AI in consulting: from workflows to value creation

Basics of artificial intelligence (AI)

• Compact: What modern AI can (and cannot) do – from large language models to retrieval (RAG), vector search, and tools.
• Overview of the most important consulting tools (ChatGPT, Copilot, Claude, etc.) and typical application limitations (hallucination, data protection, bias).

Use of AI in the consulting project

• AI agents & automation: Model task chains (Plan → Do → Check), orchestrate agents (e.g., research → synthesis → draft → quality assurance), standardize handovers/prompts.
• Build your own chatbots: Goal definition, knowledge base (RAG), roles/personas, guardrails & logging; no/low-code paths for MVPs.
• Decision templates & forecasts: From expert opinion to augmented decision making—structured analyses, sensitivities, scenarios, and risk positions.
• Automate reports, proposals, and presentations: templates, briefing prompts, fact checks, source references, and CI-compliant output.
• Governance & legal issues in practice: EU AI Regulation in everyday consulting, data classification, confidentiality, tool registration, and customer approval processes.

Case studies and use cases

• End-to-end demo: From customer briefing to final document in 60–90 minutes.
• Benchmarks and best practices from consulting and large companies—transferable to your projects.