Training course · Generative AI · Procurement

Generative AI for Procurement Teams

Vendor-neutral, hands-on day: how language models work, where they go wrong and how to roll out AI successfully in your team.

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

“Generative AI for Procurement Teams” is a hands-on course for roles such as Strategic buyers and category managers, Operational buyers and material planners and Heads of procurement and CPOs. Rather than learning Generative AI in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Procurement.

Generative AI has reached most organisations, yet teams often lack a shared understanding of what language models can actually do and where their limits lie. In this vendor-neutral course you will learn how large language models generate text, why they hallucinate and how careful prompting, context and source checking lead to reliable results. Rather than relying on any provider's marketing claims, you will work with transparent criteria that help you compare tools and judge their fit for your own tasks.

The second focus is everyday implementation. You will identify concrete use cases in your area of work, weigh benefit, risk and effort, and draft a realistic roll-out plan for your team. This covers ground rules for handling confidential data, a practical prompt library and ways to build acceptance and make results measurable. Throughout the day you work with examples from your own field, so you leave with an actionable roadmap rather than a set of abstract ideas.

Procurement has evolved from order processing into a strategic value driver: cutting costs, securing supply, managing supply chain risk and meeting sustainability requirements. Generative AI supports buyers in every phase of the source-to-pay process. AI assistants draft specifications and tender documents, compare bids, summarise supplier contracts and prepare negotiations with arguments and scenarios. AI agents and automation research potential suppliers, analyse spend data, monitor risk signals such as insolvency or delivery delays and process order confirmations. This gives procurement more time for supplier development and strategic category management. Reliable master data, clear approval rules and careful handling of confidential terms and supplier information remain essential.

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?

  • Strategic buyers and category managers
  • Operational buyers and material planners
  • Heads of procurement and CPOs
  • Supplier managers and supplier quality engineers
  • Public sector procurement staff

Typical challenges we address

  • Comparing bids with different structures quickly and fairly
  • Keeping track of supplier risks and supply chain due diligence obligations
  • Drafting precise tender documents and specifications
  • Making spend data from different systems usable for analysis

What you will be able to do

  • You can explain clearly how language models generate text and why hallucinations occur.
  • You can write prompts that consistently deliver useful, verifiable results.
  • You can compare AI tools against transparent criteria covering data protection, features and cost.
  • You can identify and prioritise concrete use cases for your area of work.
  • Use AI for tenders, bid comparisons and negotiation preparation.
  • Analyse spend and supplier risks with AI support in a data-driven way.
  • Take confidentiality, public procurement law and supply chain due diligence into account when using AI.

Course outline

Module 1 How large language models work
  • Tokens, context windows and probabilities: what happens when a model generates text
  • Training knowledge versus web search versus your own documents (RAG)
  • Text, images, audio and code: what multimodal models can do today
  • Realistically assessing typical strengths and weaknesses in office work
Module 2 Spotting hallucinations and getting reliable output
  • Why models produce plausible-sounding errors and when the risk increases
  • Prompting techniques: role, context, examples, output format and step-by-step instructions
  • Requesting sources, cross-checking facts and introducing a four-eyes principle
  • Scoping tasks so that AI assists rather than decides
Module 3 Choosing tools without vendor bias
  • Overview of chat assistants, AI built into office suites and specialist tools
  • Criteria: data processing, hosting location, admin features, integrations and pricing model
  • Enterprise licences, API access and locally hosted open-source models compared
  • Building a simple scoring matrix for your own tool selection
Module 4 Identifying use cases in your field
  • Systematically capturing recurring writing, research and analysis tasks
  • Rating benefit, risk and implementation effort for each use case
  • Distinguishing quick wins from strategic initiatives
  • Creating a prioritised use-case backlog for your team
Module 5 Rolling out generative AI in your team
  • Usage rules: which data may go into which tool and who signs off results
  • Building and maintaining a shared prompt library and templates
  • AI champions, training formats and peer exchanges to embed new habits
  • Measuring success: documenting time saved, quality and user satisfaction
Module 6 Practice lab: Procurement
  • Drafting specifications
  • Bid comparison
  • Negotiation preparation
  • Supplier research
  • Spend analysis
  • Supplier risk monitoring
Module 7 Data protection, quality & transfer to daily work
  • Bids, terms and supplier contracts are trade secrets and may only be processed in approved AI environments; contact details are subject to the GDPR. Public contracting authorities must also comply with procurement law and equal treatment, and companies may be subject to supply chain due diligence legislation.
  • 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 specifications

