Si Woong Bae*
Jae-Wook Lee- Future Geo Strategy Research Center, Korea Institute of Geoscience and Mineral Resources (KIGAM), Daejeon, Republic of Korea
Digital innovation technologies, such as artificial intelligence (AI), big data, and digital twins, are rapidly reshaping industries worldwide and fundamentally transforming traditional research and development (R&D) paradigms. The geoscience sector is no exception and must adapt through digitalization and intelligence-driven innovation to meet the demands of technological transformation. This study proposes future directions for technological development in geoscience. Comprehensive bibliometric and environmental analyses were conducted, covering domestic and international policies, market and industrial trends, and advancements in technology and R&D. Based on these findings, STEEP and SWOT analyses were applied to identify key challenges and strategic priorities. Four strategic directions have consistently emerged across the analytical frameworks: (1) advancement of AI and integration of AI agents, (2) development of resource exploration technologies for extreme environments to ensure future resource security, (3) expansion of intelligent climate technologies, and (4) creation of high-value-added services based on geoscience data. This study provides strategic insights to support digital transformation and sustainability in the geoscience sector, along with policy implications to enhance national resource security and global technological competitiveness.
1 Introduction
The global research and development (R&D) landscape is undergoing structural transformation driven by converging factors, including digital transformation, the rise of intelligent systems, climate crisis responses, and the pursuit of sustainability (Vial, 2019; Jin et al., 2025). The rapid advancement of digital technologies, such as artificial intelligence (AI), big data, and the Internet of Things (IoT)—has revolutionized research methodologies and modes of knowledge generation and analysis, triggering fundamental changes across the entire R&D cycle (Feroz et al., 2021). Concurrently, the escalating global climate crisis has elevated carbon-neutral technologies and climate adaptation research to top priorities on the R&D agenda (Cervantes et al., 2023). The international community is increasingly demanding scientific and technological innovations that align with the goals of sustainable development (Stainforth and Calel, 2020; Walsh et al., 2020). In the context of simultaneous, multilayered transformation, ranging from the digital technology revolution to climate and resource challenges, R&D policies and strategic planning must be redefined to align with the dynamics of this macro-level transition.
Although the geoscience sector has begun responding to these global transformations, its pace of innovation remains relatively slow compared to other leading industries. Historically, the mining, oil, and gas sectors have been identified as lagging in technological innovation and digital transformation (Ediriweera and Wiewiora, 2021). Recently, technologies, such as the Internet of Things (IoT), sensors, automation, and AI-based analytics, have been selectively introduced to improve the operational efficiency, safety, and environmental sustainability of industrial plants (Maroufkhani et al., 2022; Storey, 2025). Nevertheless, a substantial portion of geoscientific data remains under-digitized, with limited standardization and integration across databases, resulting in persistent challenges to data interoperability and utilization (Percivall, 2010; Bailo et al., 2020; Wang et al., 2021). To address the climate crisis and promote sustainability, low-carbon technology research, such as carbon capture and storage (CCS/CCUS), resource recycling, and environmentally responsible mining, is progressing; however, large-scale demonstration and commercialization efforts remain at an early stage compared to other industries (Wei et al., 2021; Rui et al., 2025). This relative stagnation threatens the competitiveness of the geoscience industry. Therefore, developing innovative R&D strategies and accelerating technological advancement are essential for securing a sector’s long-term resilience and growth.
In the geoscience domain, a variety of methodological approaches, such as STEEP/PEST (EL) analysis, SWOT and TOWS frameworks, and roadmap or foresight (scenario-based) analyses, have been actively employed to establish strategies to respond to global changes in the research environment and guide future R&D innovation (Wu et al., 2022; Hayati et al., 2023; Jin, 2023; Chatterjee et al., 2025). However, existing studies often focus on advancement strategies specific to individual industries or technologies, frequently overlooking broader systemic linkages. Although technology foresight studies conducted at the national or sectoral levels offer valuable insights into their respective contexts, they may not fully capture the complex, interrelated global challenges currently confronting the field (UNCTAD, 2025). Therefore, effectively addressing the evolving policy, economic, and social contexts surrounding technological innovation in geoscience requires governance and investment strategies that operate at a macro level (Calzada Olvera and Lizuka, 2024). A comprehensive and integrative strategic framework is urgently needed to guide the geoscience sector’s future direction amid global transformation and sustainability imperatives.
This study aims to provide a macro-level perspective and actionable insights into the future direction of technological development in the geoscience sector. Therefore, a comprehensive environmental analysis encompassing domestic and international policies, market and industrial structures, and trends in geoscience-related technology and R&D was conducted. Building on this foundation, STEEP and SWOT analyses were employed to identify key issues and strategic priorities for formulating R&D directions in the field of geoscience. This study establishes forward-looking strategies to proactively address the rapid advancement of science and technology and the evolving global research environment. Ultimately, this study seeks to strengthen the foundation for the geoscience sector to contribute to sustainable development nationally and globally by advancing innovation-oriented R&D strategies.
