Free resource · Word and Excel kit
AI Finance Kit: 24 use cases and 48 prompts for finance teams
A four-stage course for management controllers, accountants, treasurers and FP&A analysts to develop their skills independently, from the first variance comment to closing agents, with an Excel dataset to practice without exposing their figures.
The AI Finance Kit, in brief
- What it is
- A self-training course in generative AI for finance teams: 24 use cases, 48 quick-to-copy examples, a challenge solved in stages and a training dataset.
- For who
- Management controllers, accountants and closing managers, treasurers and credit managers, FP&A analysts, internal auditors, CFOs and finance managers of large organizations.
- Format
- A 66-page Word document and an Excel workbook (monthly profit and loss statement, supplier invoices, customer aging balance), with entirely fictitious data.
- What it contains
- A positioning test, the rules of the game (data, verification, AI Act and GDPR), the prompt finance method, 24 sheets in four levels, four corrected challenges, career paths, a 30-day deployment plan, a glossary and a progress log.
- Tools
- Copilot, ChatGPT, Claude, Gemini and Vibe de Mistral (formerly Le Chat). The prompts are independent of the tool; each entry indicates the recommended tool and what changes from one tool to another.
- What is it based on?
- The 2026 surveys on AI in finance departments (CFO Connect, Consero), the Corporate Finance Institute's finance prompt libraries, and our practice of AI workshops in companies.
- Price
- Free, in exchange for a professional email address. No unsolicited emails.
- Update
- September 2026.
- What it doesn't replace
- Neither your organization's usage charter nor the validation by your IT department of the tool and authorized data.
- Go Further
- AI training for finance teams, AI Measurement and ROI Kit, AI charter template.
The finance function is the last of the major corporate functions to adopt generative AI, and the most frequently cited reason among CFOs isn't budget or security: it's not knowing where to begin. This kit provides a structured learning path. Four levels, six fact sheets per level, a challenge at the end of each, and a fictitious dataset for practice without revealing a single figure from your company.
1. Why a path, and not just another list of prompts?
There is no shortage of prompt lists for finance. Almost all of them have two flaws. They treat a variance comment and a closing agent as equally valid, as if they required the same maturity. And they rarely explain how to verify the result, whereas in finance, a plausible answer is not necessarily the correct one: a reversed sign, a cumulative total that extends beyond a month, or thousands read as units can easily go unnoticed in a well-phrased sentence.
Recent figures confirm the delay and its cause. Data cited by CFO Connect for its report State of AI in Finance 2026Finance and accounting are the functions where AI is least deployed (40%, compared to 78% in marketing and 92% in engineering), and 68% of CFOs attribute their slow adoption to not knowing where to start. The Consero survey conducted in the first quarter of 2026 among 102 finance departments indicates where to begin: management reporting and variance analysis are the uses that pay for themselves the fastest, in three to six months.
This is the order of the kit. We start by writing and commenting on a few handwritten figures, without any sensitive data. We then move on to anonymized files, then reusable prompts and shared assistants, and only at the end to agents who perform multiple steps on cases. At each stage, the checkpoints are as important as the prompt.
2. Four levels, from drafting to agents
A ten-question test at the beginning of the kit indicates each person's starting level. Allow one and a half to two and a half hours per level; in a team, the most effective pace is one level per week with one hour of group practice.
| Bearing | What you learn | Case examples | Duration |
|---|---|---|---|
| 1. Writing and understanding | Frame a prompt, work on text and some aggregated figures, check an answer. | Commenting on a discrepancy, simplifying a financial statement, writing graduated reminders. | 1 hour 30 minutes |
| 2. Analyze your own data | Attach an anonymized file, check its quality, prioritize discrepancies, comment on a report. | Compare actual, budget and forecast; estimate the landing; check an invoice. | 2 h |
| 3. Structure and reuse | Write variable-based prompt templates, chain the steps, create a persistent assistant shared by the team. | Rolling forecast, budget and arbitration, budget review, review of auditors. | 2 h |
| 4. Delegate to agents | Describe a mission, impose a quality protocol, maintain human validation at each stage. | Closing assistant, collection monitoring, invoice controller, Excel template auditor. | 2 hour 30 minutes |
3. The 24 use cases, family by family
Each level covers the six work families of the finance function, those we use in our AI finance training. The same family can therefore be found at four levels of maturity: reporting begins with the popularization of a financial statement and ends with an agent who produces the report with commentary from beginning to end.
