Emerging technologies are rapidly transforming the way societies work, communicate, learn, produce, govern and solve problems. Technologies such as Artificial Intelligence (AI), 5G, blockchain, robotics, machine learning, augmented and virtual reality, natural language processing, semiconductors and quantum technologies are increasingly shaping India’s social and economic future.
These technologies can promote productivity, inclusion, better public services and innovation, but they can also create new challenges related to employment, privacy, cybersecurity, inequality, ethics and gender bias.
Major Emerging Technologies
Important emerging technologies highlighted in the chapter include:
- Artificial Intelligence
- Machine Learning
- Deep Learning
- 5G
- Blockchain
- Robotics
- Internet of Things
- Augmented Reality
- Virtual Reality
- Natural Language Processing
- Semiconductors
- Advanced Computing
- Autonomous Systems
- Quantum Information Technologies
Some of these are also considered critical technologies because of their implications for economic development and national security.
Importance of Emerging Technology
Emerging technologies can assist governments and businesses in:
- Planning and decision-making
- Problem-solving
- Analysing large datasets
- Improving efficiency
- Developing new products and services
- Identifying future trends
- Accelerating economic development
Thus:
Technology + Data + Innovation → Higher Productivity + Better Decision-Making
Government Support for Emerging Technologies
The chapter highlights the role of MeitY’s Emerging Technology Division, which promotes areas such as:
- AI
- AR/VR
- Internet of Things
- Blockchain
- Robotics
- Computer Vision
- Drones
Technology Innovation Ecosystem
AI Committees
MeitY established committees to develop an AI policy framework and examine the economic and social impacts of AI.
IoT Centres of Excellence
NASSCOM and state governments established Internet of Things Centres of Excellence to promote innovation and use technology for social good.
Virtual and Augmented Reality
The chapter refers to the VARCoE at IIT Bhubaneswar, reflecting the growing use of VR and AR in multiple sectors.
Centres of Entrepreneurship
These incubation centres support emerging-technology startups through:
- Infrastructure
- Mentorship
- Training
- Research and development
- Funding
- Networking
INDIAai
The National AI Portal – INDIAai provides:
- Research reports
- Datasets
- Case studies
- Courses
- Articles
- Institutional information
It is intended to strengthen India’s AI ecosystem.
AIRAWAT
AIRAWAT is envisaged as a computing platform supporting AI research and knowledge development.
Global Partnership on Artificial Intelligence
The GPAI promotes AI development based on:
- Human rights
- Inclusion
- Diversity
- Innovation
- Economic development
ARTIFICIAL INTELLIGENCE AND INDIAN SOCIETY
Meaning and Growing Role
AI enables machines and computer systems to undertake tasks involving:
- Learning
- Analysis
- Pattern recognition
- Prediction
- Decision support
The chapter notes that AI is increasingly influencing technologists, lawyers, businesses and public decision-making, while also raising concerns over individual privacy.
AI and Social Good
AI in Healthcare
AI can contribute to healthcare through:
- Disease identification
- Better diagnosis
- Treatment support
- Access to healthcare in remote areas
- Prediction of epidemics
- Image recognition
The source notes that AI can improve disease detection and help extend healthcare assistance to geographically isolated populations.
AI in Agriculture
AI can support Indian agriculture through:
Precision Agriculture
AI can use agronomic and weather data to improve farm decisions and productivity.
Crop and Pest Management
It can help:
- Monitor soil
- Identify pests
- Improve crop health
- Organize farmer data
Supply-Chain Management
AI can improve efficiency across the food supply chain.
Addressing Labour Shortages
Automation can help where agricultural labour becomes difficult to obtain.
Thus:
Data + AI + Precision Farming → Better Productivity + Lower Risk
AI and Climate Change
AI can contribute to:
- Weather forecasting
- Disaster prediction
- Climate-risk assessment
- Identification of disease-carrying animals and insects
However, AI itself has an environmental footprint, and the chapter notes the importance of reducing the carbon footprint of AI systems.
AI and Inclusive Growth
AI-led development should involve cooperation between:
- Government
- Industry
- Academia
- Society
The chapter emphasizes greater stakeholder engagement and diversity in the development of the AI ecosystem.
AI and Societal Challenges
Job Displacement
Automation can replace certain routine and low-skilled jobs.
This can lead to:
- Unemployment
- Occupational disruption
- Income insecurity
- Social instability
The source identifies job disruption as one of the biggest threats posed by AI to Indian society, particularly for low-skilled workers.
Skill Gap
AI-driven industries require new skills such as:
- Programming
- Data analysis
- Data science
- Machine learning
Without adequate reskilling, many workers may be excluded from emerging opportunities.
Thus:
Automation without Reskilling → Job Displacement
but
Automation + Reskilling → Productivity + New Employment
Data Privacy
AI systems depend heavily on the collection and analysis of large amounts of data.
This creates concerns regarding:
- Personal-data misuse
- Surveillance
- Unauthorized data access
- Privacy violations
Cybersecurity
Increasing digitalization and IoT connectivity create greater vulnerability to:
- Hacking
- Data theft
- Cyberattacks
- Disruption of critical systems
This becomes particularly serious when AI is used in:
- Healthcare
- Finance
- Defence
- Critical infrastructure
Algorithmic Bias
AI systems learn from existing datasets.