An AI assistant turns requests from business units into structured requirement specifications and statements of work, closes gaps by asking follow-up questions and keeps wording product-neutral.

Bid comparison

AI extracts prices, lead times, payment terms and deviations from the request from differently structured bids and builds a comparison matrix as the basis for the award decision.

Negotiation preparation

Market information, price trends and supplier history are turned into negotiation strategies with targets, concessions and arguments, plus role plays to prepare for difficult conversations.

Supplier research

AI supports the search for alternative sources, summarises publicly available information on potential suppliers and creates questionnaires for supplier qualification.

Spend analysis

Spend data from ERP exports is classified with AI support, mapped to categories, consolidation opportunities identified and results presented clearly for management.

Supplier risk monitoring

Automations monitor news and public sources on key suppliers; AI assesses signals of insolvency, sanctions or human rights risks and alerts the responsible people early.

Prerequisites

No technical background is required. It helps to bring along typical tasks from your day-to-day work that you would like to support with AI. You work in procurement or purchasing and know your organisation's sourcing processes.

Technical requirements

You will need a laptop with an up-to-date browser and internet access. A free account with a common AI assistant is sufficient; company licences are welcome.

Data protection & compliance

Bids, terms and supplier contracts are trade secrets and may only be processed in approved AI environments; contact details are subject to the GDPR. Public contracting authorities must also comply with procurement law and equal treatment, and companies may be subject to supply chain due diligence legislation.

Suggested dates

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

  • Wed, 25 November 2026 Online Request
  • Wed, 2 December 2026 Augsburg Request
  • Mon, 14 December 2026 Online Request
  • Fri, 15 January 2027 Online Request
  • Mon, 25 January 2027 Kaiserslautern Request
  • Mon, 1 February 2027 Online Request

Frequently asked questions

Is the course tied to a specific AI tool?

No. The training is deliberately vendor-neutral. You work with widely used chat assistants and learn principles that apply to all major language models. That way you can transfer your skills to whichever tool your organisation has approved and evaluate new offerings yourself using clear criteria instead of relying on marketing statements.

How is confidential company data handled during the course?

For the exercises you use anonymised or fictitious examples from your area of work. At the same time you learn which categories of data may be entered into which tools, what to look for regarding data processing agreements and use of inputs for training, and how to set out these rules clearly for your team.

Will we leave with something concrete to implement?

Yes. You leave with a prioritised use-case backlog, a scoring matrix for tool selection, tested prompt templates and a draft set of team usage rules. These materials are designed so you can take them straight into internal discussions with management, IT and your data protection officer.

May AI decide on contract awards?

AI can structure and compare bids and highlight anomalies. The award decision is made by procurement according to defined criteria. In the public sector, the decision must also be documented and traceable under procurement law. We show how to integrate AI support transparently into your award process.

How do we protect confidential supplier terms?

Use only approved enterprise environments where inputs are not used for training and data processing is contractually governed. Terms offered by other bidders must never find their way into communication with suppliers. In the course we discuss practical rules for handling sensitive procurement data.

How much does “Generative AI for Procurement Teams” 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.

More courses for Procurement Teams

More Generative AI courses

All 45 Generative AI courses

Generative AI · MunichGenerative AI · SalzburgGenerative AI · BerlinGenerative AI · AugsburgGenerative AI · HanoverGenerative AI · BremenGenerative AI · StuttgartGenerative AI · KaiserslauternGenerative AI · Online