Training course · AI Agents · Consulting
AI Agents for Consultants
Agentic AI for business teams: understand AI agents, automate workflows safely and keep control with human-in-the-loop and governance.
- 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 AI Agents with the everyday processes of Consulting. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.
AI agents go a step beyond conventional chat assistants: they plan sub-tasks, use tools such as search, files or business applications and complete multi-step work largely on their own. Over two days you will learn how agents are built, how they differ from chatbots and traditional automation, and which tasks genuinely justify their use. Widely used platforms serve as practical examples, including Microsoft Copilot Studio, custom GPTs and Claude with projects and tool connections.
In the hands-on sessions you design agent workflows for tasks from your own area of work, from triaging requests through research and drafting to handing results over to business systems. You decide where a person reviews and approves, which permissions an agent receives and how errors are detected. A dedicated block covers governance, data protection and accountability, so that your agents not only work but remain controllable, traceable and defensible within your organisation.
Consulting thrives on rapid onboarding, structured analysis and persuasive communication – exactly where generative AI makes a difference. Consultants use AI assistants to get up to speed on new industries, synthesise interview notes, build hypothesis trees, analyse client data and develop storylines for steering committees. AI agents support desk research, document comparison and first slide drafts. At the same time, AI is reshaping the business model: clients expect faster results and ask what value consultants add beyond what they could generate with AI themselves. Consultants who use AI confidently shift their time from grunt work towards judgement, implementation support and relationship building.
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?
- Management and strategy consultants
- IT and process consultants
- In-house consulting teams
- Independent consultants
- Analysts and junior consultants
Typical challenges we address
- Short ramp-up time for new clients, industries and topics
- Large volumes of interviews, documents and data under time pressure
- Heavy effort for slides, reports and proposals
- Confidentiality of client information when using AI
What you will be able to do
- You can explain how AI agents are structured and clearly distinguish them from chatbots and classic automation.
- You can select a suitable agent platform for your requirements using transparent criteria.
- You can design an agent workflow for a real process in your area and build a working prototype.
- You can define human-in-the-loop checkpoints, test cases and escalation rules.
- Accelerate onboarding, research and synthesis in consulting projects with AI.
- Develop structured storylines, slides and proposals with AI support.
- Use AI in client work in line with confidentiality obligations and communicate its use transparently.
Course outline
Day 1
Module 1 What makes an AI agent
- Agent building blocks: language model, instructions, knowledge, tools and memory
- How agents differ from chatbots, macros and classic workflow automation
- Levels of autonomy: from suggestion-making assistants to agents that act independently
- Realistically judging which tasks suit agents and which do not
Module 2 Platform overview: Copilot Studio, GPTs and Claude
- Microsoft Copilot Studio: agents grounded in company data and connected to Microsoft 365
- Custom GPTs: configuring instructions, knowledge files and actions
- Claude with projects, knowledge bases and tool access via the Model Context Protocol
- Selection criteria: data access, integrations, administration and licensing
Module 3 Designing and building agent workflows
- Breaking tasks into steps and defining hand-offs between agent and human
- Writing system instructions, examples and knowledge sources for consistent output
- Connecting tools: search, documents, email, spreadsheets and business applications
- Building a prototype agent for a real process from your own area
Module 4 Human-in-the-loop, quality and error handling
- Setting approval steps, escalation rules and thresholds for human review
- Test cases, evaluation criteria and spot checks for quality assurance
- Common failure modes: wrong tool choice, endless loops and fabricated facts
- Using structured user feedback to improve the agent over time
Day 2
Module 5 Governance, security and roll-out
- Roles and responsibilities across business units, IT, data protection and works council
- Least-privilege permissions, logging and protection against prompt injection
- Positioning under the EU AI Act and GDPR: transparency, documentation and data flows
- From pilot agent to production: operation, maintenance and measuring success
Module 6 Practice lab: Consulting
- Rapid onboarding
- Synthesising interviews
- Hypotheses and issue trees
- Storylines and slides
- Proposals and bids
- Faster data analysis
Module 7 Data protection, quality & transfer to daily work
- Client information is usually covered by confidentiality agreements and may only be processed in AI environments cleared contractually and under data protection law. AI use should be agreed with the client, and personal interview data must be handled in line with the GDPR.
