In Economy:

Fourth Industrial Revolution:

  • Artificial Intelligence (AI) is a key driver of the Fourth Industrial Revolution. Its effect can be seen in homes, businesses and even public spaces.
  • In its embodied form of robots, it will soon be driving cars, stocking warehouses and caring for the young and elderly.
  • AI holds the promise of solving some of society’s most pressing issues but also presents challenges such as inscrutable “black box” algorithms, unethical use of data and potential job displacement.


  • The manufacturing industry is expected to be one of the biggest beneficiaries of AI-based solutions, thus enabling 'Factory of the Future' through flexible and adaptable technical systems to automate processes and machinery to respond to unfamiliar or unexpected situations by making smart decisions.
  • Impact areas include engineering (AI for R&D efforts), supply chain management (demand forecasting), production (AI can achieve cost reduction and increase efficiency), maintenance (predictive maintenance and increased asset utilisation), quality assurance (for example, vision systems with machine learning algorithms to identify defects and deviations in product features), and in-plant logistics and warehousing.

 Smart Mobility:

  • It includes transports and logistics like autonomous fleets for ride-sharing, semi-autonomous features such as driver assist, and predictive engine monitoring and maintenance.
  • Other areas that AI can impact include autonomous trucking and delivery, and improved traffic management.


  • The retail sector has been one of the early adopters of AI solutions, with applications such as improving user experience by providing personalised suggestions, preference-based browsing and image-based product search.
  • Other use cases include customer demand anticipation, improved inventory management, and efficient delivery management.


  • Potential use cases in the energy sector include energy system modelling and forecasting to decrease unpredictability and increase efficiency in power balancing and usage.
  • In renewable energy systems, AI can enable storage of energy through intelligent grids enabled by smart meters, and also improve the reliability and affordability of photovoltaic energy.
  • Similar to the manufacturing sector, AI may also be deployed for predictive maintenance of grid infrastructure.


  • AI as customer care, for example, Laxmi at Union Bank, Eva at HDFC Bank.
  • Artificial Intelligence is the future of banking as it brings the power of advanced data analytics to combat fraudulent transactions and improve compliance.
  • AI algorithms accomplish anti-money laundering activities in few seconds, which otherwise take much more time.

In the Social Sphere:


  • Application of AI in healthcare can help address issues of high barriers to access to healthcare facilities, particularly in rural areas that suffer from poor connectivity and limited supply of healthcare professionals.
  • This can be achieved through implementation of use cases such as AI-driven diagnostics (Babylon app analysis), personalised treatment, early identification of potential pandemics, and imaging diagnostics, among others.

Education and Skilling:

  • AI can potentially solve for quality and access issues observed in the Indian education sector.
  • Potential use cases include augmenting and enhancing the learning experience through personalised learning, automating and expediting administrative tasks, and predicting the need for student intervention to reduce dropouts or recommend vocational training.
  • For example, "Thinker Maths" (personalised teaching app) useful in rural areas where teachers are not willing to go.


  • AI performs minuscule work e.g waste management thus reduces scavenging.
  • Speech recognition and translation can certainly reduce language barriers and promote harmony.


  • AI holds the promise of driving a food revolution and meeting the increased demand for food (global need to produce 50% more food and cater to an additional 2 billion people by 2050 as compared to today).
  • It also has the potential to address challenges such as inadequate demand prediction, lack of assured irrigation, and overuse/misuse of pesticides and fertilisers.
  • Some use cases include improvement in crop yield through real-time advisory, advanced detection of pest attacks, and prediction of crop prices to inform sowing practices.For example, IBM Thunder for weather forecasting.

In Security:


  • User behaviour analysis to predict and detect threat and reduce fraud.
  • Reduces crime by studying crime pattern using NCRB data, etc., this improves law and order.
  • Psycho-analysis and lie detector tests

Smart Cities:

  • Integration of AI in newly developed smart cities and infrastructure could also help.
  • Meet the demands of a rapidly urbanising population and providing them with enhanced quality of life.
  • Potential use cases include traffic control to reduce congestion and enhanced security through improved crowd management.

In the Political sphere:

  • Employing AI can predict voting patterns or polls. For example, the US election in which the MogIA used facebook and twitter, etc., along with big data to come up with poll predictions.

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