According to Mr. Beacraft, who spoke at the Anbima Summit in São Paulo on Thursday (26), the professionals most vulnerable to being displaced by the new technology are those in middle management roles with a complacent profile. These individuals will be challenged to step up, without necessarily receiving a corresponding promotion, by demonstrating strategic vision, the ability to reposition products and businesses, and the capacity to lead hybrid teams composed of humans and machines.

“Everyone will have to take a step forward. Junior professionals will have the tools to perform better. What AI does is abstract and removes the need for years of discipline, exposure, experience, and knowledge in a specific area to perform proficiently,” Mr. Beacraft told Valor in an interview.

In the same vein, teams with a limited scope will be able to expand their capabilities into adjacent areas that share a similar knowledge base. A static designer, for example, will be able to create video animations. An advertising photo may be the starting point for a film, and an architectural plan can be transformed into a three-dimensional model.

“Your financial analysts will be able to think about investment strategy. It’s the next step, but also the ability to respond to the needs of the moment. I can do something from a different department than mine when that challenge arises, rather than waiting until that talent becomes available.”

According to Mr. Beacraft, this type of functional overlap will have a significant impact on service chains, potentially leading to the elimination of entire functions and operational teams. On the other hand, it will extend what he calls the “creative flow,” enabling teams to remain productive for longer, take ownership of products, and drive significant innovation.

He notes that investment boutiques with lean teams will be able to incorporate decades of data into their analyses and accurately forecast the price behavior of commodities and financial assets—a task that a human analyst alone could never accomplish within a reasonable timeframe.

“When all this data truly comes together, it will unlock capabilities on a scale we’ve never seen before, allowing small funds to operate like much larger rivals—accessing resources they wouldn’t otherwise have—to create even more innovative and cost-effective products,” he said.

According to the expert, the same transformation will also extend to other financial services, which will increasingly adopt the digitization—or “tokenization”—of assets and processes across insurance, money transfers, payments, and credit. These changes will occur on a larger scale and at a lower cost than currently seen. “We’ll be able to factor in even more variables to make smarter decisions. Financial services and lending will become far more dynamic than in the past,” he noted.

For Mr. Beacraft, both intellectual and creative work, as well as operational capacity, still have vast potential for expansion. However, uniquely human sensations and abilities, whether emotional or physical, remain irreplaceable by machines.

“There are physical sensations like tension, anxiety, and relaxation that can’t be converted into data that machines can process. When I walk into a room, I’m using my spatial intelligence to assess what’s happening in that environment. My emotional intelligence kicks in when I’m speaking and navigating the nuances of human interaction,” he explained.

“We’re replicating cognitive intelligence. Machines will surpass us in this area because they process information on a much larger scale. But emotions and physical sensations cannot be replicated.”

In his view, the spread of generative artificial intelligence will unfold in successive waves, each targeting different audiences and business sizes. Today, only the so-called “big techs” have access to the highest-performing models with the fewest errors, referred to as “hallucinations,” the misleading results AI can produce from faulty assumptions. That advantage, however, is unlikely to last. Open-source software and reverse engineering will soon enable startups and specialized providers to collaboratively adopt—and even improve—this technology.

“Right now, much of the conversation is about making things easier, faster, and cheaper. It’s basically the same thing we’ve always done, just more efficiently. But that’s a narrow mindset. Every technological revolution has delivered real value when it moved beyond what was previously possible. And we’re still just at the beginning of this one.”