The Technology advancement driving innovative diagnostic tests developed (NGS, Mass spectrometry, digital pathology and flow cytometry etc.) with the expansion of digital health access with on-demand diagnostic tools and services, with laboratories capitalizing on high specificity and sensitivity where digital pathology features such as the implementation of Artificial Intelligence (AI), data science, and bioinformatics is another area for potential growth. This will make healthcare more affordable, accessible and scalable in personalized medicine, inborn error of metabolism, neurology, all spectrum of genetic disease and infectious diseases. thus enhancing laboratory management and improving quality systems. During presentation. The transformational changes of laboratory service in terms of platform, process and more important to the laboratory professional’s safety and practice will be discussed. The automations and machine learning that uplifted the turnaround time, accuracy of the examinations and efficiency by integrating work processes throughout the entire laboratory processes, speeding up and automating preanalytical, analytical to postanalytical, which creates both opportunities and challenges. AI can learn, be trained and like human, it makes mistakes too. In order to acknowledge the emerging technologies while addressing the pros and cons in adopting artificial intelligence in clinical laboratories, to build up data science literacy such as bioinformatics in our work space in context is critically important before applications be carried out in workflow streamlining, data visualization, predictive analysis and aid diagnosis by use of correct model for interpretation of these complex and highly heterogeneous information generated in terms of text, signals, numbers and images. Until then, the potential of this integration of Big data, computing power and technology advancement could then be fully released and ultimately benefit the laboratory service and the patient outcomes.