Each sheet follows the same template: the objective, when to use it, the estimated gain, the necessary data and those to never paste, the recommended tool, the prompt to copy, a variant, the control points of the result, the classic trap and the bridge to the next level.
The details of each case follow: the objective, when to use it, and the first checkpoint before using the result. The complete prompt and its variant are included in the kit.
Level 1: Writing and understanding
1.1 Simplifying a financial statement for a non-financial audience
Reporting. Estimated gain: 30 to 45 minutes per note, and fewer questions after broadcast. Transforming a profit and loss statement or dashboard into a ten-line explanation that a site manager or team leader can understand.
When to use it: You have to present the results of the month or quarter to a non-financial committee, or answer an operational person who asks you "what does that mean, in concrete terms?". To check : Recalculate each variance mentioned in the text (actual less budget, then as a percentage of the budget): AI sometimes makes mistakes in direction or calculation basis.
1.2 Commenting on a discrepancy based on aggregate figures
Analysis. Estimated gain: 15 to 20 minutes per post commented, and a framework of causes that prevents overlooking a lead. Obtain a structured variance comment (finding, probable causes, question to ask) from five lines of hand-typed actual/budget.
When to use it: Third day of closing: the CFO asks why purchases are above budget in Lille and you have ten minutes to offer an initial comment. To check : Recalculate the five variances before pasting: actual minus budget, and the percentage based on the budget. A sign error in the input results in an inverted comment. The full details are reproduced below.
1.3 Draft graduated payment reminders
Management. Estimated gain: 20 to 30 minutes per case, and consistent follow-up from one accountant to another. Produce in a quarter of an hour three consistent payment reminders, from a simple reminder to a formal notice, with the right tone for the right customer.
When to use it: Monday's aging report shows an invoice that's three weeks overdue, the salesperson says they've been handling it for ten days, and nothing's happening. You need to write without upsetting a client who's still placing orders. To check : Check the number, the amount including tax and the due date in the ERP before sending: a false reminder ruins your credibility.
1.4 Document the assumptions and risk factors of a budget
Forecast. Estimated gain: one to two hours per budget, and a more complete list of risks than starting from a blank page. Write the assumptions and risks page that accompanies a budget, the one that everyone demands but no one has time to write.
When to use it: The budget is set up in Excel, the presentation to the Executive Committee is in three days and you have to explain what the figures are based on and what could derail them. To check : Check that each assumption included in the note is exactly that of the budget file: AI sometimes rounds or reformulates (+3,5% becomes +3%).
1.5 Prepare the file validation rules before opening it
Data preparation. Estimated saving: 30 to 45 minutes per file, and a checklist that can be reused every month. Establish, even before opening a file, the list of checks to be performed on each column, so as not to discover errors at the time of presentation.
When to use it: A website sends you its monthly tracking file, a colleague bequeaths you an inherited binder, or you are preparing the dataset for level 2. To check : Review each control: is it executable as is in Excel by a colleague who does not have the context? If not, specify this.
1.6 Summarize a regulatory change or an internal procedure
Compliance and monitoring. Estimated gain: 45 minutes to one hour per text, and a document that the team actually reads. Get a one-page summary of a regulatory text or internal procedure in ten minutes: what changes, who is affected, and from when.
