Artificial Intelligence (AI) and Machine Learning (ML) technologies are increasingly being adopted in a variety of industries in India. The Indian AI market is anticipated to reach $20-30 billion by 2025, according to a report by NASSCOM, India’s IT industry authority. Through programmes like the National AI Portal and the AI Mission, the Indian government has also demonstrated interest in fostering the adoption of AI/ML across a number of industries, including healthcare, education, and agriculture.
The promise of AI/ML to boost company growth and innovation in India is what is driving its rising use. Businesses may automate tedious and repetitive operations using AI/ML technology, analyse vast amounts of data, and produce insights that can guide them in making decisions. This can help businesses reduce costs, increase productivity, and improve the quality of their products and services.
For instance, in the e-commerce industry, recommendation engines driven by AI may offer clients personalised product recommendations, increasing both sales and customer pleasure. For precise diagnosis, drug discovery, and patient monitoring in the healthcare industry, AI/ML can be applied, improving patient outcomes. In the financial services sector, AI/ML can be used for fraud detection, customer service, and investment analysis, leading to reduced risk and increased profitability.
Overall, the adoption of AI/ML in India has the potential to fundamentally alter how businesses run and greatly boost the economy of the nation.
AI/ML can be utilised in the e-commerce industry for a number of things, including chatbots for customer care, fraud detection, and logistics optimisation. Customers can be recommended products based on their browsing and purchasing habits, increasing the likelihood that they will be satisfied and driving up sales. Chatbots can provide quick and efficient customer service by answering frequently asked questions and addressing customer complaints. Fraud detection algorithms can analyze transaction data to identify and prevent fraudulent activities. Logistics optimization can help businesses optimize their delivery routes, reduce shipping costs and time, and improve customer satisfaction.
AI/ML applications in the healthcare industry include precise diagnosis, medication discovery, patient monitoring, and telemedicine. Diagnostic technologies driven by AI can examine patient data, medical pictures, and symptoms to provide precise diagnoses, which can improve patient outcomes. Drug development can be completed more quickly and cheaply by using drug discovery algorithms to examine vast volumes of data and find prospective new medications. In order to identify potential health concerns and give early warnings for medical emergencies, patient monitoring programmes can analyse patient data. Remote consultations and treatments are made possible via telemedicine, which raises the availability and cost-effectiveness of healthcare.
Fraud detection, customer service, risk management, and investment research can all be done with AI/ML in the financial services industry. Transaction data can be analysed by fraud detection algorithms to spot and stop fraudulent behaviour. Chatbots for customer care can offer speedy and effective customer support, cutting down on wait times and raising customer satisfaction. Business decision-makers can use risk management algorithms to analyse market trends and anticipate future dangers. Financial data can be analysed by investment analysis tools to spot prospective investment opportunities and hazards, increasing the accuracy of investment decisions.
AI/ML can be utilised for supply chain optimisation, quality assurance, and predictive maintenance in the manufacturing industry. The use of predictive maintenance algorithms can cut downtime and maintenance costs by analysing sensor data to predict equipment faults before they happen. To find flaws and raise product quality, quality control algorithms can examine product data. Algorithms for supply chain optimisation can enhance product delivery times, lower inventory costs, and optimise manufacturing schedules.
AI/ML can be utilised in the education industry to provide personalised instruction, student engagement, and career counselling. In order to improve student outcomes, personalised learning algorithms can examine student data to discover learning preferences and offer personalised recommendations for learning materials. Algorithms for measuring student involvement can examine student data to spot potential problems and offer tailored treatments. Employability and career prospects can be improved by using personalised career recommendations that are generated by algorithms that analyse student data and job market trends.
