DEI
At IT Patagonia, diversity is lived and built as a team.
We analyze why diverse work teams are not built with speeches, but with strategic decisions that impact culture and business.
Insights
IT training
Programming languages in 2026: which ones will enable you to work in technology
Discover which programming languages are worth learning in 2026, which are the most widely used, and how AI is transforming the way we program. A clear guide for those looking to start or advance in the IT industry.
AI
AI-powered data models: architecture and key decisions for generating sustainable value
How to go from data to decisions with AI: minimal architecture, governance, evaluation and steps to implement business-aligned models.
Great Place to Work
5 keys to retaining talent in the IT industry
In this article we analyze the fierce competition for talent facing the IT industry and share 5 keys to retaining technology teams: authentic value proposition, professional development, organizational culture and empathetic leadership, flexibility and well-being at work, and genuine recognition.
cyberattacks
Incident response: how to prepare to respond effectively to cybersecurity incidents
We analyze how a robust incident response plan enables organizations to react to cyberattacks quickly and effectively, reduce costs, protect sensitive data, and preserve the trust of customers and partners.
IA-first
AI-first strategy: how to build an organization-wide management and adoption model
Why is AI-first a viable operating model and a path to business sustainability? We analyze its challenges, potential risks, roles involved, and a roadmap for moving from isolated initiatives to scale.
We analyze what a turnkey modernization project entails, why the first months of assessment are crucial, and how responsibilities are distributed between the organization and its technology partner.
What changes when a model must answer to a regulator? What kind of metrics can be used to assess fairness and potential biases? What information should be prepared before an audit?
We explore why there can be significant differences between proposals that address the same need, what aspects are not shown in the price and implementation timeframe, what the main selection criteria are, and why choosing a technology partner involves looking beyond the immediate project.
Many organizations invest in ambitious governance frameworks that end up being difficult to implement. We propose an approach that moves from concept to implementation.
We present the results of the Data Governance Maturity Study and identify the gaps that most impact the ability to scale AI, comply with regulations, and reduce operational risks.
In a context where data circulates between multiple systems, teams and third parties, we propose a practical approach on how to move from declaration to control, and from control to evidence.
