AI for Consulting Firms: 15 Practical Use Cases, Risks, and Controls
Fifteen AI use cases that hold up in a consulting firm, ranked by value and risk, with the control each one needs and the ones I would not start with.
Practical guides for consulting, banking, M&A, insurance, and regulated industries. Learn how to automate presentation work while protecting confidential data, approved content, brand standards, and human review.
6 articles · Consulting
Fifteen AI use cases that hold up in a consulting firm, ranked by value and risk, with the control each one needs and the ones I would not start with.
The data model behind a credentials library that AI can safely retrieve from: CV fields, reference fields, permission levels, tagging, review cycles and GDPR duties.
Forty checks across argument, evidence, numbers, confidentiality, brand and the final file, ordered the way an experienced reviewer actually works through a deck.
Most slide libraries fail because nobody owns them. Here is the taxonomy, ownership model, review cycle and retrieval design that makes reuse actually happen.
A step by step workflow from RFP receipt to submitted proposal deck: compliance matrix, bid thesis, controlled retrieval, native slides and three separate reviews.
What I learned building proposals in consulting, and the workflow from RFP to finished deck I would use today: approved evidence, bounded AI, partners still accountable.
Authors
Our founders write from first-hand experience: Florian on consulting and agentic AI, Maximilian on data protection and enterprise operations, and Robin on AI architecture and security. We share this expertise to help teams build safer, faster, and more professional presentation workflows. Regulatory content is grounded in primary sources and receives specialist review where required.