AI: Accelerating Industrial Innovation Across Culture, Construction, Education, and Agriculture

~23 min read

AI Establishes Itself as the Innovation Engine for All Industries

In 2024, Artificial Intelligence (AI) has solidified its status as a core driving force, leading innovation across all sectors of society, moving beyond a mere technological trend. AI is no longer confined to advanced tech fields; it is deeply permeating traditional industries such as culture, sports, tourism, construction, education, and agriculture, opening up new possibilities. We are witnessing a paradigm shift where existing operational methods and services are fundamentally changing, especially as attempts to integrate AI with the expertise of each field are actively underway. This transformation is noteworthy because it goes beyond simply increasing efficiency, moving towards enhancing the quality of life for individuals and creating new value.

The Ministry of Culture, Sports and Tourism (MCST) is hosting the ‘2026 Culture, Sports and Tourism AI & Data Utilization Contest’ until June 26th. This initiative aims to discover outstanding cases that enrich the public’s cultural life by converging AI technology with cultural data. Going beyond mere idea proposals, the contest targets the creation of tangible results using actual AI technology. Building on proven achievements, such as winning the Presidential Award and the Minister of Interior and Safety Award at last year’s pan-government public data utilization startup competition, this year’s contest designates AI utilization as a mandatory element across all submission categories, prioritizing AI-driven cultural digital innovation. This signifies that AI will play a crucial role in strengthening the competitiveness of the cultural industry and discovering new growth engines.

The construction industry is also accelerating the adoption of AI. Meissa, a geospatial AI company, has signed a contract with Shinsegae Engineering & Construction to supply drone-based geospatial solutions to construction sites nationwide. This innovative endeavor aims to completely replace existing global solutions and enhance site management systems by automating and unmanned the entire process on the Meissa platform, from drone flight to data collection, analysis, and utilization. Major domestic construction companies like Hyundai E&C, Daewoo E&C, and DL E&C are choosing Meissa due to its platform capabilities optimized for Korean construction processes. Beyond that, there’s an ambitious goal to integrate multi-layered spatial data from drones, satellites, CCTVs, and IoT to establish a ‘Single Source of Truth’ for sites, and further, to implement a ‘World Model’ where AI and autonomous robots autonomously assess the site. This will not only maximize safety and efficiency at construction sites but also serve as a crucial stepping stone to accelerate the digital transformation of the construction industry in the future.

In the education sector, AI’s role is also becoming increasingly important. Samsung SDS is strengthening its collaboration with OpenAI to provide the ‘ChatGPT Edu’ service to educational institutions. This service is designed to prevent conversation content from being used as AI training data, thereby enhancing data privacy and security. It offers various functionalities based on the GPT-5 language model, including text comprehension, coding, and data analysis. Already utilized by leading global universities such as Oxford University and the University of London, this service is slated for pilot implementation at Korea National Open University in South Korea. Furthermore, the Ministry of Education and the Ministry of Science and ICT have formed a dedicated task force (TF) for AI talent development. They are rapidly advancing the ‘Republic of Korea AI Action Plan,’ which includes collaboration among AI hub universities and colleges, establishing AI practical training platforms for elementary and secondary schools, and innovating teacher training and development systems. This demonstrates the government’s strong commitment to securing national competitiveness by strengthening AI education, a core competency for future society.

The agricultural sector is also seeking innovation through AI technology. The Rural Development Administration (RDA) is conducting training to enhance the utilization capabilities of its Agricultural Science and Technology Information Service (ASTIS) system. This practical training, which includes using AI for policy report writing, data analysis, automating repetitive tasks, and creating promotional and educational content, aims to strengthen the competencies of agricultural technology dissemination officers. Additionally, through ‘AI Isak,’ an AI-powered conversational robot specializing in agriculture, the RDA provides expert agricultural knowledge and information, such as field technical support, crop variety information, and market forecasts. The focus is on quickly and accurately diagnosing and supporting issues in agricultural fields. These efforts to expand data-driven agricultural technology dissemination are expected to improve agricultural productivity and contribute to increasing farm household income.