2 Methods
To comprehensively assess the policy, market, industrial, technological, and R&D environments of the geoscience sector, this study conducted a literature review based on bibliometric analysis. Bibliometric analysis is a systematic method for collecting and organizing knowledge outputs related to a specific topic to identify research trends and the intellectual structure of a field (Donthu et al., 2021). A wide range of publicly available materials produced between 2023 and 2025 in the geoscience sector was extensively collected. These included national master plans and annual work programs, policy reports from international organizations and governments, market outlook reports, academic papers, patents, press releases, and association publications. In particular, recent R&D roadmaps and technological innovation trends from six major countries—the United States, United Kingdom, Japan, Germany, Australia, and China—were closely examined. After excluding documents with unclear provenance or low relevance, 234 sources were selected for final analysis. Using brainstorming and inductive qualitative content analysis, key strategic themes and associated issues were identified (Table 1). To enhance analytical reliability, expert cross-review was conducted. The resulting insights were mapped onto the STEEP and SWOT analytical categories for subsequent analysis.
Table 1. Summary of environmental analysis in the geoscience sector.
The STEEP analysis is a macro environmental framework that systematically examines five key dimensions: social, technological, economic, environmental, and political. This method enables the identification and interpretation of major trends and external change drivers, as well as potential opportunities and threats that may influence future research activities (Yüksel, 2012). The STEEP analysis is particularly effective in the initial stage of strategy formulation and serves as a foundation for understanding broad environmental contexts. Moreover, it is widely recognized as a complementary tool that enhances the robustness of strategic planning when used alongside other approaches, such as SWOT analysis (Vardopoulos et al., 2021).
The SWOT analysis framework identifies internal strengths and weaknesses along with external opportunities and threats to derive strategic directions. It is a widely adopted analytical tool used in the early stages of strategy development to establish approaches that leverage strengths and opportunities, while mitigating weaknesses and threats (Pickton and Wright, 1998). Internal capability analysis enables organizations to identify core resources and limitations, whereas external environmental analysis helps reveal emerging opportunities and risks. This dual perspective allows research institutions to define R&D strategies that align with the rapidly changing environment (Gürel and Tat, 2017). The SWOT matrix cross-analysis method (Weihrich, 1982) was applied to translate the results of the SWOT analysis into actionable strategies. This systematic approach derives responsive strategies by cross-referencing internal (Strengths, Weaknesses) and external (Opportunities, Threats) factors, thereby visualizing their interrelationships and supporting the formulation of coherent strategic responses (Weihrich, 1982).
Key issues and corresponding solutions were qualitatively identified through a comprehensive synthesis of policy demands, market and industrial dynamics, technological developments, and R&D trends at both domestic and international levels. This process followed a stepwise brainstorming framework, beginning with problem definition, followed by issue identification, solution formulation, and the determination of strategic directions. By linking insights from environmental analyses to concrete R&D strategies and actionable initiatives, this approach facilitates the establishment of a strategic response system that addresses the uncertainties in the evolving geoscience landscape.
3 Results
3.1 STEEP analysis
3.1.1 Social factors (society)
Globally, population growth and aging are intensifying concerns regarding social challenges, such as water scarcity and resource depletion (Unfried et al., 2022; Yang X. et al., 2022). In particular, the increasing frequency and compounding nature of extreme weather events driven by global warming, such as heatwaves, droughts, and floods, have escalated social and economic losses (Zscheischler et al., 2018; Zscheischler et al., 2025; Zhou et al., 2023; Wang et al., 2024; Brett et al., 2025). Moreover, the increasing occurrence of geo-hazards, including earthquakes, landslides, and ground subsidence (sinkholes) has become a significant societal concern (Turner, 2018; Yang H. et al., 2025). Consequently, the growing social risks associated with demographic and environmental changes have heightened the demand for R&D on safety, resilience, and sustainability in the geoscience sector. Strengthening public trust and developing proactive science-based response measures have become critical priorities in this field (Lesser et al., 2021).
