Advances in AI and Machine Learning, Making Decisions Possible with Data

Recently, major local governments have been actively attracting data centers. Thus, it is believed that the flood of associated businesses brought in by the data centers will result in job creation and economic development in the area.
This means that “companies secure competitiveness and achieve growth by converting data into economic value,” according to the economic model’s guiding concept. Thus, it makes sense to discuss the “data economy” when discussing “AI transformation.” Massive data processing is not practically impossible, but it is too costly and time-consuming for humans. However, Professor Lee clarified that AI develops its intelligence by learning information just like humans, enabling AI to emulate human perception, reasoning, and learning skills.
"Data includes information about market shifts, consumer behavior, technology trends, and other topics. Data analysis and forecasting have been significantly enhanced by advances in AI and machine learning, and companies are using data to inform strategic choices to obtain a competitive edge. Companies may swiftly and precisely extract valuable insights from their data, which aids in decision-making.

AI’s Data Analysis Boosts Industry and Corporate Competitiveness

“Macroeconomic and monetary economics,” “international economics,” “applied time series econometrics,” and “machine learning,” a sub-branch of AI, are among Professor Lee’s areas of interest. Among these, machine learning helps with the best possible decision-making by identifying patterns in data, learning from them, and making predictions based on those patterns.
After all, in the data economy, knowing how to analyze and use data is more crucial than simply obtaining it. For this reason, Professor Lee believes that “the process of acquiring high-quality data, meaningfully analyzing it, and applying it depends on a company’s competitiveness.”
“I believe that a number of industries will see significant changes in the future. Future competitiveness will be enhanced due to the data economy’s acceleration of innovation across industries. Specifically, AI and data analytics will help lower expenses, boost operational effectiveness, and give customers more individualized experiences. Companies will have to adapt if that occurs.”
Professor Lee claims that the manufacturing industry will be able to use “facility data” to forecast the likelihood of equipment failure, and determine when maintenance is necessary if the data economy is implemented.
Furthermore, real-time data increases efficiency by automatically adjusting labor speed and product quality inspection, and AI-analyzed sensor data will allow for “optimization of production processes” and "realization of autonomous factories (smart factories).”
Efficiency gains in risk management and data analysis are also possible in the financial sector. To stop different types of fraud, it examines “transaction data” and looks for abnormal patterns. Needless to mention, it can evaluate the financial situation and spending habits of clients to suggest goods that are specifically designed for them, or improve loan conditions to offer more individualized services.
In the retail sector, data is equally useful. Customer satisfaction can be raised, and consumer trends and seasonal swings can be predicted with the use of data from inventory management, personalized marketing, and customer purchase history analysis. This is the outcome of cost reduction and inventory optimization, which helps avoid shortages and surpluses.
AI and data analytics are useful in cutting expenses and boosting productivity in a variety of sectors. They are also significant in offering clients individualized experiences. Therefore, it is anticipated that the data economy would be crucial in boosting industrial innovation, and bolstering competitiveness in the future.

Digital Transformation with Ethical Use of Data

Professor Lee predicted that the data economy would not only increase Korea’s competitiveness, but also bring about real changes in our lives. To achieve this, though, the pertinent legal system that promotes collaboration and exchange between data usage and personal information protection must be improved.
To make data and AI more cost-effective and efficient, digital infrastructure—such as data centers, cloud infrastructure, and 5G and 6G networks—is also essential. To find personnel capable of handling cutting-edge data analysis and AI technologies, it is imperative to develop vocational training programs and fortify industry-academia collaboration programs.
“Data sharing is facilitated by policy support, which results in the development of new business models and value generation. To guarantee that data is used in a more reliable manner, we will also need to create security regulations and improve data protection technology. Small and medium-sized enterprises, as well as non-IT firms, should be encouraged to join the data economy.”
The data economy offers innovative opportunities. Undoubtedly, there are issues that cannot be disregarded, like data bias, the escalation of social inequity, and invasions of personal privacy. There is little question, though, that data that has already demonstrated the ability to provide individualized services in healthcare and education has the potential to boost economic growth and industry-wide efficiencies. Although the issue of bias is often raised, there are more positive aspects, such as promoting the public interest by serving as a resource for establishing environmental management and welfare policies in many areas, including transportation, energy, and public safety.
Professor Lee stated, “In the end, ethical data use principles and transparent data management are necessary to maximize positive contributions, while minimizing the negative impacts of the data economy.” We think that the data economy will bring about “digital transformation” and a more equitable and prosperous way of living when privacy and fairness are given priority on top of these values.