As we stand at a major inflection point, where artificial intelligence(AI) is transforming industries across the board, intuition-based decisions are rapidly being replaced by “intelligent decision-making” based on data analysis. Amid this shift, “Data Literacy” is emerging as a core competitive advantage that goes beyond basic interpretation—it involves discerning the authenticity of information and linking insights to business value and innovation.
However, using data without such discernment can be risky. As data volumes increase, their ability to assess its quality and statistical context becomes increasingly critical. The classic computer science adage, “Garbage In, Garbage Out(GIGO),” remains valid in the AI era, and biased data can spread errors through automated systems, leading to significant losses. In particular, statistical illusions such as “Simpson’s Paradox”—where the overall trend of the data is reversed in a subgroup—lead to serious misjudgments when analysts fail to accurately grasp the context of the data and identify confounding variables. Ultimately, what matters most in the data-driven era is not technical processing skill, but the insight to verify reliability and interpret data critically.
For those with these capabilities, AI becomes a “cybernetic teammate” rather than a competitor. According to research from Harvard University, individuals who work closely with AI significantly outperform teams working without AI, increasing work efficiency by more than 16% while also gaining greater immersion in their work and reduced stress. In particular, AI bridges knowledge gaps within organizations and helps integrate different fields of expertise, maximizing the likelihood of deriving creative and innovative solutions. When we recognize it not as a mere tool but as a partner that extends human intelligence, we can experience a new dimension of productivity.
Today’s industry strongly demands “problem-solving talent” who can go beyond mere technical knowledge to practically solve problems using AI and data. The core talent profile companies seek is not simply a technician who handles the latest algorithms, but a professional who can connect technical solutions to the business context, translating them into concrete business outcomes and value creation. In particular, the ability to bridge the gap between technology and business through collaborative communication is a differentiating factor that plays a key role in a company’s success. Therefore, it is crucial to gain practical experience in real-world data environments, define problems in practical terms, and develop the practical skills to derive solutions.
Soongsilians must focus on strengthening practical, hands-on skills. First, going beyond basic data extraction and processing languages, they must acquire automation skills to enhance efficiency by leveraging the analytical tools and automation platforms increasingly adopted in corporate settings. Furthermore they must continuously hone their data storytelling and persuasive presentation skills, turning findings into business narratives through data visualization to support decision-making. Finally, when their expertise is combined with the ability to critically evaluate the purpose of ethical biases, Soongsilians will develop a unique and irreplaceable competitive edge. In conclusion, the ability to read data is the ability to read the world. Only those who can utilize data and AI while thinking critically about data will become the true leaders of the future.
Kim Hong-jin
[Professor, School of Business Administration]
