MAISTRO: Towards an Agile Methodology for AI System Development Projects

The MAISTRO methodology introduces a comprehensive and integrative, agile framework for managing Artificial Intelligence (AI) system development projects, addressing familiar challenges such as technical complexity, multidisciplinary collaboration, and ethical considerations. Designed to align technological capabilities with business objectives, MAISTRO integrates iterative practices and governance frameworks to enhance efficiency, transparency, and adaptability throughout the AI lifecycle. This methodology encompasses seven key phases, from business needs understanding to operation, ensuring continuous improvement and alignment with strategic goals. A comparative analysis highlights MAISTRO’s advantages over traditional methodologies such as CRISP-DM and OSEMN, particularly in flexibility, governance, and ethical alignment. This study applies MAISTRO in a simulated case study of the PreçoBomAquiSim supermarket, demonstrating its effectiveness in developing an AI-powered recommendation system. Results include a 20% increase in product sales and a 15% rise in average customer ticket size, highlighting the methodology’s ability to deliver measurable business value. By emphasizing iterative development, data quality, ethical governance, change and risk management, MAISTRO provides a robust approach for AI projects and suggests directions for future research across diverse industries context for facilitating large-scale adoption.

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Publication Details

Journal
Applied Sciences
Published
2025-02-28
DOI
https://doi.org/10.3390/app15052628
Primary Topic
AI-based Problem Solving and Planning
Type
article
Field-Weighted Citation Impact
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article

MAISTRO: Towards an Agile Methodology for AI System Development Projects

João Carlos Néto, Nilo Sergio Maziero Petrin, Henrique Cordeiro Mariano
Applied Sciences
AI-based Problem Solving and Planning
article

MAISTRO: Towards an Agile Methodology for AI System Development Projects

João Carlos Néto, Nilo Sergio Maziero Petrin, Henrique Cordeiro Mariano
article en

Abstract

The MAISTRO methodology introduces a comprehensive and integrative, agile framework for managing Artificial Intelligence (AI) system development projects, addressing familiar challenges such as technical complexity, multidisciplinary collaboration, and ethical considerations. Designed to align technological capabilities with business objectives, MAISTRO integrates iterative practices and governance frameworks to enhance efficiency, transparency, and adaptability throughout the AI lifecycle. This methodology encompasses seven key phases, from business needs understanding to operation, ensuring continuous improvement and alignment with strategic goals. A comparative analysis highlights MAISTRO’s advantages over traditional methodologies such as CRISP-DM and OSEMN, particularly in flexibility, governance, and ethical alignment. This study applies MAISTRO in a simulated case study of the PreçoBomAquiSim supermarket, demonstrating its effectiveness in developing an AI-powered recommendation system. Results include a 20% increase in product sales and a 15% rise in average customer ticket size, highlighting the methodology’s ability to deliver measurable business value. By emphasizing iterative development, data quality, ethical governance, change and risk management, MAISTRO provides a robust approach for AI projects and suggests directions for future research across diverse industries context for facilitating large-scale adoption.

Applied SciencesVol. 15(5)
Senac University Center (BR), Serviço Nacional de Aprendizagem Comercial (BR)
Openalex Percentile: Top 99%
AI-based Problem Solving and Planning
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MAISTRO: Towards an Agile Methodology for AI System Development Projects — João Carlos Néto, Nilo Sergio Maziero Petrin, et al. · Applied Sciences (2025) | TGRS Research Map | TGRS