Adaptive Strategy in the Age of Machines: Investigating the Synergy between AI-Enabled Foresight and Leadership Agility

Abstract

This study explores the synergy between AI-enabled foresight and leadership agility in driving adaptive organisational strategies within dynamic digital environments. Through a descriptive literature review using manual thematic analysis, it synthesises 45 peer-reviewed studies from 2015–2025. Key themes include the conceptualisation of AI-enabled foresight and leadership agility, theoretical frameworks for their integration, synergistic effects on adaptive strategy, implementation challenges, and ethical considerations in AI-driven decision-making. Findings highlight that AI foresight, via predictive analytics and scenario modeling, enhances strategic flexibility, while leadership agility enables rapid adaptation, fostering innovation and competitive advantage. However, organisational resistance, skills gaps, and ethical concerns like transparency pose barriers. A proposed framework integrates AI foresight and agility to drive strategic outcomes. Practical recommendations include change management, leadership upskilling, and transparent AI processes. Future research should prioritise longitudinal, cross-cultural, and industry-specific studies to validate findings and address gaps, advancing understanding of AI-leadership synergy for organisational adaptability.

Introduction

Artificial intelligence (AI) has significantly transformed organizational strategy and leadership by enabling data-driven decision-making, predictive analytics, and dynamic responses to volatile markets. Traditional static strategic models are inadequate in rapidly changing digital environments, highlighting the need for strategic agility and leadership adaptability supported by AI.

This paper identifies a gap in existing literature concerning the integration of AI-enabled foresight (predictive analytics and scenario modeling) and leadership agility (cognitive flexibility and rapid decision-making). It conducts a systematic literature review (2015–2025) analyzing how these elements combine to support adaptive organizational strategies.

Key findings reveal five main themes:

1. Conceptualization: AI foresight involves anticipating future trends, while leadership agility is the capacity to adapt swiftly; current research often separates technical AI capabilities from behavioral leadership aspects.

2. Theoretical Frameworks: Integration relies mainly on dynamic capabilities and technology acceptance theories but lacks interdisciplinary models bridging AI and leadership behaviors.

3. Synergistic Effects: Combined, AI foresight and leadership agility enhance strategic flexibility and innovation, but benefits depend on organizational readiness and culture.

4. Implementation Challenges: Barriers include resistance to AI, lack of technical skills, data issues, and weak change management.

5. Ethical Considerations: Transparency, trust, accountability, and aligning AI use with organizational values are critical but inconsistently addressed.

The review emphasizes the need for integrated theoretical frameworks, improved leadership development focusing on AI literacy and emotional resilience, better change management practices, and transparent AI governance. It also notes methodological limitations, including a Western-centric research bias and predominance of qualitative studies.

Conclusion

This study significantly advances the understanding of the synergy between AI-enabled foresight and leadership agility in fostering adaptive organisational strategies. By synthesising 45 peer-reviewed studies from 2015–2025, it reveals that AI-enabled foresight, encompassing predictive analytics and scenario modeling, enhances strategic decision-making by anticipating market trends (Carayannis et al., 2025). Leadership agility, characterised by cognitive flexibility and rapid adaptation, enables leaders to leverage these insights, driving strategic flexibility and innovation (Ngui, 2025). The synergy strengthens dynamic capabilities, yielding competitive advantages, though implementation challenges like resistance and skills gaps persist (Laamanen et al., 2025; Fredriksson, 2018). Ethical considerations, particularly transparency in AI-driven decisions, are critical to maintaining trust (Pandey, 2025). The proposed framework, integrating AI foresight as an input to leadership agility, bridges technical and behavioral theories, offering a holistic lens for adaptive strategy (Hossain et al., 2025). Methodologically, manual thematic analysis proves effective for synthesising interdisciplinary insights, addressing conceptual, theoretical, and practical dimensions of the research question (Budianto et al., 2025).