When to use it: A note from your accountant, your federation or the legal department announces a new obligation, or a twenty-page internal procedure has just been updated, and you have to explain to the team what is changing for them. To check : Open the source text and check each date and threshold mentioned in the document: an incorrect effective date will spread to the entire team.
Level 2: Analyze your own data
2.1 Checking a dataset and ensuring the reliability of a legacy file
Data preparation. Estimated gain: 30 to 60 minutes per file, and above all, errors detected before they enter the reporting. Obtain in fifteen minutes a data quality report of an extraction (empty cells, duplicates, signs, formats, orders of magnitude) before any analysis.
When to use it: You receive an ERP extract or a consolidated file from a colleague and you must analyze it within the hour. To check : Recalculate yourself the expected number of lines (12 months, 3 sites, 10 positions, i.e. 360 combinations) and compare it to the number of lines in the file: the difference gives you the number of duplicates or missing lines.
2.2 Compare actual, budget and forecast figures and prioritize the variances
Analysis. Estimated gain: one hour per closing on formatting, and a shared priority list before the meeting. Obtain a table of variances between actual/budget and actual/forecast, sorted by impact in euros, with the five variances to be commented on as a priority.
When to use it: The month's workload is heavy and you have two hours before the review with the CFO. To check : Recalculate manually the difference between a revenue line and an expense line: the direction must be reversed between the two for the same sign of difference. This is the most frequent error.
2.3 Estimate the year-end landing based on the actual figures to date
Forecast. Estimated gain: half a day on the first version of the landing, provided that the method is validated position by position. Produce an annual landing estimate per site and per position, with an explicit method and a quantified variance compared to the budget and the 6+6 forecast.
When to use it: The CFO is asking "where will we end up?" at the close of September, and the June forecast doesn't take the last three months into account. He wants a first draft tomorrow morning. To check : Add together Completed to date plus Remaining to do for two randomly selected items: the total must be exactly the announced landing.
2.4 Detecting spending anomalies
Monitoring. Estimated gain: one to two hours per month of line-by-line review, and overruns identified before the review rather than after. In ten minutes, identify the charge lines that warrant verification: unexplained peaks, trend breaks, persistent overshoots, lack of comment on an overshoot.
When to use it: Before publishing the report, or when a site shows an overage that no one has announced. To check : Recalculate the difference in euros of a line flagged by test 1 (Actual less Budget) and verify that the percentage is reported to the Budget, not to the Actual.
2.5 Produce an annotated monthly report
Reporting. Estimated gain: 45 minutes to one hour per report, and a consistent style from month to month. Transform a validated variance table into management comments ready to be reviewed: three to five factual sentences per site, with the exact figures from the file.
When to use it: The figures for the month have been validated (cases 2.1 and 2.2 completed), the review with the sites has taken place, and you have one hour to write the comment page for the monthly pack. To check : Link each number in the "Numbers cited" list with the source table: a number not found is deleted, it cannot be corrected manually.
2.6 Check a supplier invoice before validation
Compliance and monitoring. Estimated gain: five to ten minutes per questionable invoice, and a uniform grid for the entire accounting team. Check in two minutes that a received invoice is consistent (calculations, dates, order, receipt, supplier) before validating it in the circuit.
When to use it: You approve today's invoices and one of them seems unusual: a round amount, an infrequent supplier, and no order. You want a checklist that's applied without any oversights. To check : Recalculate the pre-tax amount plus VAT on the checked invoice yourself: if the AI announces a difference, check that it does not come from rounding the VAT to the nearest cent.
Level 3: Structure and reuse
3.1 Automate the preparation of monthly data
Data preparation. Estimated gain: one to two hours per month from the second month onwards, and identical controls from one month to the next. Turn the monthly file check into a ten-minute routine: an assistant that always applies the same checks, plus a Power Query step that prepares the extraction before analysis.
When to use it: At the beginning of each month, the ERP extraction arrives with the same defects (duplicates, poorly formatted months, empty cells) and you redo the checks manually before you can analyze anything. To check : Count the rows before and after the Power Query step: the difference should be exactly the number of duplicates reported, no more and no less.
