In the 21st century, global competition is no longer defined solely by economic size or military capacity; rather, the power of nations is determined by their ability to produce, scale, and strategically position critical technologies. At the center of this transformation are technologies with both civilian and military applications.<\/p>\n
The concept of dual-use refers, in technical terms, to fields that can be utilized for both civilian and military purposes. However, today the concept is no longer merely a technical classification. Dual-use has evolved into a structural domain of transformation that intersects economic security, geopolitical competition, innovation policy, and investment strategies. For many years, dual-use technologies were primarily addressed within the framework of export control regimes. Multilateral arrangements such as the Wassenaar Arrangement aimed to control the military proliferation of these technologies. Yet, the current dynamics of the global system have transformed dual-use from a risk area to be controlled into a field of competition that must be strategically managed. This transformation is, of course, supported by concrete data. The increase in defense R&D expenditures demonstrates that, alongside military modernization, investments in advanced technologies have accelerated and the interaction between military and civilian technologies has intensified. Moreover, policy documents published in various countries indicate that dual-use research and innovation investments are now positioned at the core of the objective of strategic autonomy.<\/p>\n
From T\u00fcrkiye\u2019s perspective, a similar structural foundation can be observed. The steady increase in defense and aerospace exports in recent years, along with the expansion of capacity in technology-intensive fields, indicates that dual-use technologies are rising on a strong infrastructural base. Unmanned systems, sensor technologies, software infrastructures, and cybersecurity solutions generate scalable applications across both defense and civilian sectors.<\/p>\n
Today, while technology supports economic competition, it has also become a fundamental determinant of the security architecture. An artificial intelligence model developed by a country, the semiconductors it produces, or the data infrastructure it establishes can both enhance efficiency in the civilian economy and directly contribute to military capacity. For this reason, dual-use technologies stand out as a critical domain that simultaneously shapes states\u2019 power projection and economic independence.<\/p>\n
Transformation from the Cold War to the Present<\/strong><\/p>\n The concept of dual-use historically emerged within a security-oriented framework. During the Cold War\u2014when great powers competed not through direct conflict but through technology, ideology, and spheres of influence\u2014the potential of advanced technologies to translate into military capability was regarded as one of the fundamental elements of the strategic balance. For this reason, technology transfer was subject to strict control mechanisms. In this period, dual-use technologies were assessed as elements carrying the risk of shifting from civilian research and production domains into military applications.<\/p>\n However, since the late 1990s, the transformation of the global economic system and the acceleration of digitalization have rendered this approach insufficient. Semiconductors, software infrastructures, communication systems, and data processing capacity have moved to the center of global value chains; civilian technology companies have, in many areas, begun to generate innovation at a faster pace than the defense sector. Consequently, the capacity for technological development has shifted from state laboratories toward the private sector and entrepreneurial ecosystems.<\/p>\n The increase in global defense expenditures also supports this structural transformation. According to data from the Stockholm International Peace Research Institute (SIPRI), which produces global data and analysis on defense spending and military trends, global military expenditures reached an all-time high of $2.718 trillion in 2024, marking a real increase of 9.4% compared to the previous year. The report notes that global military spending has increased consecutively for ten years and recorded its sharpest year-on-year rise since the end of the Cold War. It also states that global per capita military spending reached $334, the highest level since 1990.<\/p>\n This magnitude demonstrates that the defense domain is no longer limited to platform production; it is now directly intertwined with critical technologies such as artificial intelligence, cybersecurity, autonomous systems, and advanced materials. While SIPRI data reveals that the increase in military spending is significantly linked to investments in advanced technologies, analyses by RAND Corporation (a U.S.-based think tank producing analyses in public policy and defense) and CSIS (Center for Strategic and International Studies \u2013 a research institution focusing on international security and strategy) emphasize that artificial intelligence and semiconductors have become central to both the economic and military dimensions of great power competition.