If these datasets contain social prejudices, AI may reproduce or amplify them.
This can lead to discrimination based on:
- Gender
- Race
- Class
- Social identity
Thus:
Biased Data → Biased Algorithm → Biased Outcome
The chapter warns that AI decision-making may reinforce existing social inequality.
Ethical Challenges
The use of AI in:
- Surveillance
- Warfare
- Autonomous decision-making
raises important questions of:
- Accountability
- Human control
- Fairness
- Transparency
- Ethics
Legal Challenges
AI’s borderless character and unclear legal status create difficult questions relating to:
- Liability
- Accountability
- Rights
- Regulation
The chapter points to uncertainty regarding the legal treatment of AI and algorithmic decisions.
Infrastructure Divide
Effective use of AI requires:
- Reliable internet
- Computing capacity
- Digital infrastructure
Poor connectivity can prevent rural and disadvantaged areas from benefiting equally from technological advancement.
Artificial Intelligence and Gender Gap
The chapter gives special attention to gender inequality in AI and technology.
Despite women participating substantially in STEM education, they remain underrepresented in:
- AI jobs
- Technology leadership
- AI research
- Senior technical roles
The chapter cites the Global Gender Gap Report 2022, according to which women formed around 22% of AI workers globally.
Why the Gender Gap Matters
Low female participation can produce:
- Male-dominated technology design
- Less diverse decision-making
- Biased products
- Unequal economic opportunities
Technology can therefore unintentionally reproduce social inequalities.
Major Gender-Related Challenges in AI
Lack of Diversity
Women are underrepresented particularly in technical and leadership roles.
Workplace Stereotypes
Women may face:
- Gender prejudice
- Unequal promotion opportunities
- Occupational stereotyping
Work–Life Balance
Demanding technology careers can create additional barriers where women disproportionately bear unpaid domestic responsibilities.
Gender Bias in AI Systems
Algorithms trained on biased data may discriminate against women.
The chapter gives the example of facial-recognition systems misidentifying women and minorities.
Gender Gap in Research
The chapter notes relatively low female representation in AI-related scholarly research, which can influence whose perspectives are incorporated into technological development.
Gender Gap in Venture Capital
Female-led technology ventures also receive a relatively small share of global venture-capital funding.
Government Initiatives for Women in Technology
KIRAN Scheme
The KIRAN Scheme supports women scientists in advancing their academic and professional careers.
National AI Strategy
The chapter highlights the #AIForAll approach for inclusive AI development.
State Initiatives
The chapter mentions initiatives in Telangana involving:
- AI and data-science training for girls
- Rural data-annotation centres employing women
- WE-Hub programmes supporting girls and female entrepreneurs
Way Forward for Bridging Gender Gap
- Encourage girls and women to study STEM
- Provide scholarships and mentorship
- Promote flexible and inclusive workplaces
- Ensure fair promotion opportunities
- Develop women-specific AI training programmes
- Increase diversity in datasets
- Audit algorithms for bias
- Increase women’s representation in AI leadership
Overall Way Forward for AI and Emerging Technology
Strong Regulation
India needs clear rules for:
- Data protection
- Privacy
- AI accountability
- Ethical AI use
- Transparency
The chapter stresses the need for strong legal and governance frameworks for AI.
Skill Development
Large-scale reskilling is required in:
- AI
- Machine learning
- Data analysis
- Digital technologies
This is essential to prevent technological change from turning India’s demographic dividend into a social liability.
Education Reform
AI-related learning can be introduced at:
- School level
- Undergraduate level
- Postgraduate level
to create a future-ready workforce.
Inclusion
Emerging technologies should be made accessible to:
- Rural communities
- Small businesses
- Startups
- Marginalized groups
Technology should reduce rather than widen social inequalities.
Research and Development
Public and private investment should support:
- AI research
- Innovation
- India-specific applications
- Indigenous technological capacity
Responsible AI
The chapter refers to RAISE 2020 – Responsible AI for Social Empowerment, emphasizing AI for social transformation in:
- Healthcare
- Agriculture
- Education
- Smart mobility
The guiding approach should be:
Responsible + Inclusive + Ethical + Transparent + Human-Centred AI
Digital Divide, Algorithmic Bias, Responsible AI, AI for Social Good, Human-Centred Technology, Technology-Induced Unemployment, Skill Displacement, Data Privacy, Cybersecurity, Ethical AI, Inclusive Innovation, Digital Inclusion, Gendered Digital Divide, Precision Agriculture, Technology Governance, AI for All.
Emerging technology has the potential to become one of the strongest instruments of India’s social and economic transformation. Technologies such as AI, robotics, IoT and advanced computing can improve healthcare, agriculture, education, governance and productivity, while creating entirely new opportunities for innovation.
However, technology is not socially neutral. Without appropriate safeguards, it can deepen job insecurity, digital exclusion, surveillance, privacy violations, algorithmic discrimination and gender inequality.
India’s objective should therefore not merely be rapid technological adoption, but responsible technological transformation based on ethics, inclusion, regulation, skilling, research and human welfare.
The ideal pathway is:
Technology → Productivity → Inclusion → Empowerment
rather than
Technology → Exclusion → Inequality
Only a human-centred and socially inclusive technology ecosystem can ensure that emerging technologies become instruments of social justice and national development, rather than new sources of inequality.