Blog · Published · Updated
AI training for spreadsheet work: from a question to an explainable finding
Short answer
AI training for spreadsheet work teaches people to understand a report before AI writes a comment: what a row describes, when the data were taken and what follows from them. The key exercise is catching a draft that compares two columns with the same name and a different scope. At Syntalith team training costs from €1,150 net a day. With 8 people each saving 1.5 hours a week, it pays back in 0.7 months after licence costs.
- net per day of closed training for the team
- from €1,150
- people in one training group
- up to 15
- after this time, we measure the effect on the same tasks
- 30 days
We belong to the OpenAI and Anthropic partner programmes and learn through their official courses. What this means ↓
Author: Syntalith · 3 min read
Statistics
Spreadsheets and AI: statistics 2026
0.7 mo.
payback of a €1,150 training at 8 people saving 1.5 hours a week each: €1,813 of time regained, €143 of licences a month. Scenario.
25.1%
According to a Harvard Business School study (2023) of 758 consultants, tasks within the model's capabilities were done 25.1% faster with AI.
40%
According to a study published in Science (2023), ChatGPT cut the time 453 professionals spent on writing tasks by 40%.
Source: Noy and Zhang, Science (2023) ↗
59%
According to Microsoft's Work Trend Index (2024), 59% of leaders worry about quantifying the productivity gains of AI.
Source: Microsoft and LinkedIn, Work Trend Index 2024 (2024) ↗
20.0%
According to Eurostat (2025), 20.0% of EU companies with at least 10 employees used AI.
Source: Eurostat, 20% of EU enterprises use AI technologies (2025) ↗
Figures checked: 22 October 2026
The same header, a different scope
A department compares two spreadsheets with an „orders” column. The first shows new requests, the second accepted orders. The draft prepared with AI writes about a fall in the number of orders, although the reports describe different stages of the process. The manager receives a fluent comment with a wrong conclusion.
Useful work starts by clearing up this difference with the person who maintains the report. The author writes down for AI what each column means and what one record is, and only then asks for a comment. In a later task the scope of the data matches, but some records have an empty field. The author describes what they can compare and what needs a question to the data owner, and does not treat an empty field as zero.
- 01Goalthe manager's question the report should answer
- 02Columnsmeaning, period of the data and what one record is
- 03Contexta description of the sheet given to AI
- 04Calculationschecked in the sheet, outside the model's text
- 05Commentobservation, guess and question kept apart
- The compared columns describe the same stage
- The period of the data is given beside the figure
- Empty fields are named as missing data
- The conclusion rests on specific rows
What it costs and when it pays back
- Time saved
- 8 people × 1.5 h a week × 4.33 = 52.0 h
- Value of that time
- €1,813
- Licences
- $160 (€143)
- Left after licences
- €1,670 a month
Payback of a €1,150 training
0.7 months
The hours saved are the scenario's assumption, which we check by timing the tasks before the training and after 30 days. €34.90 an hour is the EU average hourly labour cost for 2025 according to Eurostat. Claude Team licences at $20 per person a month, at the ECB rate of 1.1205 USD per euro on 22 October 2026.
We measure the hours in the scenario before the training and after 30 days, on the same team tasks. If after a month checking AI texts takes as long as writing from scratch, we change the exercises or the scope of the tool.
According to a Harvard Business School study (2023) of 758 consultants, tasks within the model's capabilities were done 25.1% faster with AI. Interpreting reports lies partly outside that range, so after 30 days we count the comments the manager had to send back with a question about the data.
When you need automation
If the cause of the problem is a faulty export, fix the source. If people rebuild the same calculations every week, check the features of your current tool or automation. Collecting data into a workbook on a schedule is covered in Excel automation with AI, and that is separate work from interpreting a finished report. The CIPD, on analysing learning needs, recommends taking current skills and the demands of the job into account, which lets you tell learning spreadsheet basics apart from practising interpretation.
A faulty export from the system
fixing the data source
on the IT side
Good data, wrong comments
training on spreadsheet work with AI
from €1,150 a day
The same calculations every week
automated reports
from €3,000
Where to start
We set the programme with the person who uses the reports, on the questions that keep coming back in reporting. The analyst knows the sheet, the manager knows the business question, and the person who maintains the report explains the definitions. For the call, a description of the sheet and its reader is enough, with no file of company data. We run the workshop as part of team training. For the free analysis, a description of one task the team does every week and of the tools it uses is enough. You get the written training programme within 2 working days.
Worked example · Scenario
How we count the payback: a spreadsheet team
We run the same count for your team in the free analysis.
€1,815
a month for 12 h a week of report preparation
Payback: 1.9 mo.
The hours for each firm size and checking in 15% of the old time are our assumptions. €34.90 an hour is the EU average hourly labour cost for 2025 according to Eurostat, for companies with 10 or more employees. We measured the model cost in our report system: a commentary with a check of the figures costs about €0.0002, converted at the NBP rate of 21 October 2026 and the ECB rate of 1.1205 USD per euro on 22 October 2026.
See the full calculation →
