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Automation, AI and the Future of Work: Why Human Judgment Will Become Increasingly Valuable

  • As artificial intelligence takes on increasingly complex tasks, what will remain uniquely human? Daniel Torres argues that the future belongs to the most adaptable professionals—not necessarily the most intelligent ones
Giancarlo Nicastro, CEO of SiiLA and host of the NXT Podcast, and Daniel Torres, Founder of Robotize
Giancarlo Nicastro, CEO of SiiLA and host of the NXT Podcast, and Daniel Torres, Founder of Robotize
By: SiiLA News
06/12/2026

Artificial intelligence is transforming the way companies operate, but its greatest impact may not lie in the technology itself. During his appearance on the NXT Podcast, Daniel Torres, Founder of Robotize, argued that automation represents an opportunity to bring work back to its most human form by eliminating repetitive, low-value tasks that still consume a significant portion of many professionals’ time.

According to Torres, it is still common to find entire teams dedicated to operational activities such as bank reconciliations, document verification, and manual data analysis. In many cases, these processes could already be automated using affordable solutions readily available in the market. In his view, the challenge lies less in the technology itself and more in resistance to change, lack of awareness, and the low prioritization of these initiatives within organizations.

Throughout the conversation, Torres emphasized that the advancement of AI will not make professionals obsolete but will require new skills. He believes that critical thinking, analytical ability, adaptability, communication, and emotional intelligence will be among the most valuable competencies in the years ahead.

“Technology will be available to everyone. The real differentiator will be the ability to understand context, ask better questions, and make sound judgments,” he said.

Another key topic discussed was the importance of data quality. Torres warned that many companies are accelerating AI initiatives before properly organizing their information. In practice, inconsistent databases, poorly structured processes, and disconnected data sources can undermine any artificial intelligence project.

“Automating a bad process only makes mistakes happen faster,” he summarized.

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