Māori Business Datasets 2020-2024

Māori enterprises are pivotal to the economic and cultural prosperity of Aotearoa, yet predictive analysis of business outcomes tailored to these enterprises remains underexplored. This research examines the application of recurrent neural networks (RNNs) and transformer architectures to forecast key performance indicators (KPIs) for Māori small and medium-sized enterprises (SMEs). Anchored in the principles of indigenous data sovereignty—specifically through the Mana Rauranga framework—this study develops predictive models that uphold and protect the integrity of Māori data.The methodology utilises publicly available datasets, including business, employment, and earnings statistics from Stats NZ, while adhering to ethical protocols aligned with Māori aspirations for self-determination in data management. Comparative experiments assess the performance of RNN and transformer models in predicting financial sustainability and business growth. Preliminary findings indicate that transformers outperform RNNs in long-term sequence prediction tasks, offering scalable and culturally attuned AI solutions to support Māori entrepreneurship. This study bridges both technical and indigenous knowledge domains, offering a blueprint for how AI can enhance Māori business success through predictive insights while safeguarding data sovereignty. Future research will focus on community collaboration to further refine and contextualise these models, ensuring their relevance and adaptability.