<\/p>\n With the 2020s, it is evident that the concept has entered its third phase. The European Union\u2019s approach to strategic autonomy has placed dual-use technologies at the center of the policy agenda, with the aim of reducing external dependencies in critical technologies and strengthening economic security. Policy documents published by the European Commission clearly state that dual-use research and innovation investments hold structural importance for Europe\u2019s competitiveness and security capacity. Expert reports published in 2025 emphasize that dual-use research must be repositioned from the perspective of economic security and technological sovereignty. Indeed, one of the most concrete reflections of this transformation in practice has been the Pentagon\u2019s recent assessment of Claude as a critical supply chain risk, followed shortly by OpenAI signing an agreement with the Pentagon, bringing the integration of all its models\u2014including ChatGPT\u2014into U.S. defense systems and autonomous capabilities onto the agenda.<\/p>\n A notable concept within this new approach is \u201cdual-use by design.\u201d According to this understanding, technologies should not be adapted to military applications at a later stage; rather, they should be designed from the outset with both civilian and defense potential in mind. This shift demonstrates that dual-use has evolved from a risk area to be controlled into a domain of competition that must be optimized.<\/p>\n In conclusion, the conceptual evolution of dual-use technologies can be summarized in three main stages: the security-centered control approach of the Cold War period, the era of technological competition shaped by global value chains, and the new framework\u2014emerging in the 2020s\u2014centered on strategic autonomy and economic security. Today, dual-use is no longer a boundary line between military and civilian domains; rather, it has become a structural element of geoeconomic competition and a strategic component of the innovation architecture. This transformation necessitates that technology policies be addressed not solely from a security perspective, but through a more holistic ecosystem approach.<\/p>\n Transformation of Dual-Use in T\u00fcrkiye<\/strong><\/p>\n In T\u00fcrkiye, this transformation has followed a somewhat different trajectory. The increase in capacity centered on the defense industry has created an important technical foundation for dual-use technologies. Data from the Presidency of Defense Industries (SSB) also demonstrates that production and R&D capacity\u2014particularly in technology-intensive fields\u2014has expanded significantly. According to SSB data, the number of defense industry firms operating in T\u00fcrkiye has reached approximately 3,500. Defense expenditures have continued their upward trend in recent years, reaching a scale of billions of dollars; this increase has progressed in parallel with the rising rate of domestic production and the acceleration of investments in critical technologies. The sector\u2019s total turnover and export performance have similarly grown, with defense and aerospace exports approaching the threshold of $10 billion in recent years, indicating that T\u00fcrkiye has become more visible in the global market for technology-intensive products. The extensive supply chain developing around prime contractors, along with increasing publicly supported R&D expenditures, demonstrates that the defense ecosystem is no longer composed of only a few major players, but has evolved into a multi-layered, widespread, and progressively deepening structure. However, at the current stage of global competition, it is not sufficient for T\u00fcrkiye to address dual-use solely from the perspective of defense production. Integration with the civilian sector, interaction with the entrepreneurial ecosystem, and the inclusion of the economic security dimension must also be incorporated into this framework.<\/p>\n Risks Associated with Dual-Use Technologies and Artificial Intelligence<\/strong><\/p>\n It is observed that, following the Industrial Revolution, many critical technologies were initially shaped by military needs and later evolved into civilian use. These systems\u2014rooted in military expectations and requirements\u2014have been adapted to civilian environments in more flexible and functional forms, resulting in a partially controlled liberalization through the transfer of relatively secure structures into civilian life. While defense-oriented systems are developed within closed and strictly regulated frameworks due to high security and control requirements, their transition into civilian applications produces more flexible, accessible, and scalable versions. For example, the internet originated within U.S. military systems, was subsequently integrated into university infrastructures, and from there spread widely to become one of the defining norms of today. When examining the components of the dual-use concept, this pattern of evolution appears highly familiar. Technologies often emerge in more controlled and relatively lower-risk environments, and then rapidly disseminate, expanding into much broader domains of use. This diffusion not only broadens areas of application but also amplifies the risks they carry. As different layers of use increasingly intertwine over time, the ecosystem expands and value creation increases, while risks become more complex and harder to manage.<\/p>\n A significant exception to this model today can be observed in the field of artificial intelligence. Unlike many other critical technologies, artificial intelligence has largely developed within civilian technology companies and research ecosystems, yet has rapidly begun to be integrated into defense applications. This indicates that the direction of technological development has reversed and that dual-use dynamics have evolved into a bidirectional structure. It is also evident that, in this emerging paradigm\u2014where technologies develop in civilian domains and transition into military structures\u2014the characterization of risk extends far beyond conventional definitions.