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Dergiler / Black Sea Journal of Engineering and Science / 2026 / Cilt: 9 Sayı: 5

Assessing Readiness for AI-Human Integration Using a Hesitant Fuzzy Analytic Hierarchy Process: An Application in the Banking Sector

Çağrı Akoğlu(Bahçeşehir Üniversitesi)0009-0003-8293-8173
Gül Tekin Temur(BAHÇEŞEHİR ÜNİVERSİTESİ)0000-0003-3853-0974
Sayfa
2463–2473
Yayın Tarihi
2026-09-15
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The resulting index not only quantifies an organization’s current state of readiness but also acts as a diagnostic tool to assist organizations in identifying areas where they may require additional support or training.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:With AI being incorporated into the core functions of organizations, understanding whether or not an organization is ready to work in conjunction with humans using AI will continue to grow in importance.
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Temel Bulgular & Veri:A total of four primary dimensions were used in developing the model which were established from conducting a thorough review of existing literature: (1) Strategic Alignment & Value Realization Readiness, (2) Data & Technical Infrastructure Readiness, (3) Human Capital & Adaptation Readiness, and (4) Trust, Governance & Institutional Legitimacy Readiness.
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Sonuç & Katkı:The resulting index not only quantifies an organization’s current state of readiness but also acts as a diagnostic tool to assist organizations in identifying areas where they may require additional support or training.
🔬Tür:Literatür & Derleme Çalışması
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Multi-criteria decision making · AI-human integration · AI-human integration readiness level

Özet

With AI being incorporated into the core functions of organizations, understanding whether or not an organization is ready to work in conjunction with humans using AI will continue to grow in importance. Therefore, this study proposes a multi criteria decision making (MCDM) based methodology to aid firms in evaluating their potential for successful integration of AI and human capabilities. An “AI-Human Integration Readiness Index” is developed to provide a systematic means to evaluate the various capabilities regarding to AI utilization. In order to handle uncertainty and hesitation when experts are making assessments of an organization’s readiness, the proposed methodology uses the Hesitant Fuzzy Analytical Hierarchy Process (HFAHP) as a novel MCDM method. A total of four primary dimensions were used in developing the model which were established from conducting a thorough review of existing literature: (1) Strategic Alignment & Value Realization Readiness, (2) Data & Technical Infrastructure Readiness, (3) Human Capital & Adaptation Readiness, and (4) Trust, Governance & Institutional Legitimacy Readiness. The resulting index not only quantifies an organization’s current state of readiness but also acts as a diagnostic tool to assist organizations in identifying areas where they may require additional support or training.

Abstract

With AI being incorporated into the core functions of organizations, understanding whether or not an organization is ready to work in conjunction with humans using AI will continue to grow in importance. Therefore, this study proposes a multi criteria decision making (MCDM) based methodology to aid firms in evaluating their potential for successful integration of AI and human capabilities. An “AI-Human Integration Readiness Index” is developed to provide a systematic means to evaluate the various capabilities regarding to AI utilization. In order to handle uncertainty and hesitation when experts are making assessments of an organization’s readiness, the proposed methodology uses the Hesitant Fuzzy Analytical Hierarchy Process (HFAHP) as a novel MCDM method. A total of four primary dimensions were used in developing the model which were established from conducting a thorough review of existing literature: (1) Strategic Alignment & Value Realization Readiness, (2) Data & Technical Infrastructure Readiness, (3) Human Capital & Adaptation Readiness, and (4) Trust, Governance & Institutional Legitimacy Readiness. The resulting index not only quantifies an organization’s current state of readiness but also acts as a diagnostic tool to assist organizations in identifying areas where they may require additional support or training.

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Bu Makaleye Atıf Yap

Akoğlu, Ç., Temur, G. T. (2026). Assessing Readiness for AI-Human Integration Using a Hesitant Fuzzy Analytic Hierarchy Process: An Application in the Banking Sector. Black Sea Journal of Engineering and Science, Cilt: 9 Sayı: 5, 2463–2473. https://doi.org/10.34248/bsengineering.1956549

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Kaynakça (26)