3.1.2 Technological factors (technology)
The pace of advancement of cutting-edge technologies, including quantum computing, artificial intelligence (AI), digital twins (DT), machine learning (ML), big data analytics, cloud computing, and satellite and drone systems, has accelerated significantly, driving the increasing convergence of these technologies in geoscience research (Stray et al., 2022; Sikakwe, 2023; Zhao et al., 2024). As scientific and technological systems are increasingly becoming complex, multidisciplinary research that integrates geology, environmental science, and information technology has become essential (Gong et al., 2023). AI-driven platforms that can process and analyze massive datasets in real time are replacing traditional data-acquisition-oriented methods. Furthermore, the integration and analysis of geological, geophysical, and geochemical datasets on cloud-based platforms foster a global collaborative ecosystem, enabling real-time research cooperation across institutions and borders (Xu et al., 2020; Boone et al., 2022; Yang L. et al., 2022; Dritsas and Trigka, 2025). Recent efforts have focused on the development of integrated Earth system monitoring technologies that combine diverse sensor networks and satellite observations, resulting in substantial advances in global-scale environmental observations and predictive modeling (Jenni et al., 2017). Resource exploration technologies extend beyond the terrestrial and continental shelf domains to extreme environments, including outer space, the deep ocean, polar regions, and the Earth’s deep crust. Competition to secure technological capabilities for exploration and development in these frontier environments is intensifying (Tolvanen et al., 2019; Hoffman et al., 2022; Wang et al., 2025). As exploration in these domains involves significant technological barriers, specialized advancements in sensing, robotics, and autonomous systems are being pursued and validated through pilot demonstrations (Aguzzi et al., 2022). Such technological innovations have enhanced the efficiency of resource exploration, improved the accuracy of disaster prediction, and advanced environmental monitoring. Collectively, these developments have broadened the scope of geoscience R&D and accelerated the sector’s digital transformation and intelligent evolution.
3.1.3 Economic factors (economy)
Critical minerals essential for batteries, semiconductors, and renewable energy technologies are emerging as new strategic economic assets. According to the IEA, global demand for lithium is projected to increase nearly fivefold by 2040, while demand for graphite and nickel is expected to roughly double and demand for cobalt and rare earth elements to rise to approximately 1.5 times their current levels under the Stated Policies Scenario (STEPS) (IEA, 2025). However, the intensifying United States–China technological rivalry and weaponization of resources have amplified supply chain vulnerabilities. Coupled with disruptions in energy and raw material supply caused by the Russia–Ukraine conflict, these factors have heightened volatility in global commodity prices and increased uncertainty in financial and trade environments (Fang and Shao, 2022; Shiquan and Deyi, 2023). The rise of resource nationalism has led many resource-rich nations to prioritize domestic refining and processing over raw material exports, while imposing higher royalties and export restrictions (Huggins and Kinyondo, 2019). Consequently, resource security has become a core element of the national economic strategy, with a growing policy emphasis on diversifying and expanding the supply chains of critical minerals, including lithium and rare earth elements, to support the growth of strategic industries, such as semiconductors and batteries. Simultaneously, efforts to enhance critical mineral recycling, and mineral revalorization technologies are gaining momentum, aiming to minimize waste and shift from a linear to a circular economy model (Kirchherr et al., 2017; Hagelüken and Goldmann, 2022). This transition mitigates the economic burden and supply risks associated with mineral acquisition as well as promotes sustainable growth. In the geoscience sector, this has spurred active research on urban mining, recycling innovation, and substitute material development, all of which contribute to securing critical mineral resources in a sustainable and economically resilient manner (Lu et al., 2025).
3.1.4 Environmental factors (environment)
Climate change mitigation and carbon neutrality have become fundamental drivers that shape future technological trends in the geoscience sector. With the advent of the carbon-neutral 2.0 era, the climate technology (Climate Tech) industry is expanding rapidly, and global energy systems are shifting from fossil fuel–based structures to renewable and clean energy sources (Kabeyi and Olanrewaju, 2022; Kennedy et al., 2024). For instance, the European Union’s REPowerEU initiative aims to meet 45% of its energy demand from renewable sources by 2030 through large-scale green investments and clean industry promotion policies (Ah-Voun et al., 2024). Similarly, the United States and several other nations have implemented subsidies and tax incentives to accelerate clean technology deployment and enhance industrial competitiveness (Cheng et al., 2024). Extensive research and development efforts are being directed toward securing zero-carbon energy sources, such as offshore wind, solar power, nuclear energy, and hydrogen (Pourasl et al., 2023; Ramakrishnan et al., 2024). Meanwhile, advancements in carbon capture, utilization, and storage (CCUS) technologies are accelerating, along with the development of value-added carbon conversion and resource utilization methods (Alok et al., 2022; Hanson et al., 2025). These environmental imperatives, which are centered on clean energy transition, carbon reduction, and sustainable development, are emerging as key determinants of the future direction of technological innovation in the geoscience domain.
