Smart processes, elimination of redundant procedures, in-depth analytics, unparalleled accuracy and efficiency and traceability amidst mountains of statistical data are what every organization aspires to achieve, regardless of industry.
To meet these aspirations, organizations need validated hyperautomation and artificial intelligence to empower its quality system and procedures. By employing AI in product and quality processes, businesses can change simple and routine tasks into dynamic processes, go from automating short tasks to long-running processes, from leveraging only structured data to including unstructured data and augmenting decision-making processes, which can radically change how efficiently quality work is completed.
As the digital revolution moves us further into the information age, its needs and challenges are becoming clearer. One of the most significant challenges is the growing use of AI in business application suites (i.e., EQMS). In general, AI is leveraged in digital business applications in one or more ways – key to solving process complexity, used in probabilistic predictions or forecasting, minimizing data entry errors, continual improvement and intelligent decision making. The larger goal of AI and hyperautomation in a quality system should be implemented to enhance the workforce towards digital skills.