Digital startup firms are key actors in innovation landscapes and a viable part of the Swedish tech industry. They operate within hypercompetitive environments, which are dynamic and volatile due to the nature of digital technologies. However, startups often face challenges such as limited resources in terms of finances, skills, and knowledge that affect their preconditions for innovation. Previous research has failed to address the unique characteristics and required management competencies of startups engaged in digital innovation. We aim to contribute to the field of IS and digital innovation, but also provide deeper insights for new startups on how to manage digital innovation. Therefore, we explore the following research question: how do digital startups manage innovation? We have conducted a multiple case study and our findings included two different approaches for digital innovation management in startups - knowledge-push and need-pull. Our findings suggest that these different approaches to digital innovation management affect several activities within the startups. These are: strategic use of data, value creation, financial resources, knowledge-sharing/capabilities, and networking. Further, we suggest practical implications for startups and suggestions for future research.

The advancements in Artificial Intelligence (AI) have received large attention in recent years and increased awareness has led to massive societal benefits and new opportunities for industries able to capitalize on these emerging technologies. The pulp and paper industry is going through one of the most considerable transformations into Industry 4.0. Integrating AI technology in the manufacturing process of the pulp and paper industry has shown great potential, but there are uncertainties which direction companies are heading. This study is an investigation of the pulp and paper industry in collaboration with IBM that aims to fill a gap between academia and the progress companies are making. More specifically, this thesis is a multiple case study of the current state and barriers of AI technology in the Swedish pulp and paper industry, the future trends and expectations of AI and the way organizations are managing AI initiatives Semi-structured interviews were conducted with 11 participants from three perspectives and the data was thematically coded. Our analysis shows that the use of AI varies, and companies are primarily experimenting with a still immature technology. Several trends and areas with future potential were identified and it was shown that digital innovation management is highly regarded. We conclude that there are several barriers hindering further use of AI. However, continued progress with AI will provide large benefit long term in areas such as predictive maintenance and process optimization. Several measures taken to support initiatives with AI were identified and discussed. We encourage managers to take appropriate actions in the continued work toward AI integration and encourage further research in the area of potential reworks in R&D. / Framgångarna inom Artificiell Intelligens (AI) har fått stor uppmärksamhet de senaste åren och ökad medvetenhet har lett till stora fördelar för samhället liksom nya möjligheter för industrier som tar vara på dessa nya teknologier. Pappers- och massa industrin genomgår en av de mest omfattande transformationerna mot Industri 4.0. Integreringen av AI-teknologi i industrins tillverkningsprocesser has visat stor potential, men också osäkerhet kring vilken riktning företag är på väg mot. Denna studie är en undersökning av den svenska pappers- och massaindustrin, i samarbete med IBM, som syftar till att minska gapet mellan akademin och framstegen företag inom industrin tar. Mer specifikt är denna uppsats en kombinerad fallstudie av det nuvarande läget, barriärerna till AI-teknik i den svenska pappers- och massa industrin, de framtida trenderna och förväntningarna på AI och metoderna företag använder för att stötta AI-initiativ. Semi-strukturerade intervjuer genomfördes med 11 deltagare från tre olika perspektiv och datan var tematiskt kodad. Vår analys visar att användning av AI varierar och företag experimenterar huvudsakligen med omogen teknik. Flera trender och områden med potential för framtiden identifierades och det visades att digital innovationshantering är högt ansedd. Vi sammanfattar med att det finns flera barriärer som hindrar fortsatt användning av AI. Fortsatt arbete med AI-tekniken kommer leda till stora fördelar på lång sikt inom områden som prediktivt underhåll och fortsatt processoptimering. Flera åtgärder för att stötta AI-initiativ var identifierade och diskuterades. Vi uppmuntrar industrin att genomföra lämpliga åtgärder i det fortsatta arbetet mot AI-integration och uppmuntrar fortsatt forskning inom potentiella omstruktureringar inom FoU.