Test automation teams have scaled many heights in automating enterprise applications at large. However, they run into challenges at execution time when applications undergo updates. A minor revision in the application user interface can result in test failures and become roadblocks for the test automation execution. Changing dynamics of end-user expectations are driving organizations to accelerate code promotion to production. Agile model of development is being endorsed more than ever, thus leading to an absolute requirement to implement measures to reduce test automation maintenance efforts. A self-healing mechanism to auto fix the scripts by identifying errors and triggers would help the testing team minimize maintenance efforts. This also calls for an AI-enabled solution that can learn the nuances of errors to fix them and reduce manual interventions