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Assessment of Artificial Intelligence Market in India—Key Industrial Applications and Insights, 2018

Assessment of Artificial Intelligence Market in India—Key Industrial Applications and Insights, 2018

Artificial Intelligence (AI) allows computer and computer-enabled systems to transcend beyond traditional computing and provides a layer of intelligence through algorithms that enable machines to complete tasks and produce results that are analogous to human-like thought processes, decision making and problem solving. The democratization of data brought about by the digital revolution has led to increasing adoption of AI-related technologies, which help business processes shift from a traditional data-centric IT to a more evolved information-centric IT process. The combination of superior hardware, cloud-based computing, and the proliferation of Big Data technology has spurred considerable development in the performance of machine learning - one of the pillars of AI that enables machines to learn from their own experience rather than from human intervention. By leveraging the advanced insight-generation and knowledge engineering capabilities of AI, businesses have the power to make informed decisions based on logical reasoning.

The last decade has seen the growth of AI from a technological luxury providing static intelligence to a strategic necessity delivering incremental intelligence through revenue generation. The Indian market offers tremendous scope for technology-assisted solutions, and in recent years, it has been an active enabler for adopting analytics and AI-based solutions. The push from the government to utilize technological advancements to reduce financial losses and increase output efficiency has also been a key driver for the adoption of AI applications in India. While there is considerable traction in the adoption of advanced technology, the Indian market has its own challenges as compared to other developed nations. As a result, service offerings in the AI market are subjected to challenges such as reluctance to invest, lack of trust owing to data privacy concerns, and security issues. There has been an exponential increase in the number of AI-based start-up companies in the last five years, which are focused on delivering solutions that cater to industry-specific requirements and generate reliable, revenue-generating insights.

Research Highlights
The study provides an overview of the AI market in India, driving factors and challenges for AI adoption, popular AI applications that have found increasing adoption in the market, and case studies demonstrating success of AI adoption and also explores some of the key industry verticals that have either already infused or are looking to incorporate AI into their business processes along with guidance on areas of opportunity for organizations in the AI space. The study also aims to inform AI services about the potential growth opportunities for AI offerings and possible strategies to increase their footprint in the Indian market.


  • Executive Summary
    • Disruptive Trends for Artificial Intelligence (AI) in India
  • Scope and Segmentation
    • Market Overview-Definitions
  • Industry Overview
    • Evolution of AI Systems
    • Transformative Landscape of AI
    • AI-Value Chain
    • Government Initiatives-Push for Adoption
    • Economic Impact of AI for India
  • Drivers and Restraints
    • Key Drivers for AI Adoption in India
    • Key Restraints for AI Adoption in India
  • Growth Opportunities and Companies to Action
    • Growth Opportunity 1-Acceleration of Digital Automation
    • Growth Opportunity 2-Autonomous Framework Approach
    • Growth Opportunity 3-Risk Mitigation
    • Strategic Imperatives for AI Service Providers
  • AI Services-Segmentation by Industry
    • AI-Key Industry Verticals in India
    • AI in BFSI-Overview of Sector
    • BFSI-Industry Challenges and Strategic AI Use Cases
    • AI in BFSI-Case Studies
    • AI in BFSI Opportunity Attractiveness Dashboard
    • AI in Healthcare-Overview of Sector
    • HealthCare-Industry Challenges and Strategic AI Use Cases
    • AI in Healthcare-Case Studies
    • AI in Healthcare Opportunity Attractiveness Dashboard
    • AI in Retail-Overview of Sector
    • Retail-Industry Challenges and Strategic AI Use Cases
    • AI in Retail-Case Studies
    • AI in Retail Opportunity Attractiveness Dashboard
    • AI in Transportation & Logistics-Overview of Sector
    • Transportation & Logistics-Industry Challenges and Strategic AI Use Cases
    • AI in Transportation & Logistics-Case Studies
    • AI in Transportation & Logistics Opportunity Attractiveness Dashboard
    • AI in Manufacturing-Overview of Sector
    • Manufacturing-Industry Challenges and Strategic AI Use Cases
    • AI in Manufacturing-Case Studies
    • AI in Manufacturing Opportunity Attractiveness Dashboard
    • AI in Agriculture-Overview of Sector
    • Agriculture-Industry Challenges and Strategic AI Use Cases
    • AI in Agriculture-Case Studies
    • AI in Agriculture Opportunity Attractiveness Dashboard
  • AI Services-Segmentation by Application
    • NLP
    • NLP-Key Application and Use Cases
    • Machine Learning
    • Machine Learning-Key Application and Use Cases
    • Machine Perception
    • Machine Perception-Key Application and Use Cases
    • Predictive Analytics
    • Predictive Analytics-Key Application and Use Cases
  • The Last Word
    • Key Recommendations
  • Appendix
    • Abbreviations and Acronyms Used

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