Banca de QUALIFICAÇÃO: JANAINE DE SOUSA PONTES

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
STUDENT : JANAINE DE SOUSA PONTES
DATE: 29/12/2025
TIME: 15:30
LOCAL: remoto
TITLE:

Artificial Intelligence in Small and Medium-Sized Enterprises: A Strategic Implementation Framework with Applied Validation

KEY WORDS:

Artificial Intelligence; Organizational implementation; Decision-making; Organizational maturity; Small and medium-sized enterprises.

PAGES: 98
BIG AREA: Engenharias
AREA: Engenharia de Produção
SUMMARY:

The recent diffusion of Artificial Intelligence solutions has intensified pressure for gains in productivity, quality, and compliance; however, the path from the decision to adopt to the attainment of results remains weakly structured—especially in small and medium-sized enterprises (SMEs), where constraints on resources, data, and capabilities heighten the risk of dispersed initiatives. This study aims to design, operationalize, and validate an AI implementation framework tailored to SMEs. The framework is the study’s primary product and prescriptively specifies implementation phases with their stage-gate criteria, roles and responsibilities, minimum artifacts, and metrics to monitor process, adoption, value creation, and risk, under principles of governance and responsible use. As a complementary instrument, an AI Eligibility and Prioritization Matrix will be developed to support the decision gate—“for what, where, and when to use”—thereby informing diagnosis and sequencing of use cases.The research will be carried out between January and July, combining expert validation with empirical application in two complementary movements: (i) a survey-based diagnosis with SMEs to map readiness, barriers, and priorities; and (ii) implementation and validation of the framework in a coconut processing company, following a cycle comprising diagnosis and prioritization using the matrix, design of pilot(s) with goals and indicators, execution (preferably in human–AI arrangements where appropriate) with continuous monitoring, and post-pilot comparative evaluation to refine the model.The intended results are to demonstrate the framework’s usefulness, clarity, and feasibility for SMEs; to show increases in internal operational productivity and stronger support for strategic decision-making in the applied cases—reflected in shorter cycle times and fewer errors, efficiency gains, and improved service levels; and to consolidate a set of operational artifacts (maturity rubrics with levels and observable evidence, checklists and document templates by phase, and an indicator monitoring dashboard), in addition to the AI Eligibility and Prioritization Matrix adapted to the SME context. The scientific and managerial contribution lies in offering a prescriptive, validatable, and replicable model to implement, measure, and learn with AI in real organizational settings.

COMMITTEE MEMBERS:
Interno - 1142787 - JOSE ALFREDO FERREIRA COSTA
Interna - 1777131 - MARIANA RODRIGUES DE ALMEIDA
Externa ao Programa - 1367404 - ADRIANA CAVALCANTE MARQUES - UFRNExterna à Instituição - MARIZA COSTA ALMEIDA - UNIRIO