References

[1] Abbas, S.M., Latif, M. and Sarwar, F., 2024. Digital leadership and innovative work behavior in it sector: The mediating role of digital entrepreneurial orientation and digital organisational culture. Employee Responsibilities and Rights Journal, pp.1-22. [2] Atienza-Barba, M., del Río, M.D.L.C., Meseguer-Martínez, Á. and Barba-Sanchez, V., 2024. Artificial intelligence and organisational agility: An analysis of scientific production and future trends. European Research on Management and Business Economics, 30(2), p.100253. [3] Barba, M.A., del Río, M.D.L.C., Martínez, Á.M. and Sánchez, V.B., 2024. Artificial intelligence and organisational agility: an analysis of scientific production and future trends. European Research on Management and Business Economics, 30(2), pp.133-145. [4] Basias, N. and Pollalis, Y., 2018. Quantitative and qualitative research in business & technology: Justifying a suitable research methodology. Review of Integrative Business and Economics Research, 7, pp.91-105. [5] Braun, V. and Clarke, V., 2006. Using thematic analysis in psychology. Qualitative research in psychology, 3(2), pp.77-101. [6] Budianto, S., Rahadian, D. and Yunita, I., 2025. The Emerging Landscape of AI-Powered Leadership: Transforming Roles and Organisations. Journal of Lifestyle and SDGs Review, 5(2), pp.e04139-e04139. [7] Bullock, S., Ajmeri, N., Batty, M., Black, M., Cartlidge, J., Challen, R., Chen, C., Chen, J., Condell, J., Danon, L. and Dennett, A., 2024. Artificial intelligence for collective intelligence: a national-scale research strategy. The Knowledge Engineering Review, 39, p.e10. [8] Carayannis, E.G., Dumitrescu, R., Falkowski, T., Papamichail, G. and Zota, N.R., 2025. Enhancing SME resilience through artificial intelligence and strategic foresight: A framework for sustainable competitiveness. Technology in Society, 81, p.102835. [9] Davidavi?ien?, V., 2018. Research methodology: An introduction. In Modernizing the academic teaching and research environment: Methodologies and cases in business research (pp. 1-23). Cham: Springer International Publishing. [10] Fredriksson, S., 2018. Organisational adaptation towards artificial intelligence: A case study at a public organisation. [11] Hasan, R., 2025. ENHANCING MARKET COMPETITIVENESS THROUGH AI-POWERED SEO AND DIGITAL MARKETING STRATEGIES IN E-COMMERCE. ASRC Procedia: Global Perspectives in Science and Scholarship, 1(01), pp.465-500. [12] Henderikx, M. and Stoffers, J., 2023. Digital transformation and middle managers’ leadership skills and behavior: a group concept mapping approach. Frontiers in psychology, 14, p.1147002. [13] Hossain, S., Fernando, M. and Akter, S., 2025. Digital leadership: Towards a dynamic managerial capability perspective of artificial intelligence-driven leader capabilities. Journal of Leadership & Organisational Studies, 32(2), pp.189-208. [14] Hossain, S., Fernando, M. and Akter, S., 2025. The influence of artificial intelligence-driven capabilities on responsible leadership: A future research agenda. Journal of Management & Organisation, pp.1-25. [15] Kendzierskyj, S., Jahankhani, H., Jamal, A., Hussien, O. and Yang, L., 2023. The role of blockchain with a cybersecurity maturity model in the governance of higher education supply chains. In AI, Blockchain and Self-Sovereign Identity in Higher Education (pp. 1-35). Cham: Springer Nature Switzerland. [16] Laamanen, T., Weiser, A.K., von Krogh, G. and Ocasio, W., 2025. Artificial Intelligence in Adaptive Strategy Creation and Implementation: Toward Enhanced Attentional Control in Strategy Processe. Long Range Planning, p.102561. [17] Lal, S. and Arora, M., 2025, May. Nexus of Digital Leadership and Workplace Dynamics: Evidence from Selected Private Universities in Uttarakhand, India. In Sustainability in emerging economies-Integrating business excellence in management education (SEE-IBEME-2024) (pp. 328-342). Atlantis Press. [18] Mohajan, H.K., 2018. Qualitative research methodology in social sciences and related subjects. Journal of economic development, environment and people, 7(1), pp.23-48. [19] Ngui, T.K., 2025. Artificial Intelligence and Leadership Agility: Concepts and their Application. International Journal of Research and Innovation in Social Science, 9(14), pp.464-476. [20] Paladugu, A., Fernandes, A. and IJtsma, M., 2025. Computational Simulation of Distributed Work as a Discovery Tool for Envisioning Future Operations. Journal of Cognitive Engineering and Decision Making, p.15553434251327698. [21] Pandey, V., 2025. Leadership in the AI Era: Navigating and shaping the future of organisational guidance. Available at SSRN 5331975. [22] Patel, M. and Patel, N., 2019. Exploring research methodology. International Journal of Research and Review, 6(3), pp.48-55. [23] Porter, D.B., Campbell, C., Jones, H., Logan-Fleming, D. and Sankey, M., 2024. Innovation Through Disruption in Australasia: The 2024 Contextualising Horizon Report. ASCILITE. [24] Snyder, H., 2019. Literature review as a research methodology: An overview and guidelines. Journal of business research, 104, pp.333-339. [25] Usul, H. and Alpay, B.Y., 2025. Digital Transformation in Internal Audit: Paradigm Shifts, Emerging Risks, and Strategic Resilience. European Journal of Digital Economy Research, 6(1), pp.23-36. [26] Warin, T. and Elimam, S., 2025. GDP 5.0: Real-Time, Micro-Founded and Sustainable Metrics for Beyond-GDP Economic Assessment (No. 2025s-20). CIRANO.

Copyright

Copyright © 2025 Dr. Abhijit Ganguly. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.