Utilizing AI in innovation management
Paavola, Taimo (2021)
Paavola, Taimo
2021
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2021111220128
https://urn.fi/URN:NBN:fi:amk-2021111220128
Tiivistelmä
Integrating AI into the innovation field is currently a new research topic. So far a limited amount of empirical studies have been published in the subject matter. This paper aims to find guidelines of current practises and challenges for scaling up AI and proposes a holistic multi-dimensional approach to integrating it for those organisations that are experimenting or in foundational steps of using AI.
The researcher utilized subject matter experts from two different domains, AI and innovation, in order to cultivate a solution that provides practical implications. Qualitative data contains interviews with eight different leaders. Design thinking method was adopted to pin-point challenges from these two different fields and to come up with a versatile solution. The approach is thus descriptive and not normative in its aim to capture characteristics and identify patterns of thought.
The results show that in order to integrate AI into innovation work it is important to have clear, categorized and robust data. The Innovation Department could benefit from AI by having pattern recognitions and forecasting customers, partners, risks and profitability. It is often that the innovative culture needs to be cultivated in the organisation. This paper provides recommendations for how experimental organisations can start their use of integrating Artificial Intelligence into their innovation work.
The researcher utilized subject matter experts from two different domains, AI and innovation, in order to cultivate a solution that provides practical implications. Qualitative data contains interviews with eight different leaders. Design thinking method was adopted to pin-point challenges from these two different fields and to come up with a versatile solution. The approach is thus descriptive and not normative in its aim to capture characteristics and identify patterns of thought.
The results show that in order to integrate AI into innovation work it is important to have clear, categorized and robust data. The Innovation Department could benefit from AI by having pattern recognitions and forecasting customers, partners, risks and profitability. It is often that the innovative culture needs to be cultivated in the organisation. This paper provides recommendations for how experimental organisations can start their use of integrating Artificial Intelligence into their innovation work.