This study decouples artificial intelligence (AI) from automation to examine their distinct yet interrelated roles in stabilizing Ghana's healthcare, manufacturing and banking and finance sectors following COVID-19. Rather than treating the two concepts interchangeably, the research empirically investigates how AI-driven cognitive analytics versus automation-driven process execution shaped operational continuity, service delivery and economic resilience.
The study adopts a mixed-methods design, combining primary survey data from 4,311 Ghanaian firms with secondary literature. A comparative sectoral analysis evaluates adoption patterns, performance gains and implementation barriers across healthcare, manufacturing and banking.
Results demonstrate that AI and automation delivered divergent but complementary impacts. Healthcare, the most disrupted sector (65.4% of firms affected), benefited from AI diagnostics and telemedicine. Manufacturing leveraged automation for predictive maintenance and quality control, though smaller firms faced expertise and cost constraints. Banking exhibited greatest resilience through AI-powered chatbots, despite limitations in handling complex inquiries. Overall, 91.4% of businesses reported sales declines, representing an estimated loss of 115.2 million Ghana Cedis.
By decoupling AI from automation, this study provides a conceptually precise, data-grounded framework for post-pandemic industrial policy. It offers actionable strategies to address skill gaps, ethical risks and access disparities, ensuring sustainable technological integration for inclusive national growth in low- and middle-income economies.