The companies highlighted in this table that have successfully used AI/ML include e-commerce, healthcare, financial services, manufacturing, and education. Healthcare organisations like Niramai and Sigtuple are utilising AI to increase diagnostic accuracy and illness early detection, while businesses like Flipkart and HDFC Bank have used AI-powered solutions to enhance customer experience. While education firms like BYJU’s and Simplilearn use AI to personalise learning and offer career assistance to students, manufacturing companies like Tata Steel and Hero MotoCorp use AI for predictive maintenance and quality control, respectively.
|
Industry |
Company | AI/ML Solution | Impact |
|
E-commerce |
Flipkart | Recommendation engine | 60% increase in sales |
|
E-commerce |
Myntra | Virtual styling assistant |
Improved customer experience and engagement |
| Healthcare | Niramai | AI-powered cancer screening |
Increased accuracy and early detection of breast cancer |
|
Healthcare |
Sigtuple | AI-powered blood testing |
Improved diagnostic accuracy and reduced testing time |
|
Financial services |
HDFC Bank | AI-powered chatbots |
Improved customer service and reduced response time |
|
Financial services |
ZestMoney | AI-powered credit scoring |
Increased lending to customers with limited credit histories |
|
Manufacturing |
Tata Steel | Predictive maintenance |
Reduced downtime and maintenance costs |
|
Manufacturing |
Hero MotoCorp | AI-powered quality control |
Improved product quality and reduced defects |
|
Education |
BYJU’s | Personalized learning |
Improved student engagement and learning outcomes |
| Education | Simplilearn | AI-powered career guidance |
Improved student outcomes and job placement rates |
Data privacy issues are a significant barrier to AI/ML adoption in India, as they are with the adoption of any new technology. The Personal Data Protection Bill, which aims to control the processing of personal data and safeguard individuals’ privacy, has been introduced by the Indian government. Companies must make sure they are in compliance with the most recent data protection laws while the bill is currently being reviewed.
A further obstacle to India’s adoption of AI/ML is a talent shortage. Despite India having a sizable reservoir of technical talent, there are currently not enough people working in the field of AI/ML. Since there aren’t many formal education programs available, businesses must either invest in employee training or recruit people from elsewhere.
With a population of more than 1.4 billion, India represents a sizable and expanding market for AI/ML technology.
As more Indian businesses adopt AI/ML technologies, the industry has significant room to develop.
The Indian government has shown interest in promoting the adoption of AI/ML in a number of industries through initiatives like the National AI Portal and the AI Mission. With the assistance of this support, businesses may be provided with the resources and incentives they need to invest in AI/ML technology.
India has plenty of space to innovate in areas like blockchain, edge computing, and quantum computing thanks to a strong technology industry.
There are many prospects for growth and innovation in the Indian industry even if there are obstacles to the adoption of AI/ML, such as worries about data privacy and a shortage of qualified people. India is a desirable location for organisations wishing to invest in AI/ML technologies due to the enormous market potential, government assistance, and opportunity for innovation in developing technologies.
As AI/ML technologies advance, it’s possible that new applications and use cases will be created. For instance, AI-powered agricultural machinery could boost agricultural output, and AI-powered medical diagnosis equipment could revolutionise healthcare in India.
Despite concerns that AI and ML may displace certain professions, it is projected that these technologies will provide new job possibilities in sectors including automation, data analytics, and AI/ML development.
Personalised recommendations, chatbots, and virtual assistants are a few examples of AI/ML-powered services that can provide customers with a more tailored and efficient experience.
It is predicted that the increasing use of AI/ML across numerous industries will contribute to the growth of the Indian economy. According to a survey by Accenture, AI could increase India’s GDP by $957 billion by 2035.
With rising acceptance, the introduction of new use cases, and potential effects on numerous businesses and the economy as a whole, the future forecast for AI/ML in the Indian market is positive. India has the potential to dominate the global AI/ML market as long as it keeps investing in these technologies.In order to take advantage of the advantages AI/ML technologies have to offer and to stay on top of the game, businesses must investigate and adopt them. Businesses should embrace AI/ML immediately to realise their full potential.