<\/p>\n The widespread diffusion of AI-based systems at this scale is also transforming the structure of the threat environment. While traditional cyberattacks required a certain level of technical expertise, AI-supported tools significantly lower this barrier. In particular, the use of language models in social engineering attacks makes such attacks more persuasive, targeted, and scalable. In addition, the use of artificial intelligence in automated code generation and the analysis of system vulnerabilities accelerates attack processes and shortens the response time of defense mechanisms. Another critical consequence is the democratization of threat-generation capacity within the framework of equal opportunity. Attacks that were previously carried out only by actors with advanced technical knowledge have become feasible for a much broader user base through AI-supported tools. This development renders the threat environment both more complex and more unpredictable.<\/p>\n At the same time, the widespread adoption of AI-based content generation tools is weakening trust and verification mechanisms in the digital environment. The increasing difficulty of distinguishing between real and artificial content is creating new security risks not only for individual users but also for institutions and states.<\/p>\n The development of artificial intelligence in the civilian domain and its integration into military structures also leads to the direct transfer of existing risks into defense systems. This situation causes issues such as ethics, bias, transparency, and autonomy to evolve from purely technical concerns into operational risk factors. Indeed, ethical debates have recently become increasingly visible. The military applications of AI-based systems bring issues such as the transparency of decision-making processes and accountability to the forefront. Therefore, dual-use technologies are also a subject of political and ethical debate. At this point, the discussions surrounding language models developed by actors such as OpenAI and Anthropic clearly demonstrate the significance of the issue. Consider a GPT system with dual-use characteristics: even in the absence of explicit malicious intent by the user, in cases such as real-time attack scenarios or the generation of sensitive information arising from carefully structured queries, who bears responsibility? The company that developed the model, the institution that deployed the system, or the user who posed the query? These questions do not yet have clear answers. Alongside defining technical boundaries, it is also necessary to address how ethical frameworks, accountability, and transparency will be established. Moreover, it is not difficult to foresee that these debates will become significantly more intense and visible in the near future, both in civilian and military applications.<\/p>\n These risks are not limited to the diffusion of technology alone. Dependence on global supply chains, reliance on foreign sources for critical components, the manipulation of AI models, and cyberattacks as next-generation threats further deepen the strategic risk dimension of dual-use technologies. A critical reality that stands out at this point is that all these risks are shaped and managed\u2014directly or indirectly\u2014through the cyber domain.<\/p>\n Cybersecurity in the Dual-Use Ecosystem<\/strong><\/p>\n Although dual-use technologies are often discussed through artificial intelligence, autonomous systems, or space technologies, the foundational layer that horizontally cuts across and enables all these domains is cybersecurity. Nearly every technology developed today is, by its nature, software-based, data-driven, and network-connected. This reality has transformed cybersecurity from merely a protective mechanism into a prerequisite for the operability of technological systems.<\/p>\n In this respect, cybersecurity is no longer a conventional support function; it is positioned as a strategic domain directly linked to economic value creation, national security, and system continuity. Particularly in the context of critical infrastructures, the increasing dependence of systems\u2014ranging from energy networks to financial systems, from transportation to healthcare\u2014on digital infrastructures transforms cyber risks into a systemic risk category. Such risks can generate cascading effects that impact not only individual institutions but entire economies through interconnected structures.<\/p>\n The integration of artificial intelligence technologies into the field of cybersecurity represents one of the most visible and rapidly evolving examples of dual-use dynamics. In particular, large language models provide a new set of tools that increase the scale and complexity of cyberattacks. These models create a wide range of applications, from malware generation to the personalization of phishing scenarios, enabling even actors without advanced technical expertise to carry out more sophisticated attacks.<\/p>\n At the core of this transformation lies the dual nature of artificial intelligence. The same technology, on the one hand, facilitates the development of anomaly detection, threat hunting, and automated response systems; on the other hand, it can also be used for attack development, vulnerability analysis, and bypassing security systems. This reality makes it impossible to position artificial intelligence solely as a defensive tool in the classical sense; rather, it has become a direct strategic instrument of power. It is precisely for this reason that the concepts of AI security and security for AI have become subjects of ongoing debate.