As such, AI has now established itself not as a technology confined to specific fields, but as a universal technology that promotes innovation across all sectors of our society. AI is being applied to meet the unique characteristics and demands of each industry, which in turn signifies the birth of new business models and the restructuring of existing industrial frameworks. AUTOFLOW is committed to meticulously analyzing these trends in AI-driven industrial innovation and providing practical insights and actionable advice to businesses and individuals.

AI Leads the Digital Transformation of the Cultural Industry

The Ministry of Culture, Sports and Tourism (MCST) is actively seeking innovative cases that integrate AI and cultural data through the ‘2026 Culture, Sports and Tourism AI & Data Utilization Contest.’ This initiative goes beyond mere technological interest, aiming specifically to qualitatively enhance the public’s cultural experiences through AI. The successful results from last year’s public data utilization startup competition demonstrated the potential of these efforts, and this year, by designating AI utilization as a mandatory element, the ministry plans to further accelerate AI-driven cultural digital innovation.

This contest is divided into three categories: ‘New Technology Utilization (ADX),’ ‘Cultural Data Utilization,’ and ‘Data Analysis.’ A total of 15 awards and 50 million Korean Won in prize money will be presented. The grand prize winner in the Cultural Data Utilization category will receive an opportunity to advance to the finals of the ’14th Pan-Government Public Data Utilization Startup Competition,’ hosted by the Ministry of Interior and Safety. This is an important program designed to revitalize the startup ecosystem utilizing AI and cultural data, and to support innovative ideas in becoming actual businesses. Eligibility is open to any South Korean citizen, either individually or in teams of up to five people (including businesses), and applications can be submitted through the official website.

This contest encourages attempts to apply AI technology across the entire spectrum of cultural content creation, distribution, and consumption to generate new experiences. For example, possibilities include AI-based personalized exhibition recommendation services, immersive cultural experience content combined with virtual reality (VR) and augmented reality (AR) technologies, and trend prediction and new content planning through AI-driven cultural data analysis. These innovative endeavors will significantly contribute to strengthening the competitiveness of the cultural industry and pioneering new markets. Furthermore, top award winners will receive support for commercialization and investment consulting (IR), helping their ideas materialize into actual businesses.

The advancement of AI technology is also bringing changes to the creative process in the cultural and artistic fields. AI can be utilized as a tool to assist or inspire creative activities in various art forms such as music composition, fine arts, and literature. Moreover, AI-based content recommendation systems will provide users with more personalized cultural experiences, which will also transform cultural content consumption patterns. Recognizing the potential of such AI technology, the MCST is demonstrating its commitment to leading the digital transformation of the future cultural industry by encouraging the participation of experts and the general public in related fields through the contest.

Digital Innovation in Construction Sites: The Role of AI Geospatial Platforms

The construction industry traditionally requires significant manpower and time, and safety management is also a critical challenge. Meissa’s AI geospatial platform, supplied to Shinsegae Engineering & Construction, is expected to play a crucial role in solving these persistent problems at construction sites. Specifically, drone-based data collection and AI-driven analysis provide real-time site information that was difficult to ascertain through traditional manual methods, thereby maximizing efficiency in various aspects such as process management, safety inspections, and material management.

The Meissa platform aims to transform the entire site operating system, going beyond being a mere data collection tool. Its unmanned and automated system, based on autonomous drone stations, reduces reliance on human labor and enables 24/7 site monitoring. This establishes a foundation for preventing safety accidents at construction sites and responding quickly to unforeseen issues. Furthermore, an operating system where design, construction, and progress data are integrated and managed as a single spatial dataset reduces errors caused by information discrepancies and enhances the overall transparency and accuracy of projects.

