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Rodrigo Krüger

Work

What I lead, build and deliver.

Enterprise AI work is easier to judge from what it produced than from how it is described. This page sets out the portfolios and programs I am responsible for, what each one is, and which part of it is mine.

Selected work

Product portfolio

Guepardo AI

Guepardo is an established enterprise platform for Brazilian tax and fiscal operations, built on SAP and used by more than 550 customers. It supports companies whose tax-related operations represent approximately 10% of Brazil's GDP.

My responsibility

I lead Guepardo AI: the strategy, roadmap and evolution of the platform's AI use cases. The platform itself predates my involvement; my responsibility is its artificial intelligence portfolio.

Scope

  • Predictive analytics for fiscal and financial operations
  • Deep learning applied to document and transaction-heavy processes
  • Generative AI embedded in existing business workflows
  • AI agents that operate against real system data and controls

Leadership

Enterprise AI portfolio and operating model

AI initiatives inside large organizations tend to accumulate as disconnected pilots, each with its own tooling, data access and definition of success.

My responsibility

I lead the Data & AI practice at NTT DATA Business Solutions, where the work is to turn that scatter into a governed portfolio: named owners, controls, adoption plans and metrics that hold up in a management review.

Scope

  • AI strategy tied to business priorities rather than tool availability
  • Data readiness, access design and model risk as delivery prerequisites
  • Human oversight and decision rights defined before deployment
  • Value measured against operational outcomes, not usage counts

Global

Global Innovation Team

NTT DATA Business Solutions operates across more than 60 countries, and innovation practice varies widely between them.

My responsibility

I represent the Brazilian operation in the Global Innovation Team, contributing to how AI capability is evaluated, shared and adopted across the group.

Scope

  • Cross-country exchange of AI use cases and delivery patterns
  • Perspective from a market with unusually complex tax and fiscal requirements

Execution

Delivery of large technical programs

Before leading Data & AI, my work centred on delivery: keeping large, mission-critical enterprise programs running to plan, to budget and to specification.

My responsibility

Before Data & AI, enterprise delivery was my work: accountable for scope, budget, quality and operational continuity. That experience is the reason I treat AI as an execution problem as much as a modelling one.

Scope

  • Program and delivery management in complex enterprise environments
  • Technical leadership across architecture, engineering and operations
  • Mission-critical systems where downtime and error carry real cost

Governance

Governance, privacy and responsible adoption

The domains I work in — finance, accounting, tax — are regulated, audited and unforgiving of unexplained outputs.

My responsibility

I treat model risk, data sensitivity, access design and human oversight as part of the implementation rather than as a review step at the end. This is also where my professional and academic work meet most directly.

Scope

  • Privacy and data-protection constraints designed into AI systems
  • Traceability and auditability of AI-supported decisions
  • Public commentary on responsible AI adoption and its limits