Leading the way in innovation for over 55 years, we build greater futures for businesses across multiple industries and 55 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.
Get access to a catalog of the latest news stories from across TCS. Discover our press releases, reports, and company announcements.
You have these already downloaded
We have sent you a copy of the report to your email again.
The COVID-19 era has seen widespread adoption of digital transformation initiatives. Artificial intelligence (AI) has modernized business operations even during such uncertain times. It can reduce a product’s time-to-market drastically and design effective go-to-market strategies. Technology giants like Microsoft, Adobe, SAP, IBM, Amazon, Google, and Apple have extensively embedded AI capabilities into their product suites to enhance overall customer experience. Adobe Sensei is one example of an AIML tool which seamlessly integrates Adobe products to create a personalized and immersive experience for customers. In the pursuit of everything-as-a-service (XaaS), these product-based companies have unleashed their cloud platforms to enable machine learning-as-a-service (MLaaS). Azure ML, Amazon Sagemaker, and Google Tensorflow are some prominent names in this area. For online businesses that have witnessed a surge during the pandemic, AI tracks customer buying patterns, implements hyper personalization, and leverages sentiment analytics, in order to enhance customer experience.
AI Now
For some years now, AI has played a major role in simplifying business operations, such as detecting fraud in unusual transactions, facial recognition, identifying phishing attacks, computer vision, and insight extraction from large documents. As the global economy recuperates from the initial impact of the pandemic, a shortage of desk workforce and other physical restrictions have forced businesses to seek alternatives and virtual means of communication to ensure business continuity.
Digital assistant chatbots and voice assistants have become breakthroughs during the pandemic, as there is a huge demand for virtual interaction. From intelligent drones delivering essentials to IoT devices manning command centers, AI has set the stage for new market opportunities.
AI for Social Transformation: Key Focus Post COVID-19
AI brings a major technological revolution akin to what was brought by the internet several decades ago. Pervasive computing and quantum computing are other big upcoming changes. The significance of any technology lies in how much transformation it will bring in the life of an ordinary person. AI has the potential to change most of our social problems and can prove to be a game changer for social transformation. Here are some areas that will be impacted by AI:
Vaccine development: One area where AI has proved to be beneficial is in vaccine development. Many tech and pharmaceutical companies have used AI to identify immune responses to COVID-19. For instance, London-based DeepMind, an AI company acquired by Google in 2014, has used its neural network AlphaFold to simulate the structure of the SARS-CoV-2 virus based on the genetic sequence. In another instance, biopharmaceutical giant Pfizer has leveraged IBM Watson to develop and test its COVID-19 vaccine.
Infrastructure: In the area of infrastructure, AI plays a pivotal role in reducing emissions and in building maintenance. Canadian tech firm Brainbox AI uses data from weather forecasts to predict the energy consumption of buildings. Air conditioning systems can accordingly be adjusted, thereby reducing the carbon footprint. In materials science, AI can be used to calculate the stress and strain in an object by analyzing images. Such an analysis can prevent potential damage to any building or other structures like bridges.
Education: AI can bridge language barriers, enabling people to converse with others from different regions. This is enabled by speech-to-speech translation tools such as natural-language generation (NLG). Google Cloud’s Natural Language API, Amazon Comprehend, and IBM Watson are some NLG tools that can be integrated with any app. Such language applications of AI can help the relatively less tech-savvy understand content from an electronic document, newspapers, or a self-service portal.
Healthcare: Amid a crucial shortage of healthcare services, smart wearables offer a convenient solution by monitoring critical health parameters, providing dietary measures, and raising health alarms. For instance, robotic sanitation machines have been widely used during the pandemic and AI algorithms developed by India’s Defence Research and Development Organisation (DRDO) have been used to detect COVID-19 by analyzing chest X-rays. AI can also provide remote healthcare facilities to areas where adequate infrastructure is not available. This was especially so during the peak COVID-19 waves, as most people could not directly access hospitals. AI can also be used to identify the genesis of a complex disease like cancer and provide timely and effective treatment.
The Limitless Potential of AI
This is just the surface of how machine learning can revamp our quality of life. The concepts of artificial super intelligence (ASI) and reinforcement learning are not far from becoming prevalent. Meanwhile, the true potential of AI, where it visibly impacts the life of the common man and brings about social transformation, is yet to be realized. Social good would now be the principal focus around which AI technologies would be developed and adopted across all domains.
Mortgage lending meets metaverse: a new frontier
Reimagining Manufacturing Processes with AI Agents
Digital social sensing to analyze consumer financial behavior
Sustainability Data Models for Advanced Climate Reporting