  1. Akbarighatar, P., Pappas, I., & Vassilakopoulou, P. (2023). A sociotechnical perspective for responsible AI maturity models: Findings from a mixed-method literature review. International Journal of Information Management Data Insights, 3(2), Article 100193. https://doi.org/10.1016/j.jjimei.2023.100193
  2. Akdil, K. Y., Ustundag, A., & Cevikcan, E. (2018). Maturity and readiness model for Industry 4.0 strategy. In A. Ustundag & E. Cevikcan (Eds.), Industry 4.0: Managing the digital transformation (pp. 61–94). Springer. https://doi.org/10.1007/978-3-319-57870-5_4
  3. Armenakis, A. A., Harris, S. G., & Mossholder, K. W. (1993). Creating readiness for organizational change. Human Relations, 46(6), 681–703. https://doi.org/10.1177/001872679304600601
  4. Braganza, A., Chen, W., Canhoto, A., & Sap, S. (2021). Productive employment and decent work: The impact of AI adoption on psychological contracts, job engagement and employee trust. Journal of Business Research, 131, 485–494. https://doi.org/10.1016/j.jbusres.2020.08.018
  5. Holmström, J. (2022). From AI to digital transformation: The AI readiness framework. Business Horizons, 65(3), 329–339. https://doi.org/10.1016/j.bushor.2021.03.006
  6. Jöhnk, J., Weißert, M., & Wyrtki, K. (2021). Ready or not, AI comes—An interview study of organizational AI readiness factors. Business & Information Systems Engineering, 63(1), 5–20. https://doi.org/10.1007/s12599-020-00676-7
  7. Kinkel, S., Baumgartner, M., & Cherubini, E. (2022). Prerequisites for the adoption of AI technologies in manufacturing: Evidence from a worldwide sample of manufacturing companies. Technovation, 110, Article 102375. https://doi.org/10.1016/j.technovation.2021.102375
  8. Lichtblau, K., Stich, V., Bertenrath, R., Blum, M., Bleider, M., Millack, A., Schmitt, K., Schmitz, E., & Schröter, M. (2015). IMPULS—Industrie 4.0-readiness. Impuls-Stiftung des VDMA.
  9. Liu, H., & Rodríguez, R. M. (2014). A fuzzy envelope for hesitant fuzzy linguistic term set and its application to multicriteria decision making. Information Sciences, 258, 220–238. https://doi.org/10.1016/j.ins.2013.07.027
  10. Mankins, J. C. (2009). Technology readiness assessments: A retrospective. Acta Astronautica, 65(9–10), 1216–1223. https://doi.org/10.1016/j.actaastro.2009.03.058
  11. Mettler, T. (2011). Maturity assessment models: A design science research approach. International Journal of Society Systems Science, 3(1/2), 81–98. https://doi.org/10.1504/IJSSS.2011.038934
  12. Mylrea, M., & Robinson, N. (2023). Artificial intelligence (AI) trust framework and maturity model: Applying an entropy lens to improve security, privacy, and ethical AI. Entropy, 25(10), Article 1429. https://doi.org/10.3390/e25101429
  13. Naheed, S., Pinto, R., & Pirola, F. (2025). A preliminary multidimensional AI readiness assessment model for SME’s. Procedia Computer Science, 253, 774–783. https://doi.org/10.1016/j.procs.2025.01.139
  14. Nazari Tehrani, A., Ray, S., Roy, S. K., Gruner, R. L., & Appio, F. P. (2024). Decoding AI readiness: An in-depth analysis of key dimensions in multinational corporations. Technovation, 131, Article 102948. https://doi.org/10.1016/j.technovation.2023.102948
  15. Nortje, M. A., & Grobbelaar, S. S. (2020). A framework for the implementation of artificial intelligence in business enterprises: A readiness model. In 2020 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC) (pp. 1–10). IEEE. https://doi.org/10.1109/ICE/ITMC49519.2020.9198436
  16. Öztayşi, B., Onar, S. C., Bolturk, E., & Kahraman, C. (2015). Hesitant fuzzy analytic hierarchy process. In 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (pp. 1–7). IEEE. https://doi.org/10.1109/FUZZ-IEEE.2015.7337948
  17. Proença, D., & Borbinha, J. (2016). Maturity models for information systems—A state of the art. Procedia Computer Science, 100, 1042–1049. https://doi.org/10.1016/j.procs.2016.09.279
  18. Saaty, T. L. (1980). The analytic hierarchy process. McGraw-Hill.
  19. Saaty, T. L. (2012). Decision making for leaders: The analytic hierarchy process for decisions in a complex world (3rd rev. ed.). RWS Publications.
  20. Sauser, B. J., Long, M., Forbes, E., & McGrory, S. E. (2009). Defining an integration readiness level for defense acquisition. INCOSE International Symposium, 19(1), 352–367. https://doi.org/10.1002/j.2334-5837.2009.tb00953.x
  21. Schumacher, A., Erol, S., & Sihn, W. (2016). A maturity model for assessing Industry 4.0 readiness and maturity of manufacturing enterprises. Procedia CIRP, 52, 161–166. https://doi.org/10.1016/j.procir.2016.07.040
  22. Smit, J., Kreutzer, S., Moeller, C., & Carlberg, M. (2016). Industry 4.0. European Parliament, Policy Department A: Economic and Scientific Policy. https://doi.org/10.2861/947880
  23. Taherizadeh, A., & Beaudry, C. (2023). An emergent grounded theory of AI-driven digital transformation: Canadian SMEs’ perspectives. Industry and Innovation, 30(9), 1244–1273. https://doi.org/10.1080/13662716.2023.2242285
  24. Torra, V. (2010). Hesitant fuzzy sets. International Journal of Intelligent Systems, 25(6), 529–539. https://doi.org/10.1002/int.20418
  25. Uren, V., & Edwards, J. S. (2023). Technology readiness and the organizational journey towards AI adoption: An empirical study. International Journal of Information Management, 68, Article 102588. https://doi.org/10.1016/j.ijinfomgt.2022.102588
  26. Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X