{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T02:51:56Z","timestamp":1791427916431,"version":"4.3.3"},"reference-count":0,"publisher":"EWA Publishing","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AEMPS"],"abstract":"<jats:p>With the rapid development of artificial intelligence (AI), its applications have gradually expanded from the commercial and civilian sectors to national security fields such as military security, cybersecurity, and critical infrastructure protection. Using a literature review and case analysis approach, this article examines the main applications of AI in different security scenarios and the risks they bring. The study finds that AI can improve the information processing and response capabilities of the national security system by enhancing the efficiency of multi-source information processing, strengthening threat identification and prediction capabilities, and increasing the autonomy of military systems. However, enhanced AI capabilities do not necessarily lead to higher levels of security. Its national security applications face three interconnected risks: technical unreliability, malicious use, and strategic instability arising from the security dilemma. Therefore, this article argues that AI governance cannot rely solely on technological improvements. Instead, it requires a governance path comprised of technical safeguards, risk-based regulation, and international cooperation. This should be achieved through testing, auditing, human-in-the-loop mechanisms, and confidence-building measures (CBMs) to mitigate the risks posed by technological errors, malicious misuse, and strategic miscalculations. Overall, the key to AI governance is not restricting AI's entry into the national security domain, but rather establishing corresponding control, oversight, and international coordination mechanisms while enhancing its security capabilities.<\/jats:p>","DOI":"10.54254\/2754-1169\/2026.37530","type":"journal-article","created":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T02:48:36Z","timestamp":1791427716000},"page":"None-None","source":"Crossref","is-referenced-by-count":0,"title":["Artificial Intelligence in National Security: Applications, Risks, and Governance Pathways"],"prefix":"10.54254","volume":"305","author":[{"given":"Qinghan","family":"Ji","sequence":"first","affiliation":[{"name":"University of Nottingham Ningbo China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"32523","published-online":{"date-parts":[[2026,10,8]]},"container-title":["Advances in Economics, Management and Political Sciences"],"original-title":[],"deposited":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T02:48:38Z","timestamp":1791427718000},"score":1,"resource":{"primary":{"URL":"https:\/\/aemps.ewapub.com\/article\/view\/37530"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,8]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,10,8]]}},"URL":"https:\/\/doi.org\/10.54254\/2754-1169\/2026.37530","relation":{},"ISSN":["2754-1169","2754-1177"],"issn-type":[{"value":"2754-1169","type":"print"},{"value":"2754-1177","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,8]]}}}