IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2604.23058.html

The Security Cost of Intelligence: AI Capability, Cyber Risk, and Deployment Paradox

Author

Listed:
  • Sukwoong Choi

Abstract

Firms are deploying more capable AI systems, but organizational controls often have not kept pace. These systems can generate greater productivity gains, but high-value uses require broader authority exposure -- data access, workflow integration, and delegated authority -- when governance controls have not yet decoupled capability from authority exposure. We develop an analytical model in which a firm jointly chooses AI deployment and cybersecurity investment under this governance-capability gap. The central result shows a deployment paradox: in high-loss environments, better AI can lead a firm to deploy less when capability is deployed through broader authority exposure under weak governance. Optimal deployment also falls below the no-risk benchmark, and this shortfall widens with breach-loss magnitude and with the authority exposure attached to more capable systems. Governance investment that reduces breach-loss magnitude shrinks the paradox region itself, while breach externalities expand the range of environments in which deployment is socially constrained. Governance maturity is therefore not merely a constraint on AI adoption. It is a condition that shapes whether capability improvements translate into productive deployment.

Suggested Citation

  • Sukwoong Choi, 2026. "The Security Cost of Intelligence: AI Capability, Cyber Risk, and Deployment Paradox," Papers 2604.23058, arXiv.org.
  • Handle: RePEc:arx:papers:2604.23058
    as

    Download full text from publisher

    File URL: https://arxiv.org/pdf/2604.23058
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Francesco Bova & Avi Goldfarb & Roger G. Melko, 2023. "Quantum Economic Advantage," Management Science, INFORMS, vol. 69(2), pages 1116-1126, February.
    2. Erik Brynjolfsson & Danielle Li & Lindsey Raymond, 2025. "Generative AI at Work," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 140(2), pages 889-942.
    3. Alessandro Acquisti & Curtis Taylor & Liad Wagman, 2016. "The Economics of Privacy," Journal of Economic Literature, American Economic Association, vol. 54(2), pages 442-492, June.
    4. Agrawal, Ajay & Gans, Joshua S. & Goldfarb, Avi, 2019. "Exploring the impact of artificial Intelligence: Prediction versus judgment," Information Economics and Policy, Elsevier, vol. 47(C), pages 1-6.
    5. Collins, Christopher & Dennehy, Denis & Conboy, Kieran & Mikalef, Patrick, 2021. "Artificial intelligence in information systems research: A systematic literature review and research agenda," International Journal of Information Management, Elsevier, vol. 60(C).
    6. Yannis Bakos & Erik Brynjolfsson, 1999. "Bundling Information Goods: Pricing, Profits, and Efficiency," Management Science, INFORMS, vol. 45(12), pages 1613-1630, December.
    7. Lee, Yong Suk & Kim, Taekyun & Choi, Sukwoong & Kim, Wonjoon, 2022. "When does AI pay off? AI-adoption intensity, complementary investments, and R&D strategy," Technovation, Elsevier, vol. 118(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pehr-Johan Norbäck & Lars Persson, 2024. "Why generative AI can make creative destruction more creative but less destructive," Small Business Economics, Springer, vol. 63(1), pages 349-377, June.
    2. Yong Suk Lee & Benjamin Cedric Larsen & Jingxin Wu, 2025. "US-China tech decoupling increases willingness to share personal data in China," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-13, December.
    3. Shilei Luo & Zhiqi Zhang & Hengchen Dai & Dennis Zhang, 2026. "Behavioral Transfer in AI Agents: Evidence and Privacy Implications," Papers 2604.19925, arXiv.org.
    4. Hana Choi & Carl F. Mela & Santiago R. Balseiro & Adam Leary, 2020. "Online Display Advertising Markets: A Literature Review and Future Directions," Information Systems Research, INFORMS, vol. 31(2), pages 556-575, June.
    5. Park, Gangmin & Kang, Songhee & Yi, Sangyoon & Kim, Junyoun, 2026. "Diverse impacts of AI investments on productivity gains: Effects of industry and innovation characteristics," Technological Forecasting and Social Change, Elsevier, vol. 224(C).
    6. Bughin, Jacques, 2025. "Corporate AI play and short term skill-biased AI change," Technology in Society, Elsevier, vol. 82(C).
    7. Mariniello Mario, 2025. "Efficiency and Distributive Goals in the EU Tech Regulatory Strategy," Intereconomics: Review of European Economic Policy, Sciendo, vol. 60(3), pages 141-148.
    8. Crumbly, Jack & Pal, Raktim & Altay, Nezih, 2025. "A classification framework for generative artificial intelligence for social good," Technovation, Elsevier, vol. 139(C).
    9. Jian Pei, 2020. "A Survey on Data Pricing: from Economics to Data Science," Papers 2009.04462, arXiv.org, revised Nov 2020.
    10. J. K. Pappalardo, 2022. "Economics of Consumer Protection: Contributions and Challenges in Estimating Consumer Injury and Evaluating Consumer Protection Policy," Journal of Consumer Policy, Springer, vol. 45(2), pages 201-238, June.
    11. Vaubourg, Anne-Gael, 2006. "Differentiation and discrimination in a duopoly with two bundles," International Journal of Industrial Organization, Elsevier, vol. 24(4), pages 753-762, July.
    12. Stefano Galavotti, 2014. "Reducing Inefficiency in Public Good Provision Through Linking," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 16(3), pages 427-466, June.
    13. Luigi Zingales, 2022. "Regulating big tech," BIS Working Papers 1063, Bank for International Settlements.
    14. Tarek Abdallah, 2019. "On the Benefit (Or Cost) of Large‐Scale Bundling," Production and Operations Management, Production and Operations Management Society, vol. 28(4), pages 955-969, April.
    15. Abendroth Dias Kulani & Arias Patricia & Bacco F. Manlio & Bassani Elias & Bertoletti Alice & Bertolini Lorenzo & Bertrand Astrid & Bili Danai & Boucher Philip & Cachia Romina & Ceresa Mario & Chaslot, 2025. "Generative AI Outlook Report," JRC Research Reports JRC142598, Joint Research Centre.
    16. Zara Contractor & Germ'an Reyes, 2025. "Generative AI in Higher Education: Evidence from an Elite College," Papers 2508.00717, arXiv.org, revised Apr 2026.
    17. Cheng, Qiang & Lin, Pengkai & Zhao, Yue, 2025. "Does generative AI facilitate investor Trading? Early evidence from ChatGPT outages," Journal of Accounting and Economics, Elsevier, vol. 80(2).
    18. Yanwen Wang & Chunhua Wu & Ting Zhu, 2019. "Mobile Hailing Technology and Taxi Driving Behaviors," Marketing Science, INFORMS, vol. 38(5), pages 734-755, September.
    19. Rahul Deb & Anne-Katrin Roesler, 2024. "Multi-Dimensional Screening: Buyer-Optimal Learning and Informational Robustness," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 91(5), pages 2744-2770.
    20. Christos Makridis & Christos A. Makridis, 2026. "The Sum of All (Workplace) Fears: How Managers Mediate the Fear of AI Job Displacement," CESifo Working Paper Series 12678, CESifo.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2604.23058. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: https://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.