The world of business is too complex and with intense competition in, startups, micro, small, and medium enterprises (MSMEs), and innovation-based sectors of emerging markets have their own set of challenges in taking timely and efficient strategic decisions. The current study investigates the impact of Artificial Intelligence (AI) and Machine Learning (ML) based Decision Support Systems (DSS) on decision quality improvement, innovation performance, and operation efficiency in these organizations. Given the actual deployment of AI/ML tools unmoderated or unmediated, the current research employs a quantitative research approach on the basis of data gathered from 300 Indian and Southeast Asian firms. The sample frame is drawn from startups, MSMEs, and new industrial units that are involved in technology-enabled or innovation-intensive industries. Data were analyzed with the assistance of SPSS through descriptive statistics, reliability test, Pearson correlation, and multiple linear regression. Results indicate that there is a positive and significant effect of AI/ML-facilitated DSS on decision-making performance and innovation results. Companies that implemented these systems indicated greater flexibility, improved scenario planning, and quicker time-to-market. Startups excel especially in the area of strategic responsiveness, and MSMEs have improved process efficiency and cost control. The research contributes by offering AI and ML adoption in smaller and resource-poor companies in emerging markets. It provides policy-makers and managers with actionable recommendations to invest in affordable, scalable DSS technologies and AI literacy training. Closing the technology gap, these technologies will enable businesses to anticipate shifting markets and compete more globally. AI/ML-based decision environments are indicated by the research to have the potential to transform the face of economic growth, resilience, and innovation in emerging economies.