<\/p>\n In addition, artificial intelligence enables a significant degree of automation in cyberattack processes. The decreasing need for human intervention across stages such as reconnaissance, vulnerability analysis, attack development, and execution increases both the speed and scale of attacks, while substantially shortening the response time of defense mechanisms. Studies that concretize this argument are also increasing. For instance, in a study conducted using Claude, different AI models were tested; even without providing the model with direct attack instructions and deliberately avoiding explicit \u201chow-to\u201d guidance, it was observed that cyberattack scenarios could be generated in a short time merely through the construction of well-structured queries. More strikingly, a substantial portion of these scenarios proved to be practically applicable and capable of producing successful outcomes. This demonstrates that the misuse risk of AI systems is directly related to the nature of user interaction itself.<\/p>\n In this context, the nature of cybersecurity investments also differs from other technology investments. While traditional technology investments focus on value creation, cybersecurity investments are largely aimed at preventing potential losses. However, uncertainty regarding when and to what extent such losses may materialize can lead the private sector to underinvest in this area. This indicates that cybersecurity is a domain that cannot be sufficiently optimized through conventional market dynamics and that public policies must assume a complementary role in addressing this gap.<\/p>\n On the other hand, the prioritization of speed over security in the development processes of digital products and services constitutes a significant structural problem. Competitive pressure, short product cycles, and a \u201cfirst-mover advantage\u201d approach often push companies to compromise on security testing. In an environment where dual-use technologies are increasingly widespread, this generates not only commercial risks but also national security risks. The emergence of such vulnerabilities in critical systems that directly affect safety and human life would render all technological advantages fragile. Therefore, strategic management must establish a balance between the agility brought by entrepreneurship and the uncompromising institutional reliability required for defense, positioning security not as an obstacle but as a prerequisite for system operability.<\/p>\n Recent cybersecurity strategy documents published by the United States also clearly reflect this transformation. In these documents, cybersecurity is addressed not only as a key defense issue but also in conjunction with innovation capacity, public-private collaboration, and the protection of critical infrastructures. In particular, it is emphasized that the protection of critical infrastructures operated by the private sector necessitates public-private partnerships and that cybersecurity has become an area of collective responsibility.<\/p>\n Within this framework, cybersecurity can be regarded as both the carrier of dual-use technologies and the fundamental layer that defines their boundaries. An insecure artificial intelligence system does not constitute a strategic advantage from a defense perspective; on the contrary, it represents a risk factor that can create vulnerabilities. Similarly, autonomous systems, sensor networks, or data platforms can only generate real value to the extent that they operate on a secure digital infrastructure. Interpreting the dual-use debate solely through the lens of technology production is insufficient; the decisive factor is the cyber capacity that enables these technologies to function securely, sustainably, and without interruption. In this context, cybersecurity ceases to be a secondary element of defense policies and becomes one of the foundational components of technology policy itself.<\/p>\n Technological Capability, Scalability and Structural Competition<\/strong><\/p>\n At the current stage, dual-use technologies can no longer be assessed merely as technical solutions with two distinct application areas. The defining issue is how these technologies reconstruct the relationship between production capacity and economic value creation. The strength of this domain arises not simply from enabling transitions between military and civilian applications, but from high knowledge intensity, deep R&D accumulation, and the capacity for scalability.<\/p>\n In the past, defense technologies were developed within more closed, vertical structures by a limited number of actors. Today, however, knowledge production is far more dispersed, multi-actor, and speed-driven. This shift has transformed technology from a linear transfer process into a mutually reinforcing interaction domain. A defense-origin solution can now rapidly find application in the civilian market; likewise, a technology developed in the civilian domain can, within a short time, become a critical component of defense systems.<\/p>\n At this point, the differentiating factor is not merely producing technology, but how that technology is managed. Structures that achieve lasting advantage in the dual-use domain are those capable of simultaneously accomplishing three things: generating strong R&D output, converting this output into economic value, and establishing the institutional capacity to sustain this process at a global scale. When this balance is not achieved, technology either remains confined to the laboratory or fails to scale.