Enterprise
AI strategy and operating model
Connect executive priorities, delivery capacity, data readiness, controls, and business ownership before scaling assistants, agents, or automation.
Enterprise AI
AI adoption where operating models, data quality, controls, and accountability matter.
Enterprise AI creates value when it is integrated into real processes, governed responsibly, and measured against business outcomes rather than tool usage alone.
Practice areas
Domain
Finance, accounting, tax and SAP
Design AI around concrete enterprise workflows: master data, approvals, reconciliations, reporting, tax rules, audit trails, and SAP integration points.
Governance
Responsible and privacy-aware adoption
Treat model risk, data sensitivity, access design, human oversight, and responsible governance as part of implementation, not as afterthoughts.
Selected professional highlights
Leadership
Director of Data & AI at NTT DATA Business Solutions
Director of Data & AI at NTT DATA Business Solutions. Leads enterprise AI strategy and governance, a current team of 15, and the Guepardo AI portfolio; represents Brazil in the Global Innovation Team across 60+ countries.
AI governance
Enterprise AI strategy and responsible adoption
Public and executive perspective on moving AI initiatives from experimentation to governed portfolios with owners, controls, metrics, and adoption plans.
Business systems
Finance, tax and SAP transformation
Domain focus on intelligent systems for fiscal, accounting, finance, and SAP-enabled enterprise processes where compliance and reliability matter.