3.1.5 Political factors (politics)
Efforts to leverage geoscience-related data and infrastructure as strategic assets for policy decision-making are becoming increasingly prominent. High-resolution geological information is actively utilized in the formulation of national strategies for land development, resource exploration, and disaster management. To support these efforts, many countries are advancing the establishment of nationwide geological databases and digital twin platforms (Cui et al., 2024; Hinsby et al., 2024). These initiatives have resulted in the standardization and open access of geological data, as well as the expansion of AI-based information services, paving the way toward a geoscience software-as-a-service (SaaS) model that enables researchers and policymakers to efficiently access and utilize critical information (Gao et al., 2024; Pondi et al., 2024). The scientific diplomacy surrounding resource exploration and marine scientific research is gaining strategic importance. Some nations are strengthening their territorial or resource claims through continental shelves and polar research activities, thereby intensifying geopolitical competition and necessitating international cooperation and diplomatic responses (Polejack, 2021; Rüffin and Rüland, 2022). Accordingly, continued efforts to enhance resource security through international collaboration and advanced science- and technology-informed policy making remain crucial to the geoscience sector in the years ahead.
The results of the STEEP analysis are presented in Table 2. The key findings highlight the following strategic directions for the future development of the geoscience sector: (1) Establishing a leading and challenge-driven research environment based on advanced convergent technologies, such as artificial intelligence (AI), machine learning (ML), and quantum sensing is essential. Such an environment can drive innovation across diverse subfields, including exploration, extraction, and disaster prediction. (2) As global competition for critical mineral resources intensifies, and supply chains undergo restructuring, national strategies for securing a stable raw material supply have become increasingly important. (3) With the growing impact of geological hazards and climate change, it is important to expand R&D efforts focused on public safety and societal problem solving while strengthening disaster forecasting and prevention technologies. (4) Accelerating the strategic utilization of geological information as a national asset is critical for enhancing its role in decision-making processes related to resource development, disaster management, and land use planning. (5) Finally, the expansion of AI-driven services enhances the accessibility and application of geological data, enabling a responsive approach to industrial demands and the advancement of science-based policy decision-making systems.
Table 2. Results of STEEP analysis.
3.2 SWOT analysis
The SWOT framework is a strategic tool that systematically examines internal factors, such as strengths and weaknesses and external environmental factors, including opportunities and threats to derive strategic directions. In this study, the analysis was conducted with a focus on the Republic of Korea, where the Korea Institute of Geoscience and Mineral Resources (KIGAM) is based. The institute’s internal capabilities and limitations were evaluated along with the broader industrial and technological environments influencing the geoscience sector. Through this integrated assessment, strategic directions for future technological development were established to address national priorities, including supply chain stability and climate crisis response. The results of the SWOT analysis are presented in Table 3.
Table 3. Results of basic SWOT and SWOT matrix analysis.
3.2.1 Strengths
The key internal strengths of the Republic of Korea include a strong governmental commitment and robust research capacity in the geoscience sector. With the increasing national recognition of the importance of resource security, supply chain stability, and responses to geological and climate-related hazards, policy support for relevant R&D activities has been expanding (Government of South Korea, 2025). Over the decades, KIGAM has accumulated extensive research expertise and human capital supported by active international collaboration and a robust global research network. Furthermore, KIGAM possesses a rich observational infrastructure and a vast repository of geoscience data maintained through the Geo-Big Data Open Platform, providing a solid foundation for data-driven research and technological innovation.
3.2.2 Weaknesses
Despite these strengths, the geoscience sector remains constrained by its traditional research-oriented structure with limited agility in planning and adopting emerging technologies (Ediriweera and Wiewiora, 2021). In the fast-evolving era of the Fourth Industrial Revolution, insufficient responsiveness to new technologies poses the risk of missing innovation opportunities. The growing trend toward interdisciplinary research has led to overlapping studies across multiple institutions, potentially fragmenting limited resources and reducing overall research efficiency. Therefore, strategic differentiation is necessary to avoid redundancy and enhance competitiveness. In addition, the domestic industrial ecosystem supporting the commercialization of geoscience technologies remains under developed (Kim et al., 2020; Lee and Cha, 2021). Weak linkages between research institutions and industries hinder the translation of scientific outcomes into practical applications, limiting innovative technologies in achieving full-scale implementation and global market penetration.
3.2.3 Opportunities
Global efforts to address the climate crisis through enhanced international cooperation are creating new opportunities for R&D engagement and funding (Polejack, 2021; Sovacool et al., 2024b). Therefore, the demand for carbon neutrality and climate adaptation technologies in the field of geoscience is rapidly increasing. The convergence of Fourth Industrial Revolution technologies, including AI, IoT, and big data, with geoscience applications also presents major opportunities for innovation. The emergence of digital geoscience transformation, combining these technologies with existing data and expertise (Zhao et al., 2024), provides fertile ground for the development of new technological solutions. Furthermore, the soaring value of critical minerals has enhanced the economic viability and market demand for resource development projects (IEA, 2025). As global competition intensifies over the supply of strategic minerals, including lithium and rare earth elements, institutions with advanced technologies in this field are well positioned to commercialize R&D outcomes and expand into international markets. The advent of the space economy, including lunar and asteroid exploration, and the rise of polar and extreme environment exploration industries represent new frontiers of opportunity for geoscience innovation.
