From Infrastructure Assets to Infrastructure Intelligence: Reimagining Civil Engineering for an Era of Artificial Intelligence, Climate Uncertainty, and Autonomous Infrastructure Systems

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Thabo Jena

Civil engineering enters the second quarter of the twenty-first century carrying a conceptual inheritance it has rarely interrogated directly. This paper advances a single, falsifiable thesis: the defining failure of twentieth-century civil engineering was not a failure of materials, computation, or design method, but a category error in the treatment of infrastructure as a class of physical assets to be optimized rather than as a class of adaptive, decision-making systems operating under irreducible uncertainty.


We call this inheritance the Asset Paradigm and argue that it persists because it is embedded in codes, procurement, liability law, curricula, and professional identity, not because it remains effective. Building on, and formally sharpening, the emerging literature on infrastructure intelligence and resilience, we contribute: (i) necessary and sufficient conditions that distinguish Infrastructure Intelligence from smart infrastructure, digital twins, and cyber-physical systems, together with a quantitative formalization; (ii) a five-stage Infrastructure Evolution Model, classifying real systems by the locus of run-time decision authority and justified against maturity-model precedents from other engineering domains; (iii) four empirically testable propositions, each with explicit variables, candidate datasets, and validation methods; (iv) an illustrative bridge structural-health-monitoring application; (v) a phased, institutionally feasible transition pathway; and (vi) a ten-item Grand Research Agenda for 2025–2050. We position the framework against complex adaptive systems, socio-technical, resilience, adaptive-governance, and deep-uncertainty theory, and identify precisely where each breaks down under conditions of artificial intelligence, climate non-stationarity, and machine-speed autonomy. We conclude with a set of concrete claims and institutional commitments.

From Infrastructure Assets to Infrastructure Intelligence: Reimagining Civil Engineering for an Era of Artificial Intelligence, Climate Uncertainty, and Autonomous Infrastructure Systems. (2026). International Journal of Latest Technology in Engineering Management & Applied Science, 15(6), 3213-3234. https://doi.org/10.51583/IJLTEMAS.2026.150600237

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References

M. Amin, “Toward self-healing energy infrastructure systems,” IEEE Computer Applications in Power, vol. 14, no. 1, pp. 20–28, 2001.

W. B. Arthur, “Complexity and the economy,” Science, vol. 284, no. 5411, pp. 107–109, 1999.

C. Axenie, M. Akbarzadeh, M. A. Makridis, M. Saveriano, and A. Stancu, Applied Antifragility in Technical Systems: From Principles to Applications. Cham: Springer Nature, 2025.

R. Bommasani et al., “On the Opportunities and Risks of Foundation Models,” arXiv preprint arXiv:2108.07258, 2021.

CMMI Product Team, CMMI for Development, Version 1.3 (CMU/SEI-2010-TR-033). Pittsburgh, PA: Software Engineering Institute, Carnegie Mellon University, 2010.

N. Dalkey and O. Helmer, “An experimental application of the Delphi method to the use of experts,” Management Science, vol. 9, no. 3, pp. 458–467, 1963.

C. Folke, “Resilience: the emergence of a perspective for social, ecological systems analyses,” Global Environmental Change, vol. 16, no. 3, pp. 253–267, 2006.

C. Folke, T. Hahn, P. Olsson, and J. Norberg, “Adaptive governance of social-ecological systems,” Annual Review of Environment and Resources, vol. 30, pp. 441–473, 2005.

F. W. Geels, “From sectoral systems of innovation to socio-technical systems,” Research Policy, vol. 33, no. 6–7, pp. 897–920, 2004.

M. Haasnoot, J. H. Kwakkel, W. E. Walker, and J. ter Maat, “Dynamic adaptive policy pathways: a method for crafting robust decisions for a deeply uncertain world,” Global Environmental Change, vol. 23, no. 2, pp. 485–498, 2013.

J. H. Holland, “Complex adaptive systems,” Daedalus, vol. 121, no. 1, pp. 17–30, 1992.

C. S. Holling, “Resilience and stability of ecological systems,” Annual Review of Ecology and Systematics, vol. 4, pp. 1–23, 1973.

INCOSE, Systems Engineering Handbook: A Guide for System Life Cycle Processes and Activities, 4th ed. Hoboken, NJ: Wiley, 2015.

F. Jiang, L. Ma, T. Broyd, and K. Chen, “Digital twin and its implementations in the civil engineering sector,” Automation in Construction, vol. 130, art. 103838, 2021.