3.2 Updating a rolling forecast with scenarios and sensitivity
Forecast. Estimated gain: half a day per monthly update, and an identical mechanism from one month to the next, therefore explainable bridges. Update the year-end landing monthly by site and by station, with two scenarios and one sensitivity, reusing the same chained prompt-model.
When to use it: The actual figures for the month have been finalized, the CFO wants an updated landing for the management committee, and the 6+6 Forecast is no longer sufficient because it dates back to June. To check : Recalculate in Excel the cumulative actual of a site using SUMIFS (Actual, with Site and Month less than or equal to the closing month) and compare it to the table from step 1 to the nearest euro.
3.3 Prepare a budget review with an operational manager
Analysis. Estimated gain: one hour of preparation per review, and reviews that lead to actions rather than justifications. Arriving at each budget review with a 30-minute script, five quantified priority variances, and open-ended questions that get the operational staff talking instead of putting them on the defensive.
When to use it: The monthly review with a site director is in two days, the figures for the month have just been validated and you haven't yet read the comments line by line. To check : Recalculate from PL_mensuel, using SUMIFS by Site and Position, the variance of the month and the sum of the five priority variances: the figures in the script must be identical to the nearest euro.
3.4 Construct the annual budget and prepare the trade-offs
Management. Estimated gain: two to three days on the first version of the budget, and an arbitration note ready the day the figures are stabilized. Build an annual budget proposal per site and per position based on actual results, with written assumptions, then prepare the necessary trade-offs to reach the target margin.
When to use it: The budget campaign is starting, the CFO is expecting a first detailed version this week and the site directors have not yet submitted their assumptions. To check : Recalculate the budgeted margin of a site: Revenue minus the nine expense items; the result should equal the margin displayed by the AI.
3.5 Transforming a dashboard into recommendations and a presentation
Reporting. Estimated gain: two to three hours per committee, and recommendations formulated in the same way each month. Each month, move from the validated dashboard to a page of recommendations and a presentation plan, with an assistant who knows your KPIs and your comment guidelines.
When to use it: The monthly dashboard has been approved, the management committee meeting is in three days, and a clear message is needed for each indicator rather than a line-by-line reading. To check : Recalculate two KPIs from the summary from the source dashboard (for example, the margin rate of a site: margin divided by revenue): they must be identical to the nearest decimal.
3.6 Prepare the auditors' review
Compliance and monitoring. Estimated gain: one to two days on the preparation phase, and fewer back-and-forths with the audit team. Prepare for the auditors' intervention with an up-to-date list of documents, documented explanations of fluctuations and a compliance note, thanks to an assistant who knows your procedures.
When to use it: The audit schedule has been received, last year's list of requests is sitting in a file, and explanations of variations need to be written before the arrival of the audit team. To check : Cross-reference the list of documents with the requests received last year: each request from the previous year should have a line, repeated or marked as not applicable with the reason.
Level 4: Delegate to agents
4.1 Monthly Closing Assistant
Management. Estimated gain: 30 to 45 minutes per closing day, and delays visible from day +1 instead of day +4. Assign an agent the daily monitoring of the closing checklist, the morning progress update and the draft reminders for contributors, without them modifying or sending anything without your agreement.
When to use it: From the last working day of the month to day 5, you spend an hour a day following up with contributors and updating the checklist. To check : Before starting, predict the progress point of the day from your own reading of the checklist (number of tasks done, behind schedule) and compare with Point_J+[n].md: any discrepancy is a task that was not read correctly.
4.2 Monitoring of debt collection and customer receivables
Analysis. Estimated gain: one to two hours per week for the credit manager, and reminders sent in the right week rather than at the end of the quarter. Obtain each week, from the export of the aged balance, a summary of customer risk, a list of graded reminders ready to validate and the cases to be removed from the standard circuit.