Meissa is chosen by major domestic construction companies because it deeply understands their practical requirements and provides optimized solutions. It goes beyond simply processing drone data, offering functionalities that meet the actual needs of construction sites, such as process management, progress calculation, and on-site technical support. This is a prime example of how AI technology can be applied in real industrial settings to create value. Meissa’s pursuit of establishing a ‘Single Source of Truth’ and a ‘World Model’ offers a glimpse into the future of the construction industry, heralding an era of automation where AI and robotic technology autonomously manage construction sites.

AI Enhances Safety and Efficiency in Education

The collaboration between Samsung SDS and OpenAI demonstrates the potential for safe and effective AI utilization in education. ‘ChatGPT Edu’ fundamentally blocks the risks of data leakage and misuse that existing generative AI services might pose, while enabling the integration of powerful features offered by cutting-edge language models like GPT-5 into educational settings. This provides an environment where both teachers and students can learn and utilize AI technology without burden, and it is expected to become a crucial pillar of future education.

Data privacy and security are among the most sensitive aspects of AI technology dissemination, especially in educational settings where sensitive information may be handled. ChatGPT Edu addresses these concerns by being designed so that conversation content between users and AI is not used for AI model training. This allows students to ask questions and explore freely, while teachers can leverage AI to enhance efficiency in lesson preparation and student guidance. Furthermore, AI-based support for creating personalized learning content holds the potential to maximize students’ learning outcomes.

The diverse functionalities offered by the GPT-5 language model will broaden the horizons of education. Its text comprehension and generation capabilities can be utilized for report writing and essay editing, while its coding abilities will open new possibilities for programming education. Data analysis features can help students interpret data and gain insights in science and social studies subjects. Web browsing functionality supports accessing the latest information and research processes, and document summarization is useful for efficiently acquiring vast amounts of information. The custom chatbot creation feature can be used to develop AI tutors tailored to specific subjects or learning objectives.

Through this collaboration, Samsung SDS is laying the groundwork for successful implementation in real educational settings, including piloting ChatGPT Edu at large-scale educational institutions like Korea National Open University. This demonstrates that AI technology can drive positive change in actual educational environments, moving beyond mere theoretical possibilities. Samsung SDS’s ‘one-team’ support system, based on its ‘AX Transformation Strategy,’ provides end-to-end services encompassing AI consulting, development, operations, cloud, and security, assisting educational institutions in successfully adopting and utilizing AI technology. These efforts will be essential for nurturing the talent that will lead the AI era.

UNIST Develops ‘π-Invariant Test-Time Normalization’ Algorithm to Enhance AI Prediction Accuracy

The ‘π-Invariant Test-Time Normalization’ algorithm developed by Professor Chang-Wook Jeong’s team at UNIST (Ulsan National Institute of Science and Technology) is a groundbreaking technology that enables AI to maintain accuracy despite changes in the size of the predicted object. This could be key to solving the problem of decreased prediction accuracy when AI models encounter new data sizes not seen during training. It is expected to significantly increase the applicability of AI, especially in fields dealing with objects of highly diverse and wide-ranging sizes, such as semiconductor manufacturing processes or power plant piping.

The core of this algorithm lies in utilizing ‘π values’ based on ‘Buckingham π theorem’ to re-normalize new input data according to the standards of existing training data. A π value is a dimensionless ratio created by combining physical quantities with units, such as length, temperature, and force, according to physical laws. If these values are the same, objects can be considered essentially in the same physical state, even if their sizes differ. The research team uses this principle to transform input data outside the training range into an ‘familiar form’ within the training range, while adhering to physical laws. By inputting this transformed data into the AI model, the model can maintain consistent prediction performance, unaffected by size variations.

Another advantage of this algorithm is its cost-effectiveness. It can be applied directly to existing trained AI models without the need to retrain new models from scratch. This significantly reduces the time and cost involved in AI model development and operation. The method of transforming input data in log space to maintain physical ratios (π values) effectively models complex physical phenomena while enhancing computational efficiency. Such technological advancements lay the groundwork for AI to be reliably utilized in more complex and diverse real-world environments.