Y. Jiang, J. Wang, X. Shen, and K. Dai, “Large language model for post-earthquake structural damage assessment of buildings,” Computer-Aided Civil and Infrastructure Engineering, vol. 40, no. 31, pp. 6324–6342, 2025.

J. H. Kwakkel, M. Haasnoot, and W. E. Walker, “Developing dynamic adaptive policy pathways: a computer-assisted approach for developing adaptive strategies for a deeply uncertain world,” Climatic Change, vol. 132, no. 3, pp. 373–386, 2015.

E. A. Lee, “Cyber physical systems: design challenges,” in Proc. 11th IEEE Int. Symp. Object and Component-Oriented Real-Time Distributed Computing, 2008, pp. 363–369.

R. J. Lempert, S. W. Popper, and S. C. Bankes, Shaping the Next One Hundred Years: New Methods for Quantitative, Long-Term Policy Analysis. Santa Monica, CA: RAND Corporation, 2003.

R. G. Little, “Controlling cascading failure: understanding the vulnerabilities of interconnected infrastructures,” Journal of Urban Technology, vol. 9, no. 1, pp. 109–123, 2002.

J. Liu, Z. Geng, R. Cao, L. Cheng, P. Bocchini, and M. Cheng, “A large language model-empowered agent for reliable and robust structural analysis,” Structure and Infrastructure Engineering, 2026.

J. Markard, R. Raven, and B. Truffer, “Sustainability transitions: an emerging field of research and its prospects,” Research Policy, vol. 41, no. 6, pp. 955–967, 2012.

J. Michael, J. Blankenbach, J. Derksen, B. Finklenburg, R. Fuentes, T. Gries, S. Hendiani, S. Herlé, S. Hesseler, M. Kimm, et al., “Integrating models of civil structures in digital twins: state-of-the-art and challenges,” Journal of Infrastructure Intelligence and Resilience, vol. 3, no. 3, art. 100100, 2024.

P. Michailidis, I. Michailidis, C. R. Lazaridis, and E. Kosmatopoulos, “Traffic signal control via reinforcement learning: a review on applications and innovations,” Infrastructures, vol. 10, no. 5, art. 114, 2025.

P. C. D. Milly, J. Betancourt, M. Falkenmark, R. M. Hirsch, Z. W. Kundzewicz, D. P. Lettenmaier, and R. J. Stouffer, “Stationarity is dead: whither water management?” Science, vol. 319, no. 5863, pp. 573–574, 2008.

National Institute of Standards and Technology (NIST), AI Risk Management Framework (AI RMF 1.0). Gaithersburg, MD: U.S. Department of Commerce, 2023.

T. Nyokum and Y. Tamut, “Artificial intelligence in civil engineering: emerging applications and opportunities,” Frontiers in Built Environment, vol. 11, art. 1622873, 2025.

A. O’Connor, Rethinking Infrastructure as Assets: Policy, Regulation and Design. London: Routledge, 2019.

E. Ostrom, “Beyond markets and states: polycentric governance of complex economic systems,” American Economic Review, vol. 100, no. 3, pp. 641–672, 2010.

SAE International, J3016_202104: Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles. Warrendale, PA: SAE International, 2021.

H. Shokravi, M. Vafaei, B. Samali, and N. Bakhary, “In-fleet structural health monitoring of roadway bridges using connected and autonomous vehicles’ data,” Computer-Aided Civil and Infrastructure Engineering, vol. 39, no. 14, pp. 2122–2139, 2024.

N. N. Taleb, Antifragile: Things That Gain from Disorder. New York: Random House, 2012.

M. Torzoni, M. Tezzele, S. Mariani, A. Manzoni, and K. E. Willcox, “A digital twin framework for civil engineering structures,” Computer Methods in Applied Mechanics and Engineering, vol. 418, art. 116584, 2024.

E. L. Trist and K. W. Bamforth, “Some social and psychological consequences of the longwall method of coal-getting,” Human Relations, vol. 4, no. 1, pp. 3–38, 1951.

S. Youwai, D. Phim, V. G. Murcia, and R. C. Onas, “Large language model-based multi-agent systems for automated foundation design: router-driven task classification and expert selection framework,” AI in Civil Engineering, vol. 5, no. 1, art. 5, 2026.

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From Infrastructure Assets to Infrastructure Intelligence: Reimagining Civil Engineering for an Era of Artificial Intelligence, Climate Uncertainty, and Autonomous Infrastructure Systems. (2026). International Journal of Latest Technology in Engineering Management & Applied Science, 15(6), 3213-3234. https://doi.org/10.51583/IJLTEMAS.2026.150600237