Training course · Make · Human Resources

Make for HR Teams

Automation with Make (formerly Integromat) and AI modules: build scenarios, routers and AI steps while keeping data protection in check.

Duration
2 days (14 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

This course connects Make with the everyday processes of Human Resources. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

Make, formerly known as Integromat, is a visual automation platform that lets you connect applications and automate recurring processes without writing code. Over two days you will learn to build scenarios systematically, from triggers and modules through routers and filters to iterators, aggregators and data stores. You will understand how data flows through a scenario, how to reshape it with functions and how to keep an eye on operations consumption.

The second focus is AI. You connect language models through Make’s AI modules and provider integrations to classify text, extract information from emails and documents, draft replies or enrich content. You learn to catch errors with error handlers, test scenarios and document them clearly. Finally, you address data protection topics such as hosting region, data processing agreements and data minimisation, so that your automations can be run safely within your organisation.

HR departments are service providers, advisers and change agents at once: they manage contracts and processes, support managers and drive topics such as people development and company culture. Generative AI can take a lot off their plate. AI assistants draft policies, employment references, job descriptions and employee communications, answer recurring questions on leave, working time or benefits and help design training and feedback processes. Automation speeds up onboarding and offboarding and analyses employee surveys. HR, however, demands particular care: personnel data is highly sensitive, decisions about people must remain fair and transparent, and many AI applications require works council involvement. Considering these conditions from the start builds acceptance and turns AI into genuine relief.

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?

  • HR business partners
  • HR officers and generalists
  • Learning and development specialists
  • Payroll and HR administration staff
  • Heads of HR and CHROs

Typical challenges we address

  • Handling recurring employee queries alongside strategic work
  • Producing policies, references and documents quickly and in a legally sound way
  • Coordinating onboarding and offboarding across many stakeholders
  • Analysing employee feedback and HR metrics meaningfully

What you will be able to do

  • You can build Make scenarios independently using triggers, routers, filters and data transformations.
  • You can process lists and records with iterators, aggregators and data stores.
  • You can integrate AI modules for classification, extraction and text generation into your processes.
  • You can safeguard scenarios with error handlers, validation and human approval.
  • Create HR documents, communications and development concepts efficiently and soundly with AI.
  • Automate HR processes such as onboarding and employee queries with clear responsibilities.
  • Take employee data protection, co-determination and the EU AI Act into account when using AI in HR.

Course outline

Day 1

Module 1 Fundamentals: scenarios, modules and data flow
  • Interface layout, scenario editor and execution history
  • Triggers, actions and searches: module types and their role in a scenario
  • Understanding bundles, mapping and data types and using them deliberately
  • Choosing between schedules, webhooks and instant triggers
Module 2 Logic: routers, filters, iterators and aggregators
  • Using routers and filters for branching and conditional flows
  • Splitting lists with iterators and combining them with aggregators
  • Applying text, date and maths functions to transform data
  • Using data stores and variables for interim values and duplicate checks
Module 3 AI building blocks in Make
  • Connecting language models via AI modules and provider integrations
  • Automating classification, structured data extraction and text generation
  • Building prompts from scenario variables and processing output as JSON
  • Combining AI agents in Make with tools and scenarios as actions
Module 4 Integrations, error handling and testing
  • Connecting common business applications and any API via the HTTP module
  • Applying error handlers such as Resume, Ignore, Break and Rollback
  • Validating AI output and routing unusable results to a person
  • Testing scenarios, optimising operations and documenting them for the team

Day 2

Module 5 Data protection, governance and operations
  • Assessing hosting region, data processing agreements and data flows to AI providers
  • Applying data minimisation and pseudonymisation within scenarios
  • Managing connections, teams and permissions across the organisation
  • Defining approval steps, monitoring and ownership for live operation
Module 6 Practice lab: Human Resources
  • Drafting HR documents
  • Employment references
  • Employee self-service
  • Onboarding automation
  • Survey analysis
  • People development
Module 7 Data protection, quality & transfer to daily work
  • Personnel data is protected by the GDPR and national employee data protection rules; in Germany, introducing AI systems capable of monitoring behaviour or performance requires works council co-determination under the Works Constitution Act. AI used for decisions on promotion, termination or performance evaluation is high-risk under the EU AI Act.
  • 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

Drafting HR documents

An AI assistant drafts policies, works agreement proposals, job descriptions and employee information in plain language, which HR then checks against employment law and agrees internally.

Employment references

Based on a structured performance assessment, AI drafts a reference letter at the appropriate rating level with favourable yet truthful wording, which HR checks against established reference conventions.

Employee self-service

A knowledge assistant answers questions on leave, travel expenses, working time or benefits based on approved policies, cites the source and hands complex cases to HR.

Onboarding automation

Workflows create checklists, welcome emails, induction plans and tasks for IT, the line manager and buddies, so new joiners are well prepared from day one.

Survey analysis

Free-text answers from employee surveys or exit interviews are anonymised and clustered by theme, sentiment summarised and fields of action for leadership and HR derived.

People development

AI supports the design of training programmes, competency models, learning paths and guides for performance and feedback conversations, tailored to roles and company culture.

Prerequisites

You should be comfortable with common office and cloud applications and have some experience with AI assistants. No programming skills are required. You work in HR and know the core HR processes and basic employment law in your organisation.

Technical requirements

You will need a laptop with an up-to-date browser and a Make account; the free plan covers most exercises. API access for a language model is set up together during the course.

Data protection & compliance

Personnel data is protected by the GDPR and national employee data protection rules; in Germany, introducing AI systems capable of monitoring behaviour or performance requires works council co-determination under the Works Constitution Act. AI used for decisions on promotion, termination or performance evaluation is high-risk under the EU AI Act.

Suggested dates

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

  • Mon, 23 November 2026 – Tue, 24 November 2026 Online Request
  • Mon, 30 November 2026 – Tue, 1 December 2026 Kaiserslautern Request
  • Wed, 9 December 2026 – Thu, 10 December 2026 Online Request
  • Tue, 19 January 2027 – Wed, 20 January 2027 Augsburg Request
  • Tue, 26 January 2027 – Wed, 27 January 2027 Online Request
  • Thu, 4 February 2027 – Fri, 5 February 2027 Salzburg Request

Frequently asked questions

Is Make the same as Integromat?

Yes. Integromat was renamed Make and substantially developed along the way. The core principle of visual scenarios made of connected modules remains, while a redesigned interface, many new integrations and AI building blocks have been added. If you used Integromat in the past, you will quickly feel at home and discover the new capabilities on the course.

How do I keep operation costs under control?

Every module that runs consumes operations or credits, and AI calls also use quota with the respective model provider. On the course you learn to design scenarios so that filters apply early, unnecessary runs are avoided and data is processed in batches. This keeps your automations economical and predictable as volumes grow.

Can Make be used in a GDPR-compliant way?

In principle yes, provided you set up the framework deliberately. This includes choosing the hosting region, signing a data processing agreement, reviewing connected AI services and applying data minimisation. On the course you work through these points with a checklist and learn to filter or pseudonymise sensitive data within scenarios.

Does the works council have to agree to AI use?

Often, yes. In Germany, as soon as an AI system is technically capable of monitoring employee behaviour or performance, the works council has co-determination rights, plus information and consultation rights. We show how to involve employee representatives early and what an AI framework agreement typically covers.

May we process personnel data in AI tools?

Only in approved environments with a data processing agreement, a clear purpose and a legal basis. Many tasks, such as drafting policies or training concepts, need no personal data at all. Where they do, minimise and pseudonymise the data. In the course we develop practical rules for your HR team.

How much does “Make for HR Teams” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 2 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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