When to use it: The aging report is exported every Monday, but nobody has time to read it line by line. To check : Before launching, choose three clients you know (one healthy, one late, one in dispute) and write down the level of follow-up you would give them; the agent must find the same ones, otherwise the classification rule is incorrectly written.
4.3 Supplier Invoice Controller
Compliance and monitoring. Estimated gain: one to two hours per batch of one hundred invoices, and consistent control across all lines instead of sampling. Have each batch of invoices received checked by an agent who verifies the supplier, recalculates the amounts, reconciles the order and the receipt, and routes each exception to the correct person, without ever validating or paying.
When to use it: The week's batch of invoices arrives in a shared library. To check : Before running the test on the entire batch, test the agent on five invoices whose results you know: three correct invoices, one with a VAT error you entered yourself, and one with manually modified IBAN numbers. It must find both and only both.
4.4 End-to-end commented monthly report generator
Reporting. Estimated gain: half a day per month, with a first complete draft on the morning of day 5 rather than the evening of day 6. Entrust an agent with the complete chain of monthly reporting: file control, variance calculation, management comments in the company style, presentation support, with two validations before distribution.
When to use it: At day 5, the figures are validated but the reporting still requires another day: tables, graphs, comments, layout. To check : Before launching, calculate the consolidated margin for the month yourself (revenue less expenses) using a pivot table and note it down; it must appear identically in the Consolidated tab and on the consolidated page of the presentation.
4.5 Excel Template Auditor
Data preparation. Estimated gain: half a day per audited workbook, and above all, errors found before they reach the forecast presented to the CFO. Have an agent audit an inherited forecast workbook, mapping tabs, inconsistent formulas, hard-coded values, broken references and loops, before entrusting them with any calculations.
When to use it: You are retrieving a predecessor's forecast workbook, or you are about to run the agent from sheet 4.6 on it. To check : Before launching the test, manually introduce two errors into a copy of the workbook: a hard-coded value instead of a formula in Forecast and a SUM function shortened by one row in Summary. The agent must find both errors in the correct location.
4.6 Rolling Forecast Agent
Forecast. Estimated gain: two to three hours per month, and a landing note available on the same day as the report is validated. Assign an agent to update the forecast monthly: integrate the actual results of the month, recalculate the landing, update three scenarios and write the note for the CFO, keeping each version.
When to use it: Each month at D+6, once the reporting has been validated, the forecast must be updated for the management committee. To check : Before launching, calculate the consolidated landing manually: cumulative actual at the end of [month] (pivot table on the export) plus Forecast 6+6 of the remaining months; the agent must land on this figure to the nearest thousand euros, otherwise a range has been incorrectly entered.
4. An example of a worksheet: commenting on a discrepancy
Here is form 1.2, as it appears in the kit. It does not require any files: five lines of handwritten information (actuals and budget) are sufficient. When to use it: On the third day of closing, the CFO asks why purchases exceed the budget on a site and you have ten minutes to offer an initial comment. Estimated profit: 15 to 20 minutes per post commented on, and a framework of causes that prevents forgetting a lead.
Act like an experienced industrial management controller preparing the monthly closing review.
Here are five lines of actual/budgeted data [site] to [period], in euros:
[Position 1] : accomplished [Rising], budget [Rising], gap [Rising] or, [percentage]. [Positions 2 to 5: same structure, one line per position].
What I already know: [two or three facts, for example: 5% rise in the price of steel in September, sales volume 7% higher than budget].
For each position where the gap exceeds [threshold, for example 3% or €20,000]write a comment in three parts: numerical observation, probable causes ranked from most likely to least likely, question to ask the operational person to confirm.
Always distinguish between volume effect, price effect and exceptional effect in the causes, and indicate which one is confirmed by a fact that I gave you.
Format: one paragraph per post, 60 words maximum, difference in euros and percentage in the first sentence.