3.2.4 Threats
Increasing global supply chain risks and weaponization of critical minerals highlight the growing uncertainty in international resource politics (Shiquan and Deyi, 2023). Some nations leverage the resource supply as an economic and diplomatic tool, posing a direct threat to Korea’s resource security. Simultaneously, leading international organizations and corporations are advancing deep-sea and Arctic resource development through massive investments and cutting-edge technologies (Tolvanen et al., 2019; Wang et al., 2025). Falling behind in this technological race could result in dependency and loss of leadership within the global geoscience community. Finally, the increasing frequency and complexity of geo-climatic disasters, such as earthquakes, landslides, and ground subsidence, pose escalating challenges to existing technologies (Alcántara-Ayala, 2025). As these events become increasingly interlinked with climate change, their scale and unpredictability continue to increase. This trend threatens public safety and underscores the urgent need for advanced, adaptive technologies to manage emerging multi-hazard risks.
Building on the SWOT framework, a SWOT matrix was employed to derive cross-strategies that leverage internal strengths to maximize external opportunities, compensate for weaknesses, and mitigate potential threats. This integrative approach establishes future research and development (R&D) for the geoscience sector (Table 3).
3.2.5 SO strategies
The SO strategies focus on exploiting external opportunities through the effective use of internal strength. First, by combining Korea’s extensive geoscience data and domain expertise with emerging technologies, it is possible to accelerate the digital transformation of geoscience research. The fusion of geological data and AI can further foster a high value-added geo-AI service industry. Second, to respond to the global transition toward a low-carbon economy, Korea’s established expertise in geological sciences should be utilized to advance core technologies in carbon capture, utilization, and storage (CCUS) and hydrogen energy. This includes the development of large-scale subsurface hydrogen storage systems and the clean hydrogen production. Third, with intensifying competition in space resource development, led by major powers, such as the United States and China, Korea can capitalize on its strengths in planetary geology to build technical and collaborative foundations for proactive participation in this emerging field.
3.2.6 WO strategies
The WO strategies aim to overcome internal weaknesses by capitalizing on external opportunities. First, recognizing the limited progress in digitalization and automation within the traditional geoscience sector, it is important to seize the opportunities presented by rapid advances in AI and ICT. The integration of machine learning, deep learning, IoT, and drone technologies into exploration, extraction, and disaster-response processes can transform experience-based operations into data-driven systems. Second, considering the rising global demand for critical minerals, Korea’s limited exploration technology and weak commercialization ecosystem must be addressed. By leveraging the external market demand, the development and commercialization of advanced exploration technologies for strategic minerals can be accelerated, positioning Korea to gain a competitive edge in global markets.
3.2.7 ST strategies
The ST strategies seek to minimize external threats by utilizing internal strengths. First, Korea should secure key technologies for resource diversification to address the growing supply chain risks stemming from the concentration of critical mineral sources in specific countries. This includes advancing urban mining, waste recycling, and mineral revalorization technologies while expanding exploration targets both domestically and overseas. Second, in response to the increasing frequency and magnitude of geological disasters, Korea’s vast geoscientific databases and monitoring infrastructure can be harnessed to enhance multi-hazard prediction technologies and improve national disaster resilience. Third, resource development in extreme environments, including the deep-sea, polar, and subsurface domains, presents challenges and opportunities. Considering the technological and regulatory barriers, international joint research should be strengthened to leverage Korea’s strong capabilities for geological surveying and resource assessment, enabling the acquisition of advanced technologies for extreme environment resource exploration.
3.2.8 WT strategies
The WT strategies emphasize defensive measures to minimize risks under conditions where internal weaknesses and external threats coexist. First, to reduce its structural dependence on foreign sources of critical resources and technologies and mitigate disruptions from geopolitical instability, Korea must strengthen its domestic industrial ecosystem through collaboration among academia, industry, and research institutions. Second, to avoid redundant investments and enhance competitiveness among national energy and resource research institutes, it is necessary to identify and focus on KIGAM’s unique research domains to foster specialized excellence and strategic differentiation within the national R&D landscape.
The cross-analysis of the SWOT matrix identifies four overarching strategic directions for future geoscience R&D: (1) AI-driven innovation in geoscience technologies—leveraging extensive geological data to integrate AI across exploration, extraction, and disaster prediction processes, thereby enhancing precision, efficiency, and creation of high value-added Geo-AI solutions; (2) Technological advancement and exploration expansion for diversified resource supply chains—advancing revalorization and recycling technologies for critical minerals while pioneering new exploration frontiers, such as deep-sea, polar, and overseas mining zones, to reduce dependency on specific countries; (3) Enhancement of technologies for climate change and geohazard resilience—improving data-driven disaster forecasting models and developing CO2 mitigation technologies (e.g., CCUS) to strengthen adaptive capacity in complex and uncertain environments; (4) Creation of new high value-added industries utilizing geoscience data—fostering digital twin, Geo-AI, and disaster prediction platform to expand the societal and industrial impact of geoscientific research beyond academia.
