Daicy Vaz

• Pereira, Vijay; Vaz, Daicy; Malik, Ashish & Ali, Faiza (2024). Cui Bono? Cow Slaughter ban and its impact on business and society in India. Organization. ISSN 1350-5084. Full text in Research Archive
• Vaz, Daicy; Pereira, Vijay; Bamal, Nisha; Bamel, Umesh & Behl, Abhishek (2024). Evaluating the resource orchestration of evolving disruptive technologies within ecosystem-based business models: evidence from the Indian railways. Journal of Technology Transfer. ISSN 0892-9912. Full text in Research Archive

View all works in NVA

• Vaz, Daicy (2026). Unbundling the Complexities, Duality and Intertwining of Strategic and Sustainable AI in Organizations. Universitetet i Agder. ISSN 9788284273419. Full text in Research Archive Show summary

  Globally, organizations are in a constant race to be among the first to develop and adopt new technologies. This research focuses on one such technology: Artificial Intelligence (AI). With AI at the forefront of technological development over the past decade, leading companies (as well as others) have invested significant time and financial resources into exploring and exploiting its potential. While a few have succeeded, most have not. This thesis, through a systematic literature review, identifies the reason for this failure of the AI implementation process as the use of non-strategic approaches in deploying AI within the organization. This thesis identifies possible reasons behind these concerns and proposes the concept of ‘Strategic and Sustainable AI (SSAI)’, which refers to organizations being simultaneously strategic and sustainable during AI adoption. Being strategic here refers to following the three phases of strategic management, i.e., strategic thinking, strategic planning and strategic implementation; whereas sustainability refers to working in the interest of the Triple Bottom Line (TBL): people, planet and profit. In this vein, this thesis derives key capabilities that organizations must develop through the three stages of strategic management, via interviews conducted with 21 senior management executives from companies that have implemented AI. These capabilities include AI-driven leadership, opportunistic adoption, resource management, foreseen challenges, embracing flexibility, monitoring measurable outcomes, gaining competitive advantage and measuring tangible and intangible outcomes. Moreover, the findings of a survey conducted with 249 employees working with AI in organizations across the world show that low peer (managerial) influence aids strategic AI adoption. In other words, where a strategy for AI adoption is in place, peer influence is at its lowest. Additionally, examination of the survey results reveals that the direct effect of peer influence on sustainable AI adoption is not significant. Moreover, when peer influence is low, employees’ individual commitment to strategic AI implementation is high. Finally, this thesis provides evidence that sustainable AI adoption is achieved only through strategic management, thereby empirically establishing the concept of ‘Strategic and Sustainable AI (SSAI)’.

View all works in NVA