sheet.
Microsoft describes enterprise data protection for work Copilot accounts. Ask IT to check the account, access and controls your task needs. Some controls depend on the plan. Make this part of the choice alongside the work the tool can do.
Read the source: Microsoft Support: data insights with Copilot in Excel; Microsoft Learn: enterprise data protection
ChatGPT Business or Enterprise: explore supplied data
ChatGPT can analyse uploaded spreadsheets and run calculations in Python. OpenAI also documents tables and charts. Test it with a file of hotel revenue and costs. Ask it to explain the columns, work out the budget gaps and show the calculations behind its answer.
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Try a short management view with a chart and source figures. Ask the user to change the month or department and make the view again. Then ask a colleague to do the same task. This shows how the tool fits questions that come up during the close.
OpenAI excludes business data from model training by default. Review the terms for the Business or Enterprise plan you are testing. Check how long files stay in the workspace and how users can share the results.
Read the source: OpenAI Help: data analysis with ChatGPT; OpenAI: enterprise privacy commitments
Claude Team or Enterprise: keep reporting context together
Claude projects can hold source files and instructions. Try a project with your pack headings, finance glossary and an approved report. Add a fresh budget schedule. Ask Claude to draft comments in the style your hotel uses for the owner’s pack.
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Check whether it follows the rules and uses the supplied figures. Can you find the manager’s note behind each reason it gives? Ask a colleague to reuse the project for a second department. The setup should help them carry your hotel’s context into the next task.
Anthropic excludes commercial inputs and outputs from training by default. Data shared as feedback, or with permission to use it, has separate terms. Review those terms and the feedback controls for the Team or Enterprise workspace you plan to use.
Read the source: Claude Help: projects and supplied knowledge; Anthropic: commercial data and model training
Worked example
Run a three-task comparison with the same files
Example with made-up details: a six-person hotel finance team chooses three jobs. They want to explain a £12,000 food cost gap, find repeat supplier references and draft the owner’s monthly summary. Each tool gets the same files and brief.
The finance lead checks the calculations and follows the source links. Team members judge whether the draft is useful and whether they can repeat the job unaided. They choose the tool that best fits their main tasks and agreed data terms.
Use a trial sheet with task, result needed, account tested, feature used, quality and cost. Add the steps needed to save and reuse the work. Put setup and connection costs beside the licence quote so you can budget for the whole job.
Illustrative example.
Trial
Use the same tasks and prepared files.
Learn
Practise with current business tools.
Apply
Improve a defined reporting workflow.
Teach a current tool, then apply it to real finance work
Our recommendation: aim for 50% of the team to be comfortable with the newest tools over 90% relying on a two-year-old one. These figures express a training preference. Keep skills fresh by revisiting what staff can do with the tools now available.
Start with an AI 101 session covering business accounts, useful context, files and checking an answer against its source. Use one finance example throughout the session. Follow it with a task each person can repeat in the next reporting cycle.
Then use an AI Design Sprint to map where those skills belong in the month-end, budgeting or reporting process. Choose the first workflow with a clear owner, useful output and enough source material to build it.
A relevant public story
Warren found a practical use for ChatGPT and Claude
Warren Lavender is an executive at a five-star luxury hotel chain. Coaching helped him become more confident with ChatGPT and Claude, and he built his own reporting dashboard. He kept exploring tools with colleagues and became more active in talks about his firm’s AI strategy.
His story shows the value of learning a tool through the hotel work a person already owns.
Read the source: Remote Humans: warren public story
Testimonial · 0:24
"I’ve learned more than I have playing around with it in the last couple of months."
Warren Lavender · Luxury hospitality
Try a practical task
Create the brief for your finance tool trial
Give each candidate tool this same assignment in an approved trial workspace.
Try this in your AI app
ChatGPT
Claude
Gemini
CodexUsing Gemini? The button copies the prompt. Paste it into the new chat.
We are evaluating business AI tools for our hotel finance team. Complete these three jobs using the attached trial files: [jobs]. Our required output for each is [output]. Apply these accounting and period rules [rules].
Show the source values, calculations and file references behind your answer. Follow our pack format [format]. Identify which parts used a spreadsheet feature, an analysis tool or your reading of the figures.
Finish with instructions another team member can use to repeat the work next month. List the input files and any workspace features needed. We will assess the result against this checklist [criteria].
Questions about this task
Should everyone use the same tool?
Use one approved starting tool where it fits the main tasks. Add another when a specific finance job and a repeatable trial justify the extra account and training.
How often should we revisit the choice?
Set a review point alongside your training plan. Re-run the priority tasks when a material feature, data term or reporting requirement changes.