Training course · Generative AI · Sales

Generative AI for Sales 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 Sales Teams” is designed for roles such as Account managers and key account managers, Business and sales development representatives and Sales managers and directors and shows step by step how to use Generative AI productively, safely and transparently in Sales – from the fundamentals to advanced workflows.

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.

In sales, the quality of preparation and customer communication decides whether a deal closes. Generative AI helps sales teams spend more time with customers and less on admin. AI assistants research companies and contacts from public sources, prepare call guides, draft personalised emails, summarise meeting notes and create proposal drafts. AI agents and automation maintain CRM data, prioritise leads and remind reps about follow-ups. For sales leaders, pipeline analysis and forecasting become faster and more transparent. The key is to use AI to support genuine relationships rather than mass, impersonal outreach. With clean CRM data, clear processes and privacy-compliant tools, AI becomes a productivity lever across the entire sales cycle.

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?

  • Account managers and key account managers
  • Business and sales development representatives
  • Sales managers and directors
  • Inside sales and sales operations
  • Pre-sales and solution consultants

Typical challenges we address

  • Finding time for research and preparation alongside day-to-day business
  • Keeping CRM data complete and up to date
  • Creating tailored proposals and tender responses quickly
  • Assessing pipeline and forecast realistically

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.
  • Prepare customer meetings faster and more thoroughly with AI.
  • Create personalised outreach, proposals and follow-ups efficiently and authentically.
  • Automate CRM maintenance and pipeline analysis in compliance with the GDPR and marketing rules.

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: Sales
  • Account research
  • Personalised outreach
  • Call preparation and objections
  • Meeting notes and CRM updates
  • Proposals and tenders
  • Pipeline analysis
Module 7 Data protection, quality & transfer to daily work
  • Customer data in sales is subject to the GDPR and to rules on unsolicited marketing by email and phone, which in Germany are particularly strict; researching and enriching personal data requires a legal basis. Confidential customer and pricing information belongs only in approved AI environments.
  • 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

Account research

An AI assistant summarises public information on target companies, such as annual reports, press releases and job ads, and derives likely challenges, stakeholder roles and conversation starters.

Personalised outreach

Research and product knowledge are turned into individual emails, LinkedIn messages and follow-ups that address the customer's situation instead of sending generic templates.

Call preparation and objections

AI creates call guides with discovery questions, typical objections and suitable responses and simulates sales conversations as role plays to prepare for difficult meetings.

Meeting notes and CRM updates

Notes or transcripts are turned into structured summaries with next steps, decision-makers and budget information and entered into the CRM as a draft.

Proposals and tenders

AI helps assemble proposal text, value arguments and answers to RFP questionnaires from existing content blocks and tailor them to the customer's requirements.

Pipeline analysis

CRM exports are analysed, stalled opportunities identified and forecast risks commented on, so pipeline reviews focus on concrete actions rather than on updating spreadsheets.

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 sales or inside sales and use a CRM system in your daily work.

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

Customer data in sales is subject to the GDPR and to rules on unsolicited marketing by email and phone, which in Germany are particularly strict; researching and enriching personal data requires a legal basis. Confidential customer and pricing information belongs only in approved AI environments.

Suggested dates

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

  • Mon, 23 November 2026 Online Request
  • Fri, 4 December 2026 Munich Request
  • Tue, 8 December 2026 Online Request
  • Fri, 8 January 2027 Hanover Request
  • Mon, 18 January 2027 Online Request
  • Mon, 1 February 2027 Berlin 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 we use AI for automated cold outreach?

AI can prepare and personalise outreach, but the legal framework stays the same: in Germany, marketing emails generally require prior consent and B2B cold calling at least presumed consent. We show how to integrate AI into your prospecting process in a legally sound way across your target markets.

How do we connect AI to our CRM?

Many CRM systems offer built-in AI features or interfaces that automation platforms can use to read and write data. To get started, exports and copy-and-paste workflows are often enough. In the course we discuss which level of integration suits your team and how to safeguard data quality.

How much does “Generative AI for Sales 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.

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