- 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
Rapid onboarding
AI produces industry overviews, explains terminology, value chains and typical KPIs and drafts key questions for the kick-off – as a starting point to be verified with reliable sources.
Synthesising interviews
Notes from stakeholder interviews are organised by theme, pain point and quote, patterns and contradictions are drawn out and the results prepared as a basis for hypotheses.
Hypotheses and issue trees
Problems are broken down with AI into mutually exclusive, collectively exhaustive sub-questions, hypotheses are formulated and the required analyses and data sources derived. This quickly yields a robust workplan for the team.
Storylines and slides
Analysis results become pyramid-structured storylines, action titles and slide drafts, which the team then sharpens and builds out in the house style. The core message stays at the centre of every slide.
Proposals and bids
Tender documents are analysed, requirements turned into checklists and proposal sections on approach, work packages and team profile written with a clear focus. The client's evaluation criteria are addressed directly.
Faster data analysis
Client data is cleaned, analysed and visualised with AI support, for example for benchmarks, cost analyses or process KPIs, with documented calculation steps. Sanity checks safeguard quality before client presentations.
Prerequisites
You should already use an AI assistant such as ChatGPT, Copilot or Claude on a regular basis. No programming skills are required. Experience in consulting projects or analytical project roles; no programming skills required.
Technical requirements
You will need a laptop with an up-to-date browser. Ideally you have access to at least one agent platform such as Copilot Studio, ChatGPT with GPTs or Claude; practice accounts can be provided if needed.
Data protection & compliance
Client information is usually covered by confidentiality agreements and may only be processed in AI environments cleared contractually and under data protection law. AI use should be agreed with the client, and personal interview data must be handled in line with the GDPR.
Suggested dates
All dates are suggestions – your preferred date is always possible.
- Wed, 25 November 2026 – Thu, 26 November 2026 Online Request
- Wed, 9 December 2026 – Thu, 10 December 2026 Salzburg Request
- Thu, 17 December 2026 – Fri, 18 December 2026 Online Request
- Tue, 12 January 2027 – Wed, 13 January 2027 Bremen Request
- Thu, 28 January 2027 – Fri, 29 January 2027 Online Request
- Wed, 3 February 2027 – Thu, 4 February 2027 Augsburg Request
Frequently asked questions
Do I need programming skills to build AI agents?
No. The platforms used on the course rely on visual interfaces, plain-language instructions and ready-made connectors. You learn to specify agents precisely from a business perspective, connect tools and test workflows. Where deeper technical integration would be needed, you will know which requirements to put to your IT team.
Which platform will we use during the course?
The course is vendor-neutral and uses Microsoft Copilot Studio, custom GPTs and Claude as examples. You build your prototype on the platform that is available or planned in your organisation. The principles of workflow design, control and governance you learn carry over to other agent solutions as well.
How do I stop an agent from acting without control?
Through deliberate design: agents receive only the minimum permissions they need, critical actions such as sending, booking or deleting require human approval, and every step is logged. In addition, you define test cases and escalation rules. These are exactly the control mechanisms you develop for your own use case during the course.
Can I use client data in AI tools?
Only if the contract, NDA and your firm's policies permit it and the tool is covered contractually. It is often sensible to agree AI use with the client. The course shows how to work with anonymised data and set clear rules for project teams.
Will AI make consultants redundant?
Grunt work such as desk research or first slide drafts becomes cheaper. Judgement, industry experience, facilitation and implementation support remain in demand. Firms that use AI well deliver faster and can invest more time in real impact for clients. Value shifts towards advice quality and outcomes.
How much does “AI Agents for Consultants” 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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