Mzumbe University

In recent years, cutting-edge technologies such as artificial intelligence (AI) have streamlined operations and fostered continuous innovation across various manufacturing systems. Generative AI (Gen-AI), a subset of AI, helps generate new ideas and perspectives using large language or diffusion models. Gen-AI is transforming the ways of designing, developing, and operating industrial systems. While Gen-AI is widely used to create text, images and video content, its applications in intelligent and adaptive manufacturing remain limited and require precision, reliability, seamless integration, and security. Since the adoption of Gen-AI is still in its infancy, stakeholders need to understand the various factors influencing its implementation. In the present study, the SAP-LAP framework is used to analyze the situation-actors-process (SAP) and learning-actions-performance (LAP) dimensions for the effective implementation of Gen AI to empower flexible manufacturing systems (FMS). In conjunction with the efficient interpretive ranking process (e-IRP), the actors and actions were further ranked. The research findings identify AI technology providers and start-ups, OEMs, and system integrators as the most prominent actors in the implementation of Gen-AI in flexible manufacturing systems, with government and regulatory bodies as key enablers through policy support and governance frameworks. Further results show that ‘Develop modular Gen-AI toolkits tailored to different FMS architectures’ ‘Promote standards and protocols for secure and ethical use of Gen-AI’ are the topmost actions. Insights from this study will be helpful to practitioners and researchers interested in adopting Gen-AI applications to enhance agility and flexibility in production systems.

This article examines the evolving integration of farming and livestock keeping in Kenya and Tanzania, and its impact on livelihoods, land use, food security, and the environment. It finds that "hybrid" agropastoral livelihoods, which blend these activities, are increasingly common as communities adapt to ecological pressure, land scarcity, and market changes. However, this integration is hindered by insecure land rights, gender inequality, conservation policies, and fragmented governance. The study also highlights the importance of cross-border mobility and informal trade for regional resilience. It concludes by urging for inclusive and coordinated policies that move beyond sectoral divides, empower marginalised groups, and are grounded in the ecological and lived realities of these regions to foster sustainable and equitable development.

Over six decades (1961-2021), Tanzania's agriculture transformed significantly due to population growth, policy shifts, and climate variability. Agricultural land expanded by 52% and arable land by 160%, but rapid population growth (3.38% annually) caused per capita arable land to drop by 57%. Cereal production surged 1,160%, supported by land expansion and yield improvements (from 805.7 kg/ha to 1,828.3 kg/ha). However, productivity remains below global averages due to limited mechanisation, erratic weather, and inconsistent policies. Key drivers include urbanisation (up 570% since 1960) and agriculture's declining GDP share despite its livelihood importance. Policies like Ujamaa villagisation and Kilimo Kwanza had uneven impacts. The study urges sustainable intensification, climate-resilient practices, and equitable land access. Future food security depends on technological adoption, infrastructure investment, and inclusive policies to balance productivity with environmental sustainability.

This study explores the potential and integration of a Swahili-speaking social robot as a mathematics tutor in Tanzanian primary schools. Leveraging the GPT-3.5 Large Language Model (LLM) and a NAO social robot, the research investigates the feasibility and effectiveness of using state-of-the-art technologies to support mathematics education in a low-resource setting. Because classroom lessons in such contexts often provide limited opportunities for individualised support, the robot was designed to serve as an after-class remedial tutor following a lesson on the same topic taught by a human teacher. Through a series of sessions conducted in five public primary schools involving 26 third- and fourth-grade pupils, the study assessed pupils’ cognitive learning outcomes and their perceptions of the social robot as a tutor. The robot’s tutoring approach incorporated contextual information and pupils’ progress to provide personalised feedback. The results show a significant improvement in pupils’ understanding of the mathematics topic following the robot’s tutoring, supported by qualitative feedback highlighting the robot’s friendliness, knowledgeability, and effective tutoring methods. The study underscores the potential of AI-powered social robots to complement classroom teaching in resource-constrained environments and offers insights for future research and development in this domain.

Despite significant growth in the avocado market across domestic, regional, and international markets, and its contributions to Tanzania’s economy and poverty reduction, smallholder producers remain largely excluded from high-value markets. This study maps the avocado value chain in the Mbeya and Njombe regions of Tanzania to identify key actors, their roles and relationships, production practices, and the critical constraints limiting smallholder producers’ market access. A mixed-methods approach was employed whereby survey data were collected from 305 farmers through questionnaires, while semi-structured interviews were conducted with 9 key informants. Data analysis involved descriptive statistics, cross-tabulation, chi-square and content analysis. The findings reveal a value chain structure that confines smallholder producers to low-value activities while traders consolidate power over market information, finance, and logistics. Similarly, wholesalers are the main market channel to high-value markets. At the production level, smallholder producers rely on unsustainable practices such as the use of unapproved inputs, misuse of pesticides, and rare soil testing, which impacts compliance with market standards. The major constraints smallholder producers face in accessing markets include low prices, financial constraints and price fluctuations. Hence, integrated interventions to strengthen producer organisations, invest in rural infrastructure and technologies is necessary to enhance smallholder producers’ market access.