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.
As the world moves toward ubiquitous connectivity, everything -- devices, machines, cameras, and humans – is generating humongous data points like logs, audios, images, videos, and more.
Organizations are now analyzing these data points to extract intelligence and create a new range of services. Building intelligence involves analyzing these data sets for patterns with the help of technologies such as artificial intelligence, machine learning, and deep learning to create factories of the future, autonomous vehicles, smart and safe cities, smart farming and so on. Highlighted below are some of the key issues that AI stakeholders need to consider to accelerate their AI programs:
Infrastructure and network
Algorithms and frameworks
AI deployment, model management and governance
Every AI application has its own complexity. It is good to have an AI Performance Management (AIPM) team that has the expertise to deal with the complexities of AI application development, build reference architectures, frameworks, tools, and understand governance procedures.