When Institutions Cannot Keep up with Artificial Intelligence: Expiration Theory and the Risk of Institutional Invalidation

Victor Frimpong ()
Additional contact information
Victor Frimpong: Management Department, SBS Swiss Business School, Flughafenstrasse 3, 8302 Kloten-Zurich, Switzerland

Administrative Sciences, 2025, vol. 15, issue 7, 1-22

Abstract: As Artificial Intelligence systems increasingly surpass or replace traditional human roles, institutions founded on beliefs in human cognitive superiority, moral authority, and procedural oversight encounter a more profound challenge than mere disruption: expiration. This paper posits that, instead of being outperformed, many legacy institutions are becoming epistemically misaligned with the realities of AI-driven environments. To clarify this change, the paper presents the Expiration Theory. This conceptual model interprets institutional collapse not as a market failure but as the erosion of fundamental assumptions amid technological shifts. In addition, the paper introduces the AI Pressure Clock, a diagnostic tool that categorizes institutions based on their vulnerability to AI disruption and their capacity to adapt to it. Through an analysis across various sectors, including law, healthcare, education, finance, and the creative industries, the paper illustrates how specific systems are nearing functional obsolescence while others are actively restructuring their foundational norms. As a conceptual study, the paper concludes by highlighting the theoretical, policy, and leadership ramifications, asserting that institutional survival in the age of AI relies not solely on digital capabilities but also on the capacity to redefine the core principles of legitimacy, authority, and decision-making.

Keywords: expiration theory; AI pressure clock; institutional expiration; assumption decay; institutional obsolescence; artificial intelligence and governance; institutional resilience; algorithmic disruption (search for similar items in EconPapers)
JEL-codes: L M M0 M1 M10 M11 M12 M14 M15 M16 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2076-3387/15/7/263/pdf (application/pdf)
https://www.mdpi.com/2076-3387/15/7/263/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jadmsc:v:15:y:2025:i:7:p:263-:d:1696144

Access Statistics for this article

Administrative Sciences is currently edited by Ms. Nancy Ma

More articles in Administrative Sciences from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().