Do not propose any cause that contradicts the facts provided, and never assert as certain a cause that I have not confirmed: mark it "to be verified".
If the discrepancies I gave you do not correspond to what was achieved under budget, please point this out before making any comments.
The outcome control pointsbefore transmitting anything:
- Recalculate the five variances before pasting: actual minus budget, and the percentage based on the budget. A sign error in the input results in an inverted comment.
- Cross out any cause that the AI presents as certain when it is not part of your facts: it remains a hypothesis until an operational person has confirmed it.
- Check that the required threshold is respected: a post below the threshold should not be commented on.
- Add up the differences in the commented posts and compare them to the site's margin difference: if they do not explain the essentials, a post is missing.
The classic trap: The AI suggests plausible causes with the assurance of a senior controller, even without any facts. "Rise in raw material prices" comes up almost every time, whether it's true or not. The comment is only valid if each cause is linked to a fact or marked "to be verified." At level 2, form 2.2 performs the same task across all positions and sites using a file, and prioritizes the discrepancies for you.
5. A risk-free training dataset
The kit comes with an Excel spreadsheet for Solveo Industries, a fictional mid-sized industrial company with €48 million in revenue and three sites that also serve as three business units (Lyon, Nantes, Lille). The file can be attached as is to any AI tool: it contains no confidential or personal data. It serves as the basis for the challenges of levels 2, 3, and 4.
- PL_monthly: the 2025 management profit and loss statement, one line per month, site and position (360 lines), in actual, budget and revised mid-year forecast.
- Supplier invoices: 120 invoices received in the last quarter, as extracted from a dematerialization tool, with order, receipt and truncated IBAN.
- Balance_agee_clients: 60 clients as of December 31st, with seniority brackets, disputes, final reminder and comments from the credit manager.
The workbook contains 25 deliberately planted anomalies and risk signals: data entry errors, duplicates, VAT inconsistencies, IBAN changes, and clients in receivership. The challenge is to identify these anomalies using AI, then compare what your controls caught with what they missed. The answer key is included as an appendix to the kit.
6. The rules of the game, before the first prompt
The kit dedicates its first part to what makes the use of AI acceptable in a financial department. Three categories of data first: what is public or fictitious and is used everywhere, what is internal but anonymizable and only goes into a company tool, and what never goes into an AI tool without written agreement (individual remuneration, IBAN, mergers and acquisitions, unpublished results).
Five verification steps, repeated in the checkpoints of each sheet: manually recalculate key figures, request the source line by line, check the sign, period, unit, and entity, test on a known case before launching a full process, and have all text originating from the finance department proofread. Finally, a list of "never": closing accounts, making an accounting decision, or drafting regulated financial communications independently remain outside the scope of AI, regardless of your level.
Since February 2025, Article 4 of the European AI Regulation requires all employers to take measures to develop their staff's AI skills; Omnibus Regulation (EU) 2026/1744 made this an obligation of means ("fostering the development of AI skills"). Following the toolkit and completing the progress log allows a finance team to demonstrate what it has learned. To formalize these rules company-wide, see our AI charter template.
7. What the kit contains
The kit is a 66-page Word document accompanied by an Excel workbook. It contains, in order: a ten-minute start with an initial prompt, the learning path map, and the placement test; the rules of the game; the seven-element finance prompt method, with a before-and-after example; the four levels, each with its introduction, six fact sheets, challenge, and "you're ready for the next step if" checklist; recommended learning paths for seven finance professions; a 30-day deployment plan for the team leader, with the weekly ritual, the shared prompt library, and the indicators to track; and six appendices: an index of the 24 cases and 48 prompts, a description of the dataset, answer keys for the challenges, a glossary, a progress log, and source files.
Download the AI Finance kit (Word and Excel, free)
66 pages, 24 use cases, and 48 prompts organized into four levels, with training data from Solveo Industries. Written by NextStart.AI based on the 2026 surveys on AI in finance departments and top finance prompt libraries.
