Por que projetos de IA agêntica falham nas empresas brasileiras?
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Objetivo: propor um framework diagnóstico das fricções humanas e organizacionais na adoção de Agentes de Inteligência Artificial (IA) em empresas brasileiras.
Estado da arte: modelos de aceitação de tecnologia (TAM/Utaut) e a literatura sobre confiança em automação identificam barreiras cognitivas e organizacionais à adoção, mas ainda oferecem poucos referenciais empíricos específicos para sistemas agênticos no contexto brasileiro.
Escopo: survey exploratório estruturado com 48 executivos brasileiros, utilizando questões de seleção múltipla sobre 24 modos de falha predefinidos, totalizando 336 menções.
Originalidade: o estudo propõe um framework diagnóstico organizado em três camadas — modos de falha observáveis, clusters de causa raiz e metaclusters de intervenção — integradas por uma jornada temporal de cinco fases, mostrando que 31% das fricções surgem antes do go-live.
Impactos: o framework oferece um referencial para diagnosticar riscos e orientar intervenções em capacitação, gestão da mudança, design da solução e governança pós-implantação.
ODS: 8 – Trabalho decente e crescimento econômico, 9 – Indústria, inovação e infraestrutura, 17 – Parcerias e meios de implementação.
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