Accelerating AI Adoption in Brazil
The Learning Organization: How to Accelerate AI Adoption in Brazil
Artificial intelligence (AI) is evolving at a breakneck speed, transforming the way we work and live. However, for most organizations, there is a growing gap between AI’s potential and its actual implementation. A recent McKinsey study revealed that although nine out of ten employees already use generative AI in their tasks, only 13% of organizations consider themselves pioneers in the formal adoption of these tools [1].
In Brazil, the outlook is promising but challenging. The country leads AI adoption in Latin America, with 40% of companies already using the technology, according to a Strand Partners study for AWS [2]. The Brazilian government is also investing heavily, with R$ 23 billion planned by 2028 to boost digital transformation [3]. Despite this progress, many companies still face barriers to scaling innovation and unlocking AI’s full value.
This article explores how Brazilian companies can become “learning organizations” to accelerate AI adoption, overcome organizational blockers, and turn innovative ideas into tangible results. We will cover four essential mindsets and practices that can help your company navigate this new era of artificial intelligence.
1. Cultivate What Is Already Growing: The Gardener Mindset
Psychologist Alison Gopnik, in her book “The Gardener and the Carpenter,” argues that parents should allow children to develop according to their natural tendencies rather than follow a predetermined plan. This “gardener mindset” is equally relevant for organizational leaders: instead of imposing a top-down transformation, they should nurture the growth that is already happening.
In many companies, AI innovation is already sprouting within specific teams and departments. These are the “AI natives,” often younger employees, who are already using AI tools to draft emails, write code, and analyze data. Instead of suppressing these initiatives out of fear of lack of governance or costs, leaders should observe them, understand what makes them effective, and then help scale them.
A practical example is that of an Asian financial services company that discovered its teams were informally using AI to optimize application development. Management, instead of banning it, embraced innovation and created a common data layer that automated time-consuming steps like data labeling, cutting AI application development time in half. In Brazil, where 53% of startups already incorporate AI into their business models [4], this approach is even more crucial to remain competitive.
The carpenter mindset, which meticulously plans every detail of technological transformation, cannot keep up with AI’s rapid pace. Leaders who try to specify exactly how AI should be implemented across the organization risk building yesterday’s solutions for tomorrow’s problems. True transformation emerges from the bottom up, through experiments and solutions created by those on the front lines.