Real-world application of data-driven and intelligent systems (AI) is increasing in the private and public sector as well as in society at large. Many organizations transform as a consequence of increased AI implementation. The consequences of such transformations may include new recruitment plans, procurement of additional IT, changes in existing positions and roles, new business models, as well as new policies and regulations. However, it is unclear how this transformation varies across different types of organizations.
The digital transformation of society has been steadily increasing during the last five decades. The Internet era of the last two decades has boosted this development and it has made possible the information sharing between individuals and organizations, and across nations, that we experience today. The early industrialization, later industrialization, and the digital transformation along with the introduction of renewable energy sources, are referred to as the first, second, and third industrial revolution. We are now entering the era of the fourth industrial revolution.
The advent of social media and electronic commerce platforms, such as Amazon, Facebook, and Twitter -- along with the development of cheaper and more powerful hardware -- has significantly increased real-world application of connected, data-driven and intelligent systems (AI) in the private and public sectors as well as in society at large. As was the case in earlier societal revolutions, old systems, schools of thought, organizations, jobs, and cultures will change or disappear. However, we argue that the AI revolution -- the shifting of the cognitive workload from humans to computers -- may have characteristics and consequences quite unlike the earlier revolutions.
Our goal is to acquire an improved understanding of how and when AI transformation occurs in the organization, which are the consequences, and which strategies are fruitful or detrimental to the organization.
We believe the strategic planning, organizational culture, and decision-making processes differ significantly between typical public and private sector organizations.
Our ambition is to develop and validate an efficient and effective framework and workflow to perform AI transformation in organizations and help them in the adoption of these technologies.
Interested in finding out more?