- Positioning test and rules of the game
- 24 cards: prompt, variant, checks, trap
- Four challenges solved using fictitious data
- Career path by profession and 30-day deployment plan
8. Frequently Asked Questions
Do you need to know about AI to use the kit?
No. Level 1 starts from scratch: a first prompt in ten minutes, without files or sensitive data. The placement test at the beginning of the kit allows those already familiar with the material to start at level 2, 3, or 4.
What AI tool is needed?
The one your organization allows. Prompts work with Copilot, ChatGPT, Claude, Gemini, and Vibe by Mistral (formerly Le Chat). Each entry indicates the most suitable tool and what changes from one tool to another, particularly for file analysis functions and level 4 agents.
Can we use the prompts with our real data?
Yes, starting at level 2 and within a business tool, after anonymization: names are replaced by codes, and IBANs and personal data are removed. Each sheet specifies what should never be pasted. To learn, start with the fictitious dataset provided with the kit.
How long does it take to go through the kit?
Approximately eight hours of practice in total: one and a half hours for level 1, two hours for levels 2 and 3, two and a half hours for level 4. In a team, one level per week with one hour of common practice works well.
Is the kit suitable for an entire team?
Yes. Its final section is aimed at the team leader: a 30-day plan, a weekly one-hour ritual, a shared prompt library, and five indicators to measure before and after. The job-specific career path chart prevents everyone from having to complete all 24 scenarios.
Can the kit be used without assistance?
Yes, it is designed for self-directed skills development. We intervene when a team wants to practice on its own projects with a facilitator, during a AI finance training half a day.
9. Going further
The kit facilitates skills development; it does not replace guided practice on your own cases. Our AI finance training Get your controllers, accountants, and analysts working in pairs on their real-world cases for half a day, using the tool validated by your IT department. For banks and insurers, see also the AI training for banking and financial services.
Read also : Measuring the uses, value and ROI of AI: the 2026 toolkit, AI Charter in Business: The 2026 Model (Downloadable), AI systems governance: the 2026 toolkit, AI Maturity Grid: Assess your organization's readiness in 90 minutes et AI Ambassador Kit: Build your internal network in 90 days.
The entire series of free kits. To drive adoption: AI charter template, AI Ambassadors Kit, Manager's toolkit for dealing with AI, Adoption Roadmap Kit, AI maturity grid, AI Measurement and ROI Kit et AI Governance KitFor the AI project sponsor: AI Act kit, GDPR kit, Security and data kit, AI and Social Dialogue Kit, frugal AI kit, AI Sovereignty Kit et responsible AI kitBy profession: AI HR kit, AI marketing kit, AI kit for lawyers, AI kit for salespeople, AI toolkit for project managers, AI innovator kit et communicator's AI kit.
10. Sources
The figures and references cited on this page and in the kit are based on the following sources.
- CFO Connect, State of AI in Finance 2026: report findings and what they mean for CFOs, 2026.
- Consero, 2026 CFO Survey, survey conducted in the first quarter of 2026 among 102 financial executives.
- Corporate Finance Institute, 15 Best AI Prompts for Finance: FP&A, Treasury, and More, 2026.
- Corporate Finance Institute, 18 Best AI Prompts for Accounting: Workflows, Examples, and Guardrails, 2026.
- CFO Connect, 25 Claude Prompts for Finance Teams: CoworkCode & FP&A, 2026.
- Jaydai, AI use cases in finance: 12 examples for CFOs, 2026.
- JMCO, How Finance Teams Are Using Claude, Copilot, and ChatGPT Inside Excel, 2026.
- DFCG, AI and digital transformation at the service of management controllers, 2026 program.
- European Union, Regulation (EU) 2024/1689 on artificial intelligence, Article 4 "Control of AI", June 13, 2024.
- CNIL, Artificial intelligence: CNIL recommendations, accessed in September 2026.