<\/p>\n In the long term, success depends on the ability to establish a cycle in which defense-centered engineering capabilities continuously interact with the civilian economy. When this cannot be achieved, technology becomes confined to a specific domain. The real value, however, lies in building a structure that spreads across different sectors and generates productivity. Competition is evolving in parallel with this shift.<\/p>\n Particularly in an era where artificial intelligence and digital infrastructures have become so central, the boundary between technology and security has nearly disappeared. Not only how advanced a technology is, but also how secure it is, has become a determining factor. An insecure system does not generate advantage; on the contrary, it produces vulnerabilities. The fact that such vulnerabilities may affect defense and critical systems that directly impact safety and human life makes these advantages far more fragile. Therefore, in the coming period, the direction of competition will be determined jointly by innovation capacity and by how secure, resilient, and manageable that innovation is. Naturally, the leadership of this transformation will be assumed by individuals and institutions that adopt this mindset, do not ignore risks, and take responsibility.<\/p>\n References<\/strong><\/p>\n In the 21st century, global competition is no longer defined solely by economic size or military capacity; rather, the power of nations is determined by their ability to produce, scale, and strategically position critical technologies. At the center of this transformation are technologies with both civilian and military applications.<\/p>\n","protected":false},"author":37,"featured_media":1696,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[28],"tags":[455,456,322,454,457,458],"ppma_author":[453],"class_list":["post-1695","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-digital-transformation-and-entrepreneurship","tag-artificial-intelligence-security","tag-cybersecurity","tag-defense-industry","tag-dual-use-technologies","tag-geopolitical-competition","tag-tech-security"],"acf":[],"aioseo_notices":[],"authors":[{"term_id":453,"user_id":37,"is_guest":0,"slug":"murat-gurakan","display_name":"Murat G\u00fcrakan","avatar_url":{"url":"https:\/\/www.toplum.org.tr\/en\/wp-content\/uploads\/2026\/04\/Murat-Gurakan.jpg","url2x":"https:\/\/www.toplum.org.tr\/en\/wp-content\/uploads\/2026\/04\/Murat-Gurakan.jpg"},"0":null,"1":"","2":"","3":"","4":"","5":"","6":"","7":"","8":""}],"_links":{"self":[{"href":"https:\/\/www.toplum.org.tr\/en\/wp-json\/wp\/v2\/posts\/1695","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.toplum.org.tr\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.toplum.org.tr\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.toplum.org.tr\/en\/wp-json\/wp\/v2\/users\/37"}],"replies":[{"embeddable":true,"href":"https:\/\/www.toplum.org.tr\/en\/wp-json\/wp\/v2\/comments?post=1695"}],"version-history":[{"count":1,"href":"https:\/\/www.toplum.org.tr\/en\/wp-json\/wp\/v2\/posts\/1695\/revisions"}],"predecessor-version":[{"id":1698,"href":"https:\/\/www.toplum.org.tr\/en\/wp-json\/wp\/v2\/posts\/1695\/revisions\/1698"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.toplum.org.tr\/en\/wp-json\/wp\/v2\/media\/1696"}],"wp:attachment":[{"href":"https:\/\/www.toplum.org.tr\/en\/wp-json\/wp\/v2\/media?parent=1695"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.toplum.org.tr\/en\/wp-json\/wp\/v2\/categories?post=1695"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.toplum.org.tr\/en\/wp-json\/wp\/v2\/tags?post=1695"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/www.toplum.org.tr\/en\/wp-json\/wp\/v2\/ppma_author?post=1695"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}\n
\nhttps:\/\/www.aa.com.tr\/tr\/ekonomi\/savunma-ve-havacilik-ihracatta-10-milyar-dolar-esigini-asti\/3788818<\/a><\/li>\n
\nhttps:\/\/www.consilium.europa.eu\/en\/policies\/defence-numbers\/<\/a><\/li>\n
\nhttps:\/\/research-and-innovation.ec.europa.eu\/research-area\/industrial-research-and-innovation\/dual-use-technologies_en<\/a><\/li>\n
\nhttps:\/\/research-and-innovation.ec.europa.eu\/news\/all-research-and-innovation-news\/new-publications-dual-use-provide-strategic-input-future-eu-ri-policies-2025-06-25_en<\/a><\/li>\n
\nhttps:\/\/research-and-innovation.ec.europa.eu\/funding\/funding-opportunities\/funding-programmes-and-open-calls\/horizon-europe_en<\/a><\/li>\n
\nhttps:\/\/www.rand.org\/topics\/artificial-intelligence.html<\/a><\/li>\n
\nhttps:\/\/www.csis.org\/programs\/defense-industrial-initiatives-group<\/a><\/li>\n
\nhttps:\/\/www.sipri.org\/media\/press-release\/2024\/world-military-expenditure-reaches-new-record-high<\/a><\/li>\n
\nhttps:\/\/www.wassenaar.org<\/a><\/li>\n
\nhttps:\/\/www.whitehouse.gov\/wp-content\/uploads\/2026\/03\/president-trumps-cyber-strategy-for-america.pdf<\/a><\/li>\n
\nhttps:\/\/openknowledge.worldbank.org\/server\/api\/core\/bitstreams\/719698c9-b21b-4dd4-a875-bfc34b2961ce\/content<\/a><\/li>\n
\nhttps:\/\/www.eye.security\/blog\/dual-use-ai-in-cyberattacks-how-llms-are-reshaping-the-threat-landscape<\/a><\/li>\n
\nhttps:\/\/trufflesecurity.com\/blog\/claude-tried-to-hack-30-companies-nobody-asked-it-to<\/a><\/li>\n
\nhttps:\/\/www.theguardian.com\/technology\/2026\/feb\/28\/openai-us-military-anthropic<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"