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Vol. 12 No. 11 (2025)
International Multidisciplinary Journal for Research & Development

Articles

The Convergence of Algorithmic Sensemaking And Organizational Humanocracy: A Longitudinal Analysis Of AI-Driven Change Management And Risk Mitigation

Published 2025-11-30

  • Ronny Barman

Ronny Barman
Department of Management and Technology, University of Edinburgh, United Kingdom

Abstract

This research explores the profound intersection between human-centric organizational structures and the integration of artificial intelligence (AI) within modern management frameworks. By synthesizing classical management theories with contemporary algorithmic processing perspectives, this study investigates how "Humanocracy"-the liberation of human potential from bureaucratic constraints-interacts with the increasing reliance on automated decision-making. The paper evaluates the shift from traditional hierarchical control to decentralized, AI-augmented systems, focusing on the concepts of algorithmic sensemaking, transparency, and fairness. Utilizing a comprehensive review of theoretical literature, patent filings, and empirical studies, the research identifies a critical tension: while AI offers predictive precision and risk scoring capabilities, its effectiveness is contingent upon the human perception of its "humanness" and the organizational culture’s readiness for discontinuous change. The findings suggest that organizational value in the digital era is not derived solely from technical deployment but from the alignment of algorithmic transparency with human values. The study concludes with a strategic framework for "Responsible AI" in financial and organizational risk management, advocating for a shift from algorithm aversion to informed human-algorithm collaboration.

Keywords

Humanocracy, Algorithmic Sensemaking, Change Management, Artificial Intelligence

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References

  1. Aziz S, Dowling M (2019) Machine learning and AI for risk management. Disrupting finance: FinTech and strategy in the 21st century, 33-50.
  2. Bhati D, Maan A (2018) U.S. Patent No. 10,133,682. Washington, DC: U.S. Patent and Trademark Office.
  3. Brannon JB, Jones K, Pitchaimani S, Patton-Kuhl DD, Malladi R, Viswanathan S (2022) U.S. Patent No. 11,397,819. Washington, DC: U.S. Patent and Trademark Office.
  4. Drucker PF (1993) The practice of management, 1st edn. Harper Business, New York.
  5. Fritz-Morgenthal S, Hein B, Papenbrock J (2022) Financial risk management and explainable, trustworthy, responsible AI. Frontiers in artificial intelligence, 5, 779799.
  6. Hamel G, Zanini M (2020) Humanocracy: creating organizations as amazing as the people inside them. Harvard Business Review Press, Brighton.
  7. Herzberg F (1976) The managerial choice: to be efficient and to be human. Dow Jones-Irwin, Homewood.
  8. Huczynski A, Buchanan D (1991) Organizational behavior. New York.
  9. Jones K, Spaeth J, Rykowski A, Manjunath N, Vudutala SK, Malladi R, Mishra A (2018) U.S. Patent No. 10,057,117. Washington, DC: U.S. Patent and Trademark Office.
  10. Kamenov K (1995) Change Management. Veliko Tarnovo: Abagar.
  11. Kamenov K (2013) Basics of Management. Svishtov: "Tsenov".
  12. Karabelova S (2001) Values and cultural practices in Bulgaria. Sofia: "Classic and Style" Ltd.
  13. Katz D, Kahn RL (1966) The social psychology of organizations. Wiley, New York.
  14. Kim Y, Sundar SS (2012) Anthropomorphism of computers. Comput Hum Behav 28:241-250. https://doi.org/10.1016/j.chb.2011.09.006
  15. Koerber A, Lim J (2024) Impact of misinformation from generative AI on user information processing: how people understand misinformation on generative AI. New Media Soc. https://doi.org/10.1177/14614448241234040
  16. Kotter D, Cohen D (2003) The heart of change. Sofia: Classics and Style Ltd.
  17. Kreiner S (1998) Key ideas in management. Sofia: "InfoDAR" EOOD.
  18. Kulkov I, Kulkova J, Rohrbeck R, Menvielle L, Kaartemo V, Makkonen H (2024) Artificial intelligence-driven sustainable development: Examining organizational, technical, and processing approaches to achieving global goals. Sustainable Development, 32(3), 2253-2267.
  19. Lee M (2018) Understanding perception of algorithmic decisions. Big Data Soc 5(1):1-16. https://doi.org/10.1177/2053951718756684g22
  20. Lim J, Ahmad N, Ibarahim M (2024) Understanding user sensemaking in fairness and transparency in algorithms: algorithmic sensemaking in over-the-top platform. AI Soc 39:447-490. https://doi.org/10.1007/s00146-022-01525-9
  21. Malladi R, Bukkapattanam A, Wigley C, Aggarwal N, Vudutala SK (2021) U.S. Patent No. 11,087,020. Washington, DC: U.S. Patent and Trademark Office.
  22. Morewedge CK (2022) Preference for human, not algorithm aversion. Trends Cogn Sci 26(10):824-826. https://doi.org/10.1016/j.tics.2022.07.007
  23. Nadler DA, Shaw RB, Elise Walton A (1995) Discontinuous change: leading organizational transformation. Jossey-Bass, San Francisco.
  24. Nadler D, Tushman M. Beyond the Charismatic Leader: Leadership and Organizational. California Management Review, vol. 32, No. 2.
  25. Perifanis NA, Kitsios F (2023) Investigating the influence of artificial intelligence on business value in the digital era of strategy: A literature review. Information, 14(2), 85.
  26. Petrova E (2011) Perspectives on "Management of Change". Problems of postmodernity, Volume 1, no. 2.
  27. Rogers EM (1962) Diffusion of innovations. Free Press of Glencoe, New York.
  28. Santalainen T, Voutilainen E, Porenne P, Nissinen J (1988) Results management. Moscow: Progress.
  29. Shin D (2022) The perception of humanness in conversational journalism: an algorithmic information-processing perspective. New Media Soc 24(12):2680-2704. https://doi.org/10.1177/1461444821993801
  30. Shin DD (2023) Algorithms, humans, and interactions: how do algorithms interact with people? Designing meaningful AI experiences (1st ed.). Routledge. https://doi.org/10.1201/b23083
  31. Shin D (2024) Artificial misinformation: exploring human-algorithm interaction online. Springer Nature, Switzerland. https://doi.org/10.1007/978-3-031-52569-8
  32. Tekic Z, Füller J (2023) Managing innovation in the era of AI. Technology in Society, 73, 102254.
  33. Varanasi, S.R. (2025) AI for CAB Decisions: Predictive Risk Scoring in Change Management. International Research Journal of Advanced Engineering and Technology, 2(06), 16-22. https://doi.org/10.55640/irjaet-v02i06-03
  34. Xu H, Niu K, Lu T, Li S (2024) Leveraging artificial intelligence for enhanced risk management in financial services: Current applications and future prospects. Engineering Science & Technology Journal, 5 (8), 2402-2426.

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