Artificial Intelligence in Business Context: A qualitative study on how Artificial Intelligence influences business strategy adjustments
Abstract
Technological advancements are undoubtedly providing a significant support in increasing
operational efficiency of organizations from any industry. Organizations often suffer to cope with
the technological changes that they make, since it has become a regular process that happens at a
speed that is quite tough to trace. In the new era of the digital world, one example of technology
that is having tremendous attention to be the main driver of a disruptive change in the near future
is Artificial Intelligence (AI). Nevertheless, research on how Artificial Intelligence shapes business
context in terms of adjusting existing strategies lacks concentration. Hence, this research aims at
investigating how organizations are changing their internal strategies in order to cope with the AI
transformation. This has been achieved by conducting multiple case studies from three industries
including telecommunication, automobile, and clothing. The findings show that organizations
invest in AI when they see a great prospect of AI in terms of value creation. Unfortunately, the
expected level of value cannot be created until AI gets matured to some extent. Furthermore,
organizations need to align their existing strategies with AI strategy to diffuse the AI adoption
properly within the organization which will eventually create value. Additionally, the findings
show that the strategic changes are being performed in terms of staffing strategies, marketing
strategies and strategies related to processing internal software to some extent. In terms of decision
making with AI, the study suggests that a combination of humans and AI would facilitate making
better decisions rather than by only humans or only AI.
Degree
Master 2-years
Collections
View/ Open
Date
2022-07-05Author
Siju, Mariyam Akhter
Hasan, Refat Binte Umme
Keywords
Artificial Intelligent
strategic changes
internal strategies
value creation through technological innovation
value chain resilience
Series/Report no.
2022:13
Language
eng