Training course · Claude · Controlling

Claude for Controllers

Claude as an AI assistant for knowledge work: projects, Artifacts, long documents, analysis and precise writing for teams.

Duration
1 day (7 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

“Claude for Controllers” is a hands-on course for roles such as Controllers and finance business partners, Heads of controlling and FP&A analysts. Rather than learning Claude in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Controlling.

Anthropic's Claude has become a go-to AI assistant for demanding knowledge work: it handles very long documents, reasons transparently and writes in a measured, easily steerable style. In this practical day you learn to exploit these strengths systematically. You analyse lengthy reports, contracts or policies, compare several sources and extract key findings with references to the exact passages. With Projects you store background knowledge and working instructions permanently, so Claude knows your terminology, templates and quality standards and you no longer start from scratch with every request.

We also show how to use Artifacts to produce standalone deliverables – structured documents, tables, charts or small interactive tools – and share them with your team. You analyse files with the built-in analysis capability, use research and connectors to company data, and put Claude to work as a critical reviewer of your own writing. A dedicated session covers Team and Enterprise plans, access management and data protection. By the end you have tested project set-ups and prompt patterns that you can apply straight away in your own function.

Controlling depends on reliable figures, fast analysis and clear communication with management. Generative AI supports controllers at exactly these points: AI assistants explain variances in the monthly report, suggest formulas and pivot structures, sanity-check planning assumptions and turn findings into plain-language management commentary. AI agents and automation pull data from the ERP, BI tools and spreadsheets, prepare forecasts and generate standard reports. This accelerates the shift from number cruncher to business partner who explains root causes and prepares decisions. A clean data foundation, clearly defined KPIs and expert review of every AI result remain essential before anything reaches a report or a board paper.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • Controllers and finance business partners
  • Heads of controlling
  • FP&A analysts
  • Cost centre and project controllers
  • Sales and manufacturing controllers

Typical challenges we address

  • Commenting on monthly reports and explaining variances under time pressure
  • Consolidating plans and forecasts from many spreadsheets and departments
  • Defining KPIs consistently and presenting them for different audiences
  • Answering ad-hoc management questions quickly and reliably

What you will be able to do

  • You write precise, structured instructions that let Claude handle complex tasks reliably.
  • You analyse long and multiple documents and obtain referenced, verifiable summaries.
  • You set up Projects with a knowledge base and style rules and share them with your team.
  • You use Artifacts and the analysis capability to produce usable documents, tables and evaluations.
  • Use AI for variance analysis, forecasting and management commentary with traceable results.
  • Have AI build formulas, queries and small reporting automations and validate them confidently.
  • Establish rules for quality assurance and confidential use of controlling data.

Course outline

Module 1 Understanding and directing Claude
  • Model family, strengths and limitations compared with other assistants
  • Clear instructions with context, examples and the desired output format
  • Structured input using sections and tags for complex tasks
  • Extended thinking and step-by-step approaches for demanding questions
Module 2 Analysing long documents
  • Uploading and querying large PDFs, reports and contract sets
  • Comparing multiple documents and surfacing contradictions
  • Summaries with references to specific passages
  • Deriving checklists and review grids from policies and guidelines
Module 3 Projects and knowledge base
  • Creating Projects with knowledge documents and persistent instructions
  • Storing style and terminology rules for consistent results
  • Sharing Projects with the team and developing them together
  • Making good use of connectors to drives and business applications
Module 4 Artifacts, analysis and writing
  • Creating Artifacts for documents, tables, charts and interactive tools
  • Analysing files and spreadsheets with the built-in analysis capability
  • Drafting, shortening, rewording and tailoring text to audiences
  • Using Claude as a critical reviewer of arguments and gaps
Module 5 Team use, data protection and quality
  • Team and Enterprise plans: administration, roles and sharing
  • Handling confidential and personal data in line with GDPR
  • Checking output: verifying facts, figures and quotations
  • Defining internal guidelines and reusable prompt patterns
Module 6 Practice lab: Controlling
  • Variance commentary
  • Formulas and queries
  • Challenging forecast assumptions
  • Management reporting
  • Reporting automation
  • KPI glossary
Module 7 Data protection, quality & transfer to daily work
  • Controlling data contains trade secrets and often personal data such as payroll costs per employee; only use approved AI environments and pseudonymise data in line with GDPR principles. Listed companies must also protect inside information under MAR.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Variance commentary

An AI assistant analyses budget-to-actual and prior-year comparisons, identifies the biggest drivers by cost type, product or region and drafts commentary for the monthly report for controllers to review.

Formulas and queries

Describe the analysis you need in plain words and receive suggested spreadsheet formulas, pivot logic, Power Query steps or SQL queries with explanations that you can test straight away.

Challenging forecast assumptions

AI questions planning assumptions on volumes, prices and costs, highlights inconsistencies between departmental plans and builds best, base and worst-case scenarios as a basis for discussion.

Management reporting

KPIs and raw data are turned into concise executive summaries, slide outlines and traffic-light commentary tailored to executives, divisional heads or cost centre owners.

Reporting automation

A workflow pulls ERP and BI exports, checks completeness, refreshes standard reports and sends drafts to cost centre owners, who add their comments before the pack is finalised.

KPI glossary

An AI assistant helps document KPI definitions, calculation logic and data sources consistently, so that business units and management speak the same language and discussions about figures become more objective.

Prerequisites

Confident use of office applications and a web browser; prior AI experience is helpful but not required. Your own non-confidential documents are welcome as practice material. You work in controlling or FP&A and are comfortable with spreadsheets and core cost accounting metrics.

Technical requirements

A laptop with an up-to-date browser or the Claude desktop app and a Claude account; we recommend Pro, Team or Enterprise access for Projects and larger files.

Data protection & compliance

Controlling data contains trade secrets and often personal data such as payroll costs per employee; only use approved AI environments and pseudonymise data in line with GDPR principles. Listed companies must also protect inside information under MAR.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Wed, 25 November 2026 Online Request
  • Thu, 3 December 2026 Munich Request
  • Wed, 9 December 2026 Online Request
  • Thu, 17 December 2026 Stuttgart Request
  • Tue, 12 January 2027 Online Request
  • Fri, 22 January 2027 Berlin Request

Frequently asked questions

How does Claude differ from ChatGPT in everyday work?

Both are capable general-purpose assistants. Claude particularly stands out with very long documents, careful reasoning and an easily steerable writing style, while Projects and Artifacts support structured work. Which tool fits better depends on your tasks, integrations and company policies – the course gives you criteria for an informed assessment.

What are Artifacts and why would I use them?

Artifacts are standalone deliverables that Claude creates in a separate panel next to the chat – a document, a table, a chart or a small interactive tool, for example. They can be revised in a targeted way, downloaded and shared. A conversation therefore produces ready-to-use results rather than scattered fragments of text.

Is my data used to train Claude?

On Team and Enterprise plans, business content is not used for model training as a matter of principle. For individual accounts this depends on settings you should review yourself. Regardless of the plan, GDPR and internal confidentiality rules apply. In the course we walk through the relevant settings and the questions to ask.

Will AI replace our BI system?

No. BI systems and data warehouses remain the reliable data foundation. AI adds a layer for interpretation, commentary and fast ad-hoc analysis. In the course we show how to pass exports to AI assistants sensibly, check results against the source and automate recurring steps without creating shadow IT.

How reliable are figures calculated by AI?

Language models can miscalculate or mismatch data. Prefer having calculations run through generated, reviewable code or formulas, and reconcile totals with the source. We practise checking routines that let you confirm plausibility quickly before any number makes it into a report.

How much does “Claude for Controllers” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 1 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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