Professor Chang-Wook Jeong’s team’s research is a significant achievement that has elevated the versatility and practicality of AI technology. In particular, the development of an AI algorithm that ensures size invariance will contribute to pioneering even more diverse and sophisticated AI application fields in the future. This will help AI establish itself as an essential tool for effectively understanding and predicting phenomena occurring at various scales in the complex real world, beyond merely solving specific problems.

Agriculture: Enhancing Productivity and Field Responsiveness with Data and AI

The Rural Development Administration (RDA) is focused on increasing the responsiveness of agricultural fields through the dissemination of data-driven agricultural technologies. The ‘Agricultural Science and Technology Information Service (ASTIS)’ system is a core platform that systematically manages vast amounts of data collected from city/county agricultural technology centers and agricultural sites, and provides technical resources utilizing this data. Through this system, agricultural technology dissemination officers can easily access the latest research findings and field know-how, effectively transferring them to farm households. This forms a crucial foundation that can directly contribute to improving agricultural productivity and increasing farm household income.

Training to enhance ASTIS system utilization capabilities also constitutes an important part. The Rural Development Administration supports officers in maximizing system usage to effectively analyze data and provide optimized technical consulting to farm households based on this analysis. In particular, practical training, including using AI for policy report writing, data analysis, automating repetitive tasks, and creating promotional and educational content, contributes to increasing officers’ work efficiency and strengthening their expertise. Self-directed learning support, considering individual AI utilization levels and areas of interest, will further maximize these educational effects.

The application of AI in agriculture extends beyond simple data management and analysis. The ‘Ask AI Isak’ service provided by the Rural Development Administration offers real-time expert agricultural knowledge and information, such as field technical support, crop variety details, and market forecasts, through an AI-powered conversational robot specializing in agriculture. This helps farmers obtain quick and accurate answers to the problems they face and provides crucial reference materials for agricultural management decisions. Such AI-based information provision systems will be a key factor in strengthening the future competitiveness of agriculture.

Noh Hyung-il, Director of the Rural Support Policy Division, stated, “We will focus on strengthening field responsiveness to diagnose and support agricultural site issues more quickly and accurately,” expressing the commitment to meet farmers’ technological demands through the expansion of data-driven agricultural science and technology dissemination and the advancement of the technology dissemination system. This indicates that AI and data technologies will play an essential role in the sustainable development of agriculture and the enhancement of farm household competitiveness. The Rural Development Administration’s efforts are expected to accelerate the era of smart farming and contribute to securing future food security.

The AI Era: Innovation in Mathematics Education and Educational Democratization

The open-source release of the ‘MathNet’ dataset, spearheaded by MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), marks a significant milestone in enhancing AI’s mathematical reasoning capabilities. The systematic collection and organization of original problems submitted by participating countries in the International Mathematical Olympiad (IMO) each year, and their free availability to AI researchers and students worldwide, holds the potential to not only democratize AI education but also fundamentally shift the paradigm of mathematics education itself.

MathNet contains over 30,000 mathematics problems and solutions, making it the largest and highest-quality proof-based mathematics dataset built to date. The more than 30,000 expert-authored problems, collected from 143 competitions across 47 countries and 17 languages worldwide, go beyond simple problem-solving to reflect diverse cultural backgrounds and mathematical approaches. This signifies that the AI model is designed to learn a broader and more creative mathematical way of thinking. In particular, the inclusion of unique perspectives and traditions from each country’s mathematical community, such as combinatorics problems from Romania or number theory problems from Brazil, is a distinctive strength of MathNet.

Unlike existing datasets that focused primarily on competition problems from the United States and China, MathNet has secured a unique position in terms of ‘diversity,’ encompassing problems from dozens of countries across six continents. This diversity is essential for AI models to understand and apply more universal mathematical principles without being biased towards specific regions or cultures. As MIT doctoral candidate Shaden Alshammari stated, the effort to resolve the regrettable scattering of creative problem booklets brought by each country after events, and to utilize them for the public good of AI research and education, is particularly noteworthy.