3.3 Critical issues and mitigation strategies
To establish future technological strategies for the geoscience sector, a comprehensive analysis was conducted separately from the STEEP and SWOT frameworks, encompassing domestic and international policy trends, market and industrial transformations, technological advancements, and R&D. Based on these findings, key issues were identified, and corresponding solutions were formulated (Figure 1). The major issues can be summarized as follows: (1) strengthening resource security amid resource depletion and global supply chain reconfiguration; (2) pioneering new exploration frontiers beyond terrestrial and coastal boundaries to secure future resources; (3) advancing sustainable resource development and the adoption of environmentally friendly technologies in response to climate change and regulatory pressures; (4) enhancing Earth system monitoring and predictive capabilities to address extreme weather events and geological hazards; (5) leveraging geoscientific data for public safety and social services, thereby increasing the societal value of geoscience research. These issues represent both critical challenges and emerging opportunities that shape the sustainable development of the geoscience industry.
Figure 1. Formulating strategic priorities through the resolution of critical issues.
Therefore, a set of strategic approaches and implementation measures were proposed (Figure 1), from which five core strategic directions were derived: (1) Accelerating digital and intelligent transformation through advanced technologies. Integrating AI and other digital innovations across geoscience fields to enhance exploration and resource management efficiency. Develop domain-specific AI models and immediately apply in the field to build a foundation for digital and intelligent geoscience; (2) Expand exploration boundaries into extreme environments. Broaden the scope of resource exploration and development beyond terrestrial and coastal regions to include the Arctic, deep seabed, and outer space—unexplored domains that hold potential for next-generation resource security; (3) Advance sustainability-oriented technological innovation. Strengthen low-environmental impact, high-efficiency technologies throughout the full resource development lifecycle to support climate change mitigation and sustainable growth; (4) Enhance integrated Earth system monitoring and prediction capabilities. Establish unified data networks by integrating dispersed domestic and international geoscientific and environmental datasets, as well as applying AI-based modeling for early warning of geological hazards—such as earthquakes and landslides—and for proactive detection of geo-environmental changes driven by extreme climate events; and (5) Creating public value and service innovation through geoscientific knowledge and data. Standardize, integrate, and open geoscientific data to build user-friendly platforms that provide rapid access to essential information. The development of new service models, such as Geoscience Software as a Service (Geo-SaaS), should be promoted to strengthen the contribution of geoscience to national safety and public welfare.
4 Policy implications
4.1 Strategic directions
This study conducted a series of analytical processes, including STEEP analysis, SWOT analysis, and the identification of key issues and strategic priorities to derive future directions for technological development in the geoscience sector. The results revealed four strategic directions that were consistently emphasized across multiple analytical frameworks: (1) enhanced application of AI and AI agents to accelerate digital and intelligent transformation, (2) resource exploration in extreme environments to secure future resource availability, (3) advancement of climate technologies to support carbon neutrality and environmental sustainability, and (4) expansion of geological data services to generate new value through data-driven innovation. These strategies collectively provide a roadmap for strengthening the resilience, sustainability, and global competitiveness of the geoscience sector in an era of rapid technological and environmental transformation.
The rapid integration of AI into the global geoscience sector is driving technological innovation by enabling the rapid analysis of vast geological and environmental datasets and early detection of anomalies (Zhao et al., 2024). To achieve this transformation, it is essential to develop and apply domain-specific AI models tailored to subfields, such as resource exploration, mining, and disaster prediction, while accumulating sufficient real-world validation cases to ensure practical reliability. Machine learning–based resource prediction models and deep learning-based automated geological image analyses are emerging as core tools that can identify the distribution and grade of mineral and energy resources with far greater speed and accuracy than conventional methods (Sun et al., 2024). Furthermore, to enhance preparedness for geohazards, such as earthquakes, landslides, and ground subsidence, it is crucial to establish real-time anomaly detection models using sensor data coupled with risk simulation systems that integrate topographic and geological information (Ju et al., 2025). In addition, advanced techniques, such as deep learning–based analysis of drilling and geophysical exploration data, are being developed to construct high-resolution 3D subsurface models that significantly improve geological interpretation and prediction accuracy (Guo et al., 2024; Ma et al., 2024). The acquisition and advancement of AI-driven technologies will transform geoscience into a data-centric industry, reinforcing the security and resilience of national geoscience. Therefore, strategic R&D investment and sustained policy support are imperative for securing technological leadership in this rapidly evolving field.
