This represents a dilemma in the companies' environment; it is important to balance between being an early adopter of technology, such as AI – and investing in the right technology that complies with current norms, ethics and values. Therefore, it will be appropriate to continuously improve and adapt strategy, organization and management through business model innovation in line with demands from both the technological and institutional environment to ensure long-term competitive advantage.
These are the key findings from a new master thesis from the Western Norway University of Applied Sciences (Høgskulen på Vestlandet). The aim of the study has been to research how innovation companies in the Norwegian Media Cluster relate to and handle AI, in addition to explain how AI is used in the companies’ business models. The study is conducted by students Martine Brandal Øvrelid and Runa Elin Fjelle – who also spent their internship in the cluster organization, NCE Media.
The qualitative multiple case study’s empiricism is based on interviews with key players in the Norwegian Media Cluster; Vimond, IBM, Mjoll and TV 2 as case companies, in addition to interviews with NCE Media, Beat Technology and the Norwegian Government Security and Service Organization.
All of the case companies use AI in the category of machine learning, despite the fact that the technology is far from optimal at present. However, it is rapidly improving. Specifically, the findings indicate that use of machine learning in work processes, related to automatic speech recognition (ASR), natural language processing (NLP), natural language understanding (NLU) and natural language generation (NLG), provides the greatest value.
A dilemma between forces for change and ethics
The study has uncovered that AI, in certain areas, probably will provide greater value in interaction with humans rather than being developed to be an independent technology. Solutions with AI can be used as decision support, where they are only used as tools in decision-making. This will probably be more beneficial than using it as a decision-making tool that make decisions on independent basis, according to the findings.
Throughout the study the students also found that forces in the technological environment are pushing for change - while forces in the institutional environment are slowing down the degree of adoption of innovative technology such as AI. This can be seen as a dilemma where it’s important to make careful considerations between making sure to always use safe technologies, which can limit the degree of innovation, or quickly adopting new technologies that can accelerate innovation but increase the uncertainty, which is the case with AI.
It is crucial that the adoption of AI don’t create democratic challenges. It has to be handled in accordance with norms and values such as trust and credibility as well as regulations such as the GDPR.
Furthermore, the research suggest that this dilemma can be addressed through business model innovation. The case companies facilitate increased R&D as well as the adoption of machine learning through business model innovation. This is achieved through increased focus on flexibility and improvements in, for example, activities, revenue models, collaboration and projects.
AI is already a technology that a large proportion of the world’s population are surrounded by every single day - perhaps without even knowing. AI is a phenomenon that develops very quickly. Due to this ever increasing pace, today’s AI is not the same as it was just a few years ago. This entails challenges in the form of a number of uncertainties, as uncritical use can have catastrophic consequences. However, this is an area that lacks previous research.
Due to the great awareness of legitimacy and how they are perceived in the institutional environment, the companies are less profit- and technology oriented than expected – also when the companies are influenced and challenged by strong forces from the surroundings that are pushing for changes.