The open-source release of MathNet provides invaluable research resources to AI researchers, opening an opportunity to advance AI’s mathematical reasoning capabilities. Furthermore, by allowing students worldwide free access to high-quality mathematics problems and solutions, it will significantly contribute to bridging educational gaps and democratizing mathematics education. This is an example of how AI technology can contribute to realizing social values, such as alleviating educational inequality, beyond mere technological advancement. We anticipate that AI models utilizing MathNet will contribute to solving mathematical challenges and help more students discover the joy of mathematics.

Industry-Academia-Research Collaboration for AI Talent Development and the Future Direction of Education

The launch of the AI Talent Development Task Force (TF) by the Ministry of Education and the Ministry of Science and ICT demonstrates a strong national commitment to preparing for the AI era. Both ministries are working closely to implement the ‘Republic of Korea AI Action Plan’ and are striving to build an organic cooperation system among AI hub universities, AI colleges (including the four major science and technology institutes), and AI-focused universities. This represents a strategic approach to systematically strengthen the educational system for fostering AI professionals and to cultivate the core talent required by future society in a timely manner.

The TF is focused on supporting the cultivation of AI competencies from the foundational education stage, including establishing AI practical training platforms for elementary and secondary schools, and innovating teacher training and development systems. In particular, the development of ‘Guidelines for Generative AI Utilization in Education’ will serve as a crucial foundation for guiding students to use AI safely and ethically. This is an essential effort to maximize the positive aspects of AI technology while minimizing potential risks. As Vice Minister of Education Choi Eun-ok mentioned, talent policy in the AI era cannot be achieved through the efforts of a single ministry alone, making cross-ministerial collaboration to create synergy paramount.

Ryu Je-myung, Second Vice Minister of Science and ICT, emphasized the rapid pace of AI technology development and underscored the importance of talent development that keeps pace with it. This implies the need to build a talent development system that can flexibly respond to the rapid evolution of AI technology and continuously acquire new knowledge and skills. Collaboration among AI hub universities, the four major science and technology institutes, and AI-focused universities will leverage the strengths of each institution to create synergy and contribute to developing more efficient and effective AI talent development programs.

In addition to these government-led efforts, active participation from the private sector, as seen in the collaboration between Samsung SDS and OpenAI, is also essential for AI talent development. Providing AI solutions tailored to the characteristics and needs of educational institutions, and establishing a safe and ethical AI utilization environment, are crucial factors that help AI technology successfully take root in educational settings. Ultimately, talent development in the AI era will be achieved through organic cooperation among government, educational institutions, and industry, which will be a core driving force for securing sustainable national competitiveness.

Conclusion: AI Unlocks New Horizons for Industrial Innovation

Today, AI is deeply penetrating almost every sector of our society, accelerating innovation. From discovering creative content in culture, sports, and tourism, to enhancing safety and efficiency at construction sites, creating personalized learning environments in education, improving productivity in agriculture, and laying the mathematical foundation for AI’s own advancement, AI acts as a core driver, solving unique challenges and opening new possibilities in each industry.

Specifically, the cases discussed in this article clearly demonstrate that AI technology is moving beyond mere theoretical concepts to create tangible value in real industrial settings. The MCST’s contest aims to improve the quality of public life through the convergence of AI and culture, Meissa’s solution drives the digital transformation of the construction industry, Samsung SDS’s ‘ChatGPT Edu’ provides a safe and effective AI educational environment, and UNIST’s algorithm contributes to enhancing the reliability and versatility of AI technology itself. Furthermore, the Rural Development Administration’s data-driven agricultural technology dissemination and MIT’s ‘MathNet’ release effectively illustrate how AI can contribute to realizing social values and advancing future technology.

In conclusion, AI is no longer an option but a necessity. It is time for both businesses and individuals to understand the potential of AI technology and actively explore how it can be applied in their respective fields. AUTOFLOW will continue to meticulously analyze evolving AI technology trends and provide in-depth insights into their impact on various industrial sectors and practical application strategies. AI-driven innovation will persist, and keeping pace with these changes will be the key to securing future competitiveness.

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