What Should Office Workers Prepare for in 2026 [Reading Science]

The Divide in Labor Created by AI Literacy and Emotional Literacy

The core keyword in the 2026 labor market is "the ability to collaborate with AI." As companies fully integrate generative AI into every stage of their work processes, the human role is shifting from merely executing tasks to directing and calibrating AI.

Experts believe that in the age of AI, it is not entire professions that disappear, but rather the individual work units that make up those professions. Kim Donggyu, a research fellow at the Future Occupation Research Team of the Korea Employment Information Service, explains, "Repetitive and rule-based tasks are quickly being taken over by AI, leaving humans with roles that require judgment and adjustment."

In the 2026 labor market, the ability to collaborate in utilizing and controlling generative AI is emerging as a core human competitive advantage. Photo by Pixabay

In this environment, the core competencies that office workers must possess can be summarized as two types of literacy: AI literacy, which involves utilizing and controlling AI, and emotional literacy, which fills in the human context that AI misses. AI literacy is not just about using tools, but about the judgment skills needed to understand, verify, and responsibly apply AI-generated results. When these two abilities are combined, an individual's labor is transformed from something that can be replaced to "advanced labor."

The Essence of AI Literacy: Not Just 'How to Use' but 'Design and Verification'

In 2026, AI literacy goes beyond the skills of asking questions or giving commands. The key is the ability to design the work structure by setting work goals, constraints, and criteria for judgment. Even when using the same tool, results differ not because of functionality, but because of differences in design and verification levels.

Seong Nakho, Head of Technology at Naver Cloud, explains, "AI is evolving beyond a simple tool to a stage where it can set its own plans when given a goal." He adds that, unlike in the past when detailed instructions were necessary, the structure of work is changing to focus on providing goals and context. What matters most is not the quantity of commands, but the context. Only when the background and criteria for judgment are provided together can AI-generated results be effectively used in real work.

As the use of AI becomes more widespread, verification skills become even more important. It is necessary to develop the habit of not accepting AI-generated results at face value, but instead checking for errors, leaps in logic, and biases. Seong emphasizes, "Even if the error rate decreases, AI cannot take ultimate responsibility for the results," highlighting that inspection and judgment will remain the domain of humans.

Emotional literacy is also crucial. As AI takes on more efficiency-driven tasks, human value will be revealed in the ability to read emotions, relationships, and context. Sensing nuances in customer complaints, mediating conflicts within organizations, and arbitrating interests are still uniquely human responsibilities.

Research fellow Kim Donggyu points out, "If AI adoption reduces new hiring, young people may lose opportunities to gain experience," stressing the need for policy responses such as expanding internships and supporting youth employment. However, he also notes that as repetitive office work is restructured first, the value of field-based blue-collar jobs may be highlighted once again.

2026 marks a period when the boundaries between AI and humans become increasingly blurred. AI literacy and emotional literacy are not just technical skills, but essential survival competencies for enduring and growing over the next decade.