AI Consulting & Corporate Strategy
An educational, governance-first guide for management consultants and in-house strategy teams. GenAI is treated as disciplined support for structured thinking (issue trees, options, scenarios, executive drafts) — not a substitute for professional judgment. As capability increases across the maturity ladder, risk increases too, and controls must scale to keep outputs defensible, reviewable, and fit for executive decision-making.
Download and Run
The book PDF is published as a versioned GitHub Release asset. The companion notebooks live in this repository and open directly in Google Colab.
Chapter Notebooks (Colab)
Each notebook is executable, auditable, and classroom-ready. Labs produce structured outputs and governance artifacts (run manifest, prompt log, risk log, deliverables bundle) so results are reviewable rather than ephemeral.
Chapter 1 — Level 1 (Chatbots)
Drafting: emails, memos, meeting notes, and executive-friendly prose with governance boundaries.
Chapter 2 — Level 2 (Reasoners)
Issue trees, option sets, trade-offs, assumptions registers, and questions-to-verify lists.
Chapter 3 — Level 3 (Agents)
Supervised multi-step workflows: intake → structure → draft → QA → approval → archive bundle.
Chapter 4 — Level 4 (Innovators)
Internal IP: playbooks, templates, evaluation tests, and controlled rollouts for consulting work.
Chapter 5 — Level 5 (Organizations)
Operating model simulation: governance, ownership, evidence, QA gates, and supervision-ready artifacts.
The Five-Level Maturity Ladder
The book’s organizing spine is a progression from individual drafting assistance to fully governed, organization-grade operations. The point is not “more AI.” The point is usefulness that survives partner review, client scrutiny, and audit/reconstruction.
- Level 1 — Chatbots: supervised drafting of memos, emails, meeting notes, and executive updates.
- Level 2 — Reasoners: explicit reasoning structures: issue trees, alternatives, trade-offs, assumptions, and verification planning.
- Level 3 — Agents: multi-step workflows with human checkpoints, role separation, and traceable logs.
- Level 4 — Innovators: reusable consulting assets (templates, playbooks, evaluation suites) with controlled releases and regression tests.
- Level 5 — Organizations: operating model + governance: intake, data controls, QA, approvals, recordkeeping, and audit-ready evidence bundles.
Recurring Mini-Cases (Used in Every Chapter)
The ladder is taught through recurring strategy cases so readers can isolate what changes when AI capability increases: the structure improves, the risk scales, and governance must become more explicit.
Market Entry
Market map, segmentation hypotheses, competitor scan framing, and a defensible entry options set.
Cost Transformation
Value-driver tree, initiative pipeline, assumptions register, and risks-to-controls mapping.
Capital Allocation
Options framing (invest / divest / return), scenario comparisons, and decision-ready narratives.
Operating Model Redesign
Target operating model, role clarity, process boundaries, and implementation sequencing with controls.
Independent AI Evaluation (Gemini)
The evaluation below is included as an independent classroom-focused assessment of the book as a teachable consulting curriculum. It is not a factual validation of content and does not replace human review.
This book is an exceptional resource for MBA and MFIN students because it bridges the gap between high-level strategy and technical execution with remarkable precision. By structuring the curriculum around a "maturity ladder"—progressing from simple drafting (Level 1) to complex organizational operating models (Level 5)—it ensures students build durable skills that do not rely on the fleeting "magic" of specific models. The integration of companion Colab notebooks for every chapter ensures that students are not merely reading about concepts like "structured reasoning" or "verification plans," but are actively implementing them to produce auditable artifacts (e.g., Draft Bundles, Reasoning Bundles). This "operating manual" approach allows students to transition from novices to defensible practitioners capable of managing AI risk within a month.
The book’s defining strength is its treatment of governance, which it correctly frames not as a compliance afterthought but as the central "operating system" of professional advisory work. Instead of teaching fragile prompt tricks, the author instills a "governance-first" posture where every output is treated as a draft until verified, facts are strictly separated from assumptions, and accountability remains human. This focus protects the material from obsolescence; while model capabilities may change, the professional discipline of separating "inference from evidence" and maintaining a "chain of reasoning" remains constant. For students entering high-stakes fields, this book provides a robust mental model for using AI to accelerate labor without eroding the trust that defines their future professions.
Note: This is an opinionated evaluation produced by an external model (Gemini) for classroom discussion. Treat it as a perspective, not as evidence of correctness. All outputs remain subject to human verification and review.
License and Disclaimers
Educational disclaimer: This material is provided for educational purposes only. It does not constitute consulting, legal, accounting, tax, or investment advice. Human professional judgment and review are required for any reliance-bearing use.
Confidentiality and client data hygiene: Do not paste confidential client information into external model prompts. Use redaction/anonymization and “minimum necessary” inputs by default. Document any exception and follow your firm’s policies.
Facts are not assumptions: Outputs must clearly separate facts provided by the user from assumptions and open questions. Treat all model-generated content as Not verified until validated by a human.
No fabricated sources: The workflow assumes zero tolerance for invented benchmarks, citations, customers, competitors, or “precise” numbers without provenance. When evidence is missing, the correct output is an explicit verification task list.
Repository license: See the repository’s LICENSE file for terms.