There is one figure that should be on the agenda of every executive committee in Latin America: by 2030, artificial intelligence and automation could generate nearly US$450 billion in annual economic value across the region, according to the McKinsey Global Institute.
But many of the companies investing to capture that value could be leaving money — and trust — on the table.
The problem?
It’s not that they lack technology. It’s that they are not clearly explaining how that technology changes things for their customers, their teams, and their broader environment.
The challenge is getting people to understand and trust it
The report Agents, robots, and us: How AI reshapes work and skills in Latin America, published by McKinsey in July 2026, shows that AI adoption in Latin America is still below the levels seen in the United States and Europe: 14% compared with 27% and 25%, respectively.
The technology already exists. So, what is holding adoption back? To a large extent, it is the difficulty of understanding what it is for, what it changes, and what it means for each person.
And this affects three key groups.
1. Customers: They don’t want a technology lesson
Demand for AI fluency — the ability to use and manage these tools without needing to program them — has grown 11-fold in two years across the region.
Interest is growing, but many brands are still explaining AI through the lens of technology: they talk about models, features, and capabilities. Customers want to know something much simpler: What’s the benefit for me?
Does it save me time? Does it make a process easier? Does it give me access to a better service? What changes compared with what I already had?
AI communication needs to answer those questions. Less technology for technology’s sake. More tangible benefits.
2. Teams: If you don’t explain the change, someone else will
McKinsey estimates that 36% of employment in the region consists of people-centered jobs, while another 28% corresponds to hybrid roles in which people will work alongside AI.
That means that, for many workers, the scenario will not be “AI or people.” It will be people + AI.
But for that to work, companies need to explain what will change in day-to-day work: which tasks will be automated, what new responsibilities will emerge, and what skills teams will need to develop.
When that information doesn’t reach employees, questions arise:
Is my job at risk? What is expected of me now? Will I need to learn something new?
When a company does not explain the change, doubts, rumors, and uncertainty emerge.
3. Public opinion and regulators: Don’t wait for others to define your position
The conversation around responsible AI use is already taking place among companies, governments, regulators, the media, and consumers.
And here, many brands are arriving late. They wait for a new regulation, a controversial news story, or a crisis before explaining how they use AI and what limits they have.
The problem is that, by then, the conversation has already started without them. Companies need to define in advance what principles guide their use of AI, how they protect data, which decisions still depend on people, and how they manage risks.
Three audiences, the same mistake
Customers, teams, and the public have different questions.
But companies often make the same mistake with all of them: they talk about AI based on what the technology does, instead of explaining what it changes for people.
Buying a tool does not guarantee that someone will want to use it. Implementing it does not mean that teams know how to work with it. And having an AI policy does not mean that the public will trust it.
Technology needs communication to become adoption.
How do we approach this at AXON?
Our starting point is simple: every audience needs to know what changes for them.
That is why we work across three fronts:
- For customers: turn AI capabilities into benefits that are easy to understand.
- For teams: explain which tasks will change, what new skills they will need, and how AI will be integrated into their work.
- For the public: define and communicate a clear position on how AI is used and what measures are in place to ensure it is used responsibly.
Because the companies that capture that US$450 billion will be the ones that manage to help their customers understand its value, enable their teams to know how to use it, and build trust in how the company is using it.
That is AXON’s work: making technological change understandable, adoptable, and trusted.