{"id":28499,"date":"2025-11-05T09:00:00","date_gmt":"2025-11-05T08:00:00","guid":{"rendered":"https:\/\/itpatagonia.com\/?p=28499"},"modified":"2026-04-13T22:13:05","modified_gmt":"2026-04-13T20:13:05","slug":"una-estrategia-ai-first","status":"publish","type":"post","link":"https:\/\/itpatagonia.com\/en\/blog\/una-estrategia-ai-first","title":{"rendered":"Data & AI: Consolidating an AI-first strategy"},"content":{"rendered":"

Philosophy AI-first<\/em> It argues that artificial intelligence must cease to be an accessory resource for become the strategic core of organizations<\/strong>. <\/p>\n\n\n\n

This implies that every decision, process, and experience of people is influenced by the use of data and intelligent algorithms. <\/p>\n\n\n\n

In a context where competitiveness depends on the ability to anticipate and adapt, AI-first<\/em> It's not a fad, but a path towards corporate sustainability<\/strong>.<\/p>\n\n\n\n

In this article we ask for help from Daniel Menal<\/a>, Head of Data & AI at IT Patagonia to analyze how to scale from isolated artificial intelligence projects to a culture AI-first<\/em>, the main challenges and aspects to consider, and the role of leadership in fostering cultural transformation.<\/p>\n\n\n\n

What does adopting a strategy entail today? <\/strong>AI-first<\/em><\/strong><\/h2>\n\n\n\n

As Daniel explained to us, this philosophy has multiple meanings. <\/p>\n\n\n\n

Depending on the level of maturity of the organization, AI-first<\/em> It can be represented as the actions taken internally to boost the business or reduce operating costs. But there are cases where it is strongly linked to how the company interacts with its end customers, especially in sales channels.<\/p>\n\n\n\n

Adopt an approach AI-first<\/em> means rethinking the way businesses are conceived<\/strong>. <\/p>\n\n\n\n

It's not just about using chatbots or recommendation systems. The key lies in integrate artificial intelligence into the very architecture of the organization<\/a>. From how products and services are designed, to how internal resources and the commercial area are managed.<\/p>\n\n\n\n

Today, AI-first<\/em> This involves having a robust, flexible, and secure data infrastructure capable of centralizing dispersed information and ensuring its quality. <\/p>\n\n\n\n

It also demands incorporate artificial intelligence across the board<\/a>, so that marketing, logistics, finance, or human resources can use AI tools such as strategic enablers<\/strong>. <\/p>\n\n\n\n

All of this is supported by an organizational culture that values data and by committed leadership that guides change.<\/p>\n\n\n\n

Be AI-first<\/em> It doesn't mean implementing isolated projects. It involves redesigning how business operations are conceived and executed. It consists of a shift in mindset that distinguishes those who innovate from those who merely experiment.<\/p>\n\n\n\n

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An AI-first approach allows you to transform the way an organization thinks, decides, and operates.<\/figcaption><\/figure>\n\n\n\n
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5 things to consider when implementing an approach <\/strong>AI-first<\/em><\/strong><\/h2>\n\n\n\n

Implement an approach AI-first<\/em> It's not just about deploying artificial intelligence solutions in isolation, but about transform the way the organization thinks, decides and operates<\/strong>. <\/p>\n\n\n\n

For artificial intelligence to become a true engine of competitiveness and not just a passing experiment, it is necessary to address certain key factors that ensure its effective and sustainable adoption. <\/p>\n\n\n\n

Below, we present five key aspects for the transition to a model AI-first<\/em> be successful.<\/p>\n\n\n\n

1. Robust, flexible, and secure data infrastructure<\/strong><\/p>\n\n\n\n

To scale with AI, it is essential to have access to clean, structured and unstructured data, with clear governance and security policies. <\/p>\n\n\n\n

Companies that do so, They report improved metrics for immediate access to internal data<\/a>, greater regulatory compliance and lower failure rate in artificial intelligence initiatives. <\/p>\n\n\n\n

2. Cross-cutting integration of AI in all areas<\/strong><\/p>\n\n\n\n

Instead of having isolated artificial intelligence projects (chatbots, prediction, partial automation), adopt an approach AI-first<\/em> This means that all areas of an organization use this technology as a strategic enabler to:<\/p>\n\n\n\n