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 an international treaty that proposes a structural response to the challenges of the digital age, establishing common principles that seek to protect people without hindering technological innovation. Understanding its scope is key to anticipating the direction data regulation will take in the coming years.
We present a comprehensive look at the characteristics of a modern AI-powered pipeline, the capabilities it must possess, and the challenges companies face when implementing it. We also analyze how to achieve the right balance between automation and human oversight.
We share a practical look at how to use the 7Rs framework to streamline your portfolio and build a modernization roadmap that combines speed with control.
We explore what data maturity really means from a business perspective, how to identify an organization's current level of data maturity, and why advancing AI without a solid foundation can generate more risks than benefits.
We analyze what data stewardship means and entails, and the challenges it presents for individuals and organizations. We also address the role of the data steward and the disruption that artificial intelligence introduces to data governance processes.
In this article we organize the discussion around three key axes: the different possible modernization routes, the main trade-offs that condition decision-making, and the specific criteria to evaluate each scenario, with metrics and a roadmap adjusted to the maturity level of each organization.
