🏁 We're in the AI Race. But What's the Finish Line?

I wanted to write something about the latest advances in artificial intelligence, the billion-dollar investments, and everything happening with companies like OpenAI and Anthropic. But as I went through different news stories, I kept running into something that felt much more interesting.

In Chile we have startups growing thanks to AI, researchers building tools to help detect disease, and companies automating processes that once required full teams. At the same time, new forms of fraud appear, people worry about jobs that could disappear, and communities question the resources this technology consumes.

And something curious happens to me. On one hand, I am genuinely excited about what we are achieving. I use AI practically every day, I build things with it, and I keep being surprised by what it can do. But then I look at what is happening around us and I start having more questions than answers.

The opportunities are real. So are the changes.

Recently I was reading about Vambe, a Chilean startup that builds AI agents to serve customers and automate sales. Founded in 2023, it has already surpassed US$10 million in annual recurring revenue and works with more than 2,300 companies across Latin America.

What is interesting is that we are not talking about building the next ChatGPT. They are using the technology to solve a fairly everyday problem: answering customers, managing conversations, and selling. And they are doing quite well.

But I found another detail in an interview with its founders in Forbes Chile. One of their clients reduced its call center from 50 people to 10 after implementing the solution, according to Vambe’s CEO.

That is where something interesting appears. A Chilean company is growing, hiring professionals, and creating a business that would have been hard to imagine a few years ago. Meanwhile, some of its clients can do the same work with much smaller teams.

I am not saying that is necessarily bad. If a company can serve customers better, sell more, and reduce costs, it makes every bit of sense that it would want to do so. But we also cannot ignore what that means for the people whose jobs start to change or simply stop existing.

And this is probably only just beginning.

The same technology can solve a problem and create another

In medicine we are also seeing interesting advances. Researchers from CENIA and Universidad Católica developed an AI system in Chile that can analyze chest X-rays, identify anomalies, and generate draft reports for specialists to review. It still needs development and clinical validation, but think about the potential for hospitals where specialists are scarce and patients have to wait for a diagnosis.

Now look at cybersecurity. AI also lets us analyze threats, find vulnerabilities, and detect suspicious behavior with far greater capacity. But the people carrying out attacks are using similar tools.

A few weeks ago, Chile’s PDI warned about increasingly personalized fraud, deepfakes, and new attack techniques powered by AI. We used to receive phishing emails that were fairly easy to spot. Today it is possible to imitate voices, generate convincing videos, and prepare far more elaborate scams.

And that makes me think of something: we are building better tools to protect ourselves while also making it easier for others to develop more sophisticated attacks. That is not unique to AI. Technology has always had positive and negative uses. But the speed and ease with which these capabilities are reaching more people feel different to me.

Even the infrastructure has its contradictions

Another Chile story caught my attention. In Quilicura, neighbors have questioned the water consumption of data centers. According to information published by Google, its facility used roughly 458 million liters during 2024.

These are the installations that make much of the digital services we use possible. They also generate investment, connectivity, and jobs. Google, moreover, is funding water-efficiency projects in the Maipo basin, including precision irrigation initiatives that use AI.

So we have a technology that can help us use water better, while its infrastructure also needs to consume it. And that is not a small thing. The International Energy Agency estimates that global electricity consumption by data centers could nearly double by 2030.

I think these are exactly the topics we should be looking at more closely. It is not enough to announce investments or show off new capabilities. It also matters where the infrastructure is built, what resources it needs, and how it affects communities.

And meanwhile, we keep investing billions

This week Anthropic formally filed its documentation for a possible IPO. OpenAI had also started that process, though it ruled out listing during 2026.

The figures moving around these companies are enormous. And behind them come investments in chips, energy, data centers, and new platforms. Governments do not want to fall behind either. The United States, China, and Europe are trying to secure their own technological capabilities, infrastructure, and access to strategic resources.

That makes sense. Nobody wants to depend completely on others when a technology starts to matter for a large part of their economy. But there is still something we do not know.

How many of these investments will end up being profitable? Who will capture most of the business? And what will happen to the countries and companies that cannot move at the same pace?

I think we may be facing a real technological revolution and, at the same time, a market that may be overstating some expectations. One does not contradict the other.

What makes me think most is what comes next

In my case, AI has allowed me to build projects like NeuraPRO and ViaMind Radar, experiment with new ideas, and move much faster than I could have a few years ago. That already changed the way I work.

But I have also learned that building something is only one part of the problem. Afterward you have to get users, control costs, keep the systems running, and make sure someone actually finds value in what you made.

That is why I find it hard to believe either the speeches that promise AI will solve practically everything or those that claim we are headed straight for catastrophe. Reality will probably be far more complicated.

And if I think a little further ahead, especially about the world our children will live in, the questions get even bigger. What should they learn today if machines will be able to perform many of the tasks we spent years studying to master? How will an economy work where some companies can produce far more with far fewer people? And if we manage to raise productivity enormously, will that mean we all live better?

Not necessarily. At least, not automatically.

What I am clear about is that this race has already started, and I do not think it makes much sense to stay on the sidelines watching. I want to keep learning, trying tools, building, and taking the opportunities that appear.

But I also believe it is worth looking a little beyond the next launch, the billion-dollar valuations, and who has the smartest model. Because we could end up building extraordinary technology without being very clear about how we want to use it as a society.

Maybe we still do not know what the finish line of this race is. But it would be good to start discussing it while we keep moving forward, not after we have already arrived.

Related reading:

• How Will We Know We Still Have Control?
• The New Technology Race
• Silent Labor Crisis

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✍️ Claudio from ViaMind

“Dare to imagine, create and transform.”

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