As terrestrial and coastal resources become increasingly depleted and economically marginal, global competition for resource acquisition is expanding into extreme environments, such as the Arctic, deep oceans, and outer space, which remain largely inaccessible to humans (Tolvanen et al., 2019; Wang et al., 2025). Thus, the development of resources in these frontier regions has become an essential national priority rather than a discretionary endeavor to secure future resource security. However, resource development in extreme environments poses formidable technical challenges and limitations, necessitating parallel advancement of dedicated technologies and pilot-scale demonstration projects. Continuous progress is required in specialized high-performance technologies, including ultra-deep and high-pressure petroleum and gas extraction, simultaneous recovery of lithium and helium from hydrocarbon reservoirs, and advanced exploration of deep-sea and polar mineral resources. For example, the exploration vessel Tamhae-3, equipping with world-class deep-sea survey systems, is expected to serve as a game-changer for resource exploration in the Pacific Ocean and Arctic regions, extending far beyond the waters surrounding the Korean Peninsula. In the emerging field of space resource exploration, the establishment of ground-based testbeds and pilot demonstrations will be critical for pre-validating technologies and increasing the probability of success of in situ resource utilization missions (Sanders and Larson, 2015). Achieving these goals requires urgent national-level investments in R&D, expansion of international collaborations, and capacity building in infrastructure and human expertise. Such efforts will play a pivotal role in securing advanced technologies for extreme environmental resource development and in ensuring long-term national resource resilience.
As the frequency and severity of extreme weather events caused by global warming continue to rise, climate technology (Climate Tech) is emerging not merely as an environmental concern but as a key instrument for national security and economic risk management (Iyke, 2024; Cheng et al., 2025). Sustainable growth of the climate technology industry requires the simultaneous advancement of environmentally friendly technologies and continuous policy support to foster the formation of emerging markets for these innovations. For instance, it is imperative to establish infrastructure and technical standards across the entire clean hydrogen value chain, including the production, storage, transportation, and utilization of blue, green, and white hydrogen (Li et al., 2024). In carbon capture and storage (CCS) processes, strategies should enhance environmental and economic efficiency, such as using renewable energy to power capture operations, thereby minimizing additional energy consumption and secondary carbon emissions (Yang L. et al., 2025). Furthermore, the carbon capture and utilization (CCU) sector demands increased R&D investment and pilot-scale demonstrations of promising technologies, such as mineral carbonation and synthetic fuel production (Zhang et al., 2020). Proactive investment and regulatory reform in next-generation climate technologies, including direct air capture (DAC), advanced CO2 sorbent materials, and enhanced rock weathering (Fuss et al., 2018; Lehmann and Possinger, 2020)—will be essential for achieving substantial greenhouse gas reduction while simultaneously driving green industrial growth. Meanwhile, emerging climate technologies such as hydrogen and CCUS face substantial sociotechnical barriers, including high infrastructure costs, fragmented regulatory environments, and complex stakeholder coordination, as highlighted by recent empirical studies (Gordon et al., 2023; Sovacool et al., 2024a). These constraints indicate that successful deployment will require not only technological innovation but also stronger institutional alignment and enhanced governance capacity to support long-term transition pathways.
Globally, the establishment of digital-twin-based Earth data integration platforms is progressing rapidly. Notable examples include the U.S. Geological Survey’s EarthMAP and the European Union’s Destination Earth (DestinE), both of which integrate geological and environmental datasets to generate predictive insights using AI (Nativi et al., 2021). In response to global trends, it is imperative to enhance integrated management and AI-driven analysis of geoscience data to accelerate the creation of new high-value-added services within the sector. To this end, a national geoscience data platform should be advanced and leveraged to develop innovative service models, such as Geoscience Software as a Service (Geo-SaaS) (Pondi et al., 2024). Moreover, AI-powered knowledge retrieval and AI agent technologies must be developed to provide researchers and policymakers with rapid access to relevant geoscientific information, thereby improving data accessibility and utilization (Chen et al., 2024; Pantiukhin et al., 2025). The expansion of geoscience data services must be supported by institutional frameworks that promote data standardization, integration, and open access as well as by policies to strengthen data quality assurance and governance. By establishing robust data infrastructure and promoting service innovation, the geoscience sector can foster a high value-added data industry ecosystem while significantly enhancing its capacity for science-based decision support at the national and global levels.
