Food system is complex and encompasses stakeholders from local, regional, and global level. The activities and outcomes of the food system are associated with environmental, economic, and social impacts. Due to the growing population, and urbanization, along with the fact that global food system contributes up to 30% of anthropogenic GHG emission, one of the main contributors to climate change, a sustainable food system that could meet the food demand in the urban areas is in need. Therefore, high-tech urban agriculture (HTUA) that uses advanced technologies and enables food production in a controlled environment is seen as a promising solution, which remains niche in Sweden. This study adopted the sustainable food system approach and used the theory of multi-level perspective (MLP) on sustainability transitions to explore this technology-driven transition and identify the challenges and opportunities in developing HTUA in Sweden. Through the analysis of five Swedish policy documents and interviews with four HTUA initiatives in Stockholm, three main aspects are identified: 1) external context; 2) policy environment; and 3) communication and influence, which are independent but also interconnected. According to the findings, the global environment and Swedish context, such as climatic condition and Swedish consumption, provide HTUA an opportunity to develop. The findings also suggest that though the characteristics of HTUA initiatives and the priorities within the Swedish policy environment have overlapping traits, the policies are not effectively translated into practice and thus making it challengeable to develop HTUA in the long run. Implementing more strict restrictions and regulations on the external price, providing an easier access to urban space, simplifying the procedure for the financial support, raising public awareness towards HTUA, and bridging the knowledge gap among all stakeholders through collaborations and partnerships are suggested to reduce the risk of initiating HTUA. However, further research is still required to understand the potential of HTUA in the transformation towards a sustainable food system.

Artificial intelligence (AI) holds immense potential to revolutionize the global food system, driving sustainability, enhancing efficiency, and addressing food security challenges. However, the successful integration of AI in the food system demands a deep understanding of the complex interplay between technology, social factors, economic considerations, and ethical implications. This study explores the opportunities and challenges in implementing AI technologies within the Swedish food system, focusing on primary production. The research utilizes an expanded Socio-Technical System Theory (STST) framework, incorporating economic and ethical dimensions alongside the traditional social and technical levels. Literature review and semi-structured interviews provide insights into the dynamics of AI adoption in the Swedish context. The findings reveal that AI adoption in the Swedish food system is currently in the early adopter phase, with broad range applications. However, the study also uncovers significant barriers to widespread AI adoption, including the lack of suitable business models, fragmented data sharing infrastructures, and ethical concerns surrounding data privacy and ownership.  The analysis emphasizes the need for developing user-friendly interfaces, leveraging narrow AI applications, and establishing seamless data flow across the food value chain. The study contributes to the theoretical development of the Socio-Technical System Theory framework by demonstrating the importance of incorporating economic and ethical dimensions in understanding the complex dynamics of AI adoption in socio-technical systems. The findings also have practical implications for policymakers, industry actors, and researchers, emphasizing the significance of context-specific AI development, as well as the need for collaborative innovation processes. The research acknowledges its limitations, including the focus on primary production and the reliance on qualitative methods, and identifies potential areas for future research, such as comparative analyses across different food sectors and the use of quantitative approaches.  In conclusion, this study provides a timely and critical contribution to the understanding of AI's role and potential in transforming the Swedish food system. It indicates the need for developing suitable business plans, establishing data sharing platforms, and ensuring a harmonized data flow to harness the benefits of AI while navigating its challenges and risks, paving the way for a more sustainable and resilient food future. / Artificiell intelligens (AI) har enorm potential att revolutionera det globala livsmedelssystemet, driva hållbarhet, förbättra effektiviteten och hantera livsmedelssäkerhetsutmaningar. Men en framgångsrik integration av AI i livsmedelssystemet kräver en djup förståelse för det komplexa samspelet mellan teknik, sociala faktorer, ekonomiska överväganden och etiska implikationer. Denna studie utforskar möjligheterna och utmaningarna med att implementera AI-teknologier inom det svenska livsmedelssystemet, med fokus på primärproduktionen. Forskningen använder ett utökat ramverk för Socioteknisk Systemteori (STST), som inkluderar ekonomiska och etiska dimensioner tillsammans med de traditionella sociala och tekniska nivåerna. Litteraturöversikt och halvstrukturerade intervjuer ger insikter i dynamiken kring AI-antagande i svensk kontext. Resultaten visar att AI-antagandet i det svenska livsmedelssystemet för närvarande befinner sig i den tidiga antagandefasen, med breda tillämpningar. Studien avslöjar dock också betydande hinder för ett utbrett AI-antagande, inklusive bristen på lämpliga affärsmodeller, fragmenterade datadelingsinfrastrukturer och etiska bekymmer kring dataintegritet och ägande. Analysen betonar behovet av att utveckla användarvänliga gränssnitt, utnyttja smala AI-applikationer och etablera sömlösa dataflöden över hela livsmedelsvärdekedjan. Studien bidrar till den teoretiska utvecklingen av Socioteknisk Systemteori genom att visa vikten av att inkludera ekonomiska och etiska dimensioner för att förstå den komplexa dynamiken kring AI-antagande i sociotekniska system. Resultaten har också praktiska implikationer för beslutsfattare, branschaktörer och forskare, och betonar betydelsen av kontextspecifik AI-utveckling samt behovet av samarbetsinriktade innovationsprocesser. Forskningen erkänner sina begränsningar, inklusive fokus på primärproduktion och beroende av kvalitativa metoder, och identifierar potentiella områden för framtida forskning, såsom jämförande analyser över olika livsmedelssektorer och användningen av kvantitativa metoder. Sammanfattningsvis ger denna studie ett aktuellt och kritiskt bidrag till förståelsen av AI roll och potential i att transformera det svenska livsmedelssystemet. Den pekar på behovet av att utveckla lämpliga affärsplaner, etablera plattformar för datadelning och säkerställa ett harmoniserat dataflöde för att utnyttja AI fördelar samtidigt som man navigerar dess utmaningar och risker, och banar vägen för en mer hållbar och motståndskraftig livsmedelsframtid.