Leading the way in innovation for over 50 years, we build greater futures for businesses across multiple industries and 131 countries.
Our expert, committed team put our shared beliefs into action – every day. Together, we combine innovation and collective knowledge to create the extraordinary.
We share news, insights, analysis and research – tailored to your unique interests – to help you deepen your knowledge and impact.
At TCS, we believe exceptional work begins with hiring, celebrating and nurturing the best people — from all walks of life.
You have these already downloaded
We have sent you a copy of the report to your email again.
Life Sciences industry is extremely excited about AI capabilities and rightly so, however there’s a regulatory picture that we need to keep in mind. After all, an organization is investing time, money and resources in AI adoption with a definite ROI in mind and it is of no good if the product/service does not get regulatory approval.
AI-based systems are quite dissimilar from traditional systems in the way that it is not always possible to explain how and why the system decided in a certain vein. Most of the ML algorithms work as a Black Box, which poses an ethical issue especially, when dealing with Personal Information (PI)/Sensitive PI. This does not sit well with the regulators who need to understand how a certain conclusion was arrived. A Black Box makes an AI solution less auditable and non-transparent.
It is imperative to rationally evaluate current Risk Management practices and policies, identify the shortcomings and plug the gaps with robust technical and procedural controls.
Integrated ecosystems are key to better patient outcomes.Talk to our experts
Find out more