Major economies increasingly regard AI as a core technology of national competitiveness and security, advancing it through coordinated national strategies. In a context of intense global investment and rapid AI advancement, delayed adoption and capability development may significantly erode future technological leadership. This urgency is particularly acute in the geoscience sector, where digital transformation has lagged and accelerating technological maturity is essential for improving research efficiency and industrial competitiveness. Accordingly, among the four strategic directions, AI integration and the expansion of high-value geoscience data services are the most actionable and policy-aligned in the short term. This is consistent with the findings of Zhao et al. (2024), which empirically demonstrate the need for AI–geoscience convergence and highlight its potential for expansion across diverse application domains. The AI–geoscience integration pathway identified through macro-environmental scanning and STEEP–SWOT analysis in this study complements prior technology-focused reviews (Zhao et al., 2024) by offering a more comprehensive and strategic perspective, thereby reinforcing the rationale for advancing this research direction. Although climate technologies still face cost and technical hurdles, strong policy momentum and global carbon neutrality commitments position them as near-term investment priorities. In contrast, extreme-environment exploration technologies require a long-term approach due to persistent technical uncertainties and complex regulatory, geopolitical, and collaborative challenges.
4.2 Future work
The integrated STEEP–SWOT framework has demonstrated both practical utility and structural strengths in supporting strategic decision-making within complex policy environments. It is particularly effective for long-term policy planning, sustainability assessment, structured analysis of external drivers, and the development of strategic scenarios, and has been widely applied in domains such as urban planning and climate policy (Dioba et al., 2025). While this approach offers a useful heuristic for organizing strategic analysis, some studies have noted its susceptibility to subjective interpretation, a static evaluative structure, and reliance on assumption-based scanning—particularly in factor classification and external trend analysis (Rastogi and Trivedi, 2016; Gürel and Tat, 2017). These challenges, however, can be mitigated through the complementary use of structured methods such as Delphi expert consultation, the analytic hierarchy process (AHP), multi-criteria decision analysis (MCDA), and scenario planning, which enhance the framework’s analytical rigor and adaptability (Bottero et al., 2021; Vardopoulos et al., 2021). In future research, integrating these methods could enable more systematic prioritization of strategic factors and facilitate the validation of strategic directions under diverse policy and technological scenarios.
5 Conclusion
This study aims to identify future directions for technological innovation in the geoscience sector by employing a multidimensional analytical framework that includes STEEP analysis, SWOT matrix analysis, and key issue identification, based on comprehensive reviews of domestic and international policies, markets, and R&D trends. Collectively, these findings provide a strategic blueprint for strengthening national and global competitiveness amid digital transformation and sustainability transitions. Across multiple analytical approaches, four core strategic directions consistently emerged: (1) Enhanced application of AI and AI agents, which can accelerate digital and intelligent transformation in exploration, resource management, and hazard prediction; (2) Resource exploration in extreme environments, including the Arctic, deep sea, and outer space, to secure future resources and ensure long-term national resilience; (3) Advancement of climate technologies, such as CCUS, clean hydrogen systems, and next-generation carbon reduction methods, to achieve carbon neutrality and promote sustainable resource development; (4) Expansion of geological data services, through the integration of digital twin platforms, Geo-SaaS models, and AI-based data analytics, to create new high value-added industries and support science-informed decision-making. Among the four directions, AI integration and data service expansion are most actionable in the short term. In contrast, climate technologies require sustained investment, and extreme-environment exploration remains a longer-term challenge. This study confirms the practical value of the STEEP–SWOT framework in guiding strategic planning in geoscience. Future research should enhance the robustness of this framework by incorporating structured methodologies such as Delphi, AHP, and scenario planning to support more rigorous prioritization and validation of strategic options under evolving conditions.
Data availability statement
The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.
Author contributions
SB: Conceptualization, Formal Analysis, Investigation, Methodology, Writing – original draft, Writing – review and editing. J-WL: Funding acquisition, Supervision, Writing – review and editing.
Funding
The author(s) declared that financial support was received for this work and/or its publication. This research was supported by the Basic Research Project (Policy Research on Geological Resources Technology and Industry in Preparation for 2030 Amid the Global Transition, GP2025-002) of the Korea Institute of Geoscience and Mineral Resources (KIGAM), funded by the Ministry of Science and ICT.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that generative AI was not used in the creation of this manuscript.
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Keywords: geoscience, STEEP analysis, strategic priorities, SWOT analysis, technology strategy
Citation: Bae SW and Lee J-W (2026) Future technology strategies for the geoscience sector: insights from STEEP and SWOT analyses. Front. Earth Sci. 13:1743903. doi: 10.3389/feart.2025.1743903
Received: 11 November 2025; Accepted: 18 December 2025;
Published: 08 January 2026.
Edited by:
Karoly Nemeth, Institute of Earth Physics and Space Science (EPSS), HungaryReviewed by:
An Xianjin, Guizhou Normal University, ChinaVladyslav Zakharovskyi, Massey University, New Zealand
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*Correspondence: Si Woong Bae, c2l3b29uZ0BraWdhbS5yZS5rcg==