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Case study · AI Adoption

Tax Reform Delivery Model

A delivery model that made AI adoption repeatable under pressure.

Scalable AI Adoption

Context & Constraints

Brazil’s Tax Reform represents one of the most complex regulatory transformations in history, creating an exponential increase in client demand for KPMG.

The existing delivery approach was not designed to scale under this pressure. Teams needed to deliver complex projects with efficiency and consistency, while effectively adopting AI as an accelerator, not a parallel experiment.

Architecture

Redesigned the Service Delivery Model (SDM) into six structured phases (Business Context, Kick-off, Pre-Workshop, Workshops, Impact Matrix, Action Plan). To operationalize this, I created role-based AI accelerators (personas, prompt banks, templates) embedded directly into consultants' workflows for each phase.

My Role

Redesigned the end-to-end Service Delivery Model. Translated consulting methodology into structured, AI-enabled workflows. Developed AI accelerators and authored practical execution manuals.

Results & Validation

6-phase AI-enabled delivery lifecycle

Role-based AI personas (e.g., Impact Analyst)

Standardized prompt banks & execution templates

Drove 30-80% efficiency gains in specific workflow tasks. AI alone does not solve scale; process does. By embedding AI into a rigid 6-phase delivery model, we turned a regulatory crisis into a standardized, repeatable operation.

Stack

Service DesignAI PersonasOps

Building something where reliability matters?

I design, ship and operate systems like this one.

Let's talk

Building GenAI where reliability matters? Let's talk.

leonardo@leonardosa.pro

Madrid, Spain · from August 2026 · English / French / Portuguese / Spanish

© 2026 Leonardo Costa de Sá