Abstract

In an era defined by digital transformation, resource-constrained businesses—particularly small and medium-sized enterprises (SMEs)—are under increasing pressure to make timely and accurate decisions despite limited access to skilled personnel, time, and capital. Automated Decision Support Systems (ADSS) represent a promising technological solution to this challenge, offering structured, data-driven guidance that enhances managerial decision-making while reducing operational overhead. This technical review explores the design, architecture, and deployment of ADSS tailored to the unique needs of resource-constrained environments. The paper examines key components of ADSS, including knowledge-based systems, machine learning algorithms, rule-based engines, and data integration frameworks. It highlights how these systems automate repetitive tasks, predict outcomes, and recommend optimal courses of action in domains such as inventory control, customer relationship management, finance, and strategic planning. Particular attention is paid to cloud-based and low-code/no-code platforms that lower adoption barriers for businesses lacking extensive IT infrastructure. The review also synthesizes recent advances in adaptive learning, real-time analytics, and user-friendly interfaces that improve accessibility and relevance in dynamic business environments. Additionally, the paper presents implementation strategies and case studies where ADSS have enabled operational resilience, reduced decision latency, and enhanced strategic agility in businesses with constrained resources. Despite their potential, ADSS adoption in SMEs remains limited due to concerns over cost, data quality, algorithmic transparency, and change resistance. The paper identifies these limitations and offers solutions including modular system design, stakeholder training, and the use of explainable AI to foster trust and usability. This review contributes to the growing discourse on democratizing intelligent decision-making tools, advocating for inclusive digital innovation that supports equitable business growth. It underscores the urgent need for scalable, affordable, and intelligent systems that empower resource-limited businesses to compete effectively in the global marketplace.