The Growth of Generative AI startups in the Indian market.

India’s Digital Economy In A Nutshell

India To Have 900 Million+ Active Internet Users By 2025

The State Of Indian Startup Economy

• 3rd Largest Ecosystem In The World
• 768K+ Jobs Created In The Past Six Years
• 68K+ Indian Startups Launched To Date
• $143 Bn+ Funding Raised By Indian Startups
• 111 Indian Startups In The Unicorn Club
• 5.3K+ Funded Startups In India
• 9.5K+ Investors Participated In Startup Funding
• $500 Bn+ Combined Valuation Of Indian Startups
• 1.2K+ M&A Deals Recorded
• 24 Listed Indian Internet Companies

Artificial Intelligence: At The Centre Stage Of World’s Fifth Industrial Revolution

What Is Generative AI

GenAI is a form of artificial intelligence designed to create new content by learning from existing data. Leveraging advanced algorithms, it produces unique outcomes that mimic human creativity.

What Is Predictive AI?

Predictive AI is engineered to forecast outcomes based on the analysis of historical data and existing information. These systems employ machine learning algorithms to identify trends and statistical patterns within large sets of data.

Difference Between Generative AI & Predictive AI

Generative AI Vs Predictive AI: What Sets Them Apart

How Generative AI Works

The Generative AI Application Frontier

Evolution of Generative AI

Key Statistics From Generative AI Startup Ecosystem In India

• 70+ Native GenAI Startups In India
• $440 Mn+ Raised By Native GenAI Startups Since 2019
• 1 In Every 3 Indian GenAI Startup Is Working In Code & Data Segment
• 81% GenAI Products From India Have Sector-Agnostic (Horizontal) Use Cases
• Bengaluru Is Home To The Highest Number Of GenAI Startups In India
• 80+ Indian Institutional Investors Have Backed GenAI Startups
• 88% Indian GenAI Startups Are In Seed Stage
• 58% Indian GenAI Startups Are Founded In Or After 2021

Overview of India's GenAI Startup Space

GenAI Startups in India: Building from Scratch or Leveraging Existing Tech

GenAI Natives: Startups that began their business operations offering products or services anchored in transformer LLM models.

GenAI Adopters: Startups that initially launched without leveraging transformer-based LLM models in their products or services, but later integrated this technology into their core or supplementary offerings.

Segment Wise Distribution: GenAI Startups In India

Code and data is the target for 33% of Indian GenAI startups.

The Code & Data aspect of GenAI encompasses features such as generating code, crafting documentation, and converting text to SQL.

A range of modern SaaS startups, from digital marketing to app development and big data, are looking to leverage GenAI to enhance user experience and streamline operations.

Mapping the Genesis: Geographic Analysis of Indian GenAI Startups

88% Of India's GenAI Startups Are In Early Stage

Total Capital Raised

• Seed Stage - $50 Mn+ (88%)
• Growth Stage - $58 Mn+ (9%)
• Late Stage - $338 Mn+ (3%)

Where the Money Flows: GenAI Startups and Investors in India

A Directory of Indian Generative AI Businesses

Generative AI Market Potential: India and Global

Key Statistics From The Global Generative AI Market

$4.4 Tn+ GenAI’s Global Economic Impact

400+ GenAI Startups In The World

Marketing And Advertising Top Sector Using GenAI in 2023

$552 Bn+ GenAI’ Global Market Size By 2030

$897 Bn+ Estimated Revenue Generation By GenAI Players By 2030

10% Share Of GenAI Products And Services In Corporate IT Spend By 2030

Generative Artificial Intelligence (GenAI) Value Chain

Global GenAI Market Size To Cross $550 Bn+ By 2030

Industries Poised for Disruption Through Generative AI

Approximately 75% of the total value generated by adopting GenAI in business operations is expected to originate from these domains.

Generative AI: Revolutionizing the AI Tool Landscape

Generative AI: India's High-Impact Sectors

India's Top 5 GenAI Growth Catalysts

• Digitalisation & Cloud Computing: With more than 759 Mn active internet users, India ranks as the world's second-largest internet user base. Cloud computing in India is estimated to account for 8% of India’s GDP by 2026, with a potential to add $310 Bn to $380 Bn to the country’s GDP.
• Demand For Creative Content: India's significant consumer base for tech giants like Google, Meta, and Snapchat creates a lucrative marketplace for digital marketing, leading to increased demand for digital creatives today and in the future.
• Access To Structured Data: The internet has produced enormous volumes of user and business data worldwide, totalling 329 Mn terabytes (TB) each day. Enhanced access to organised data will significantly enhance AI adoption in the nation, resulting in heightened output accuracy.
• New Developments In AI Models: Just as the 2017 breakthrough in transformer ML models by Google scientists paved the way for the development of today's popular Generative AI models like ChatGPT and BARD, future innovations in this technology have the potential to broaden its applications across various domains and industries.
• Workflow Automation: As India aims for a $5 Tn economy by 2030, automation in business operations will play a key role. The adoption of Chatbots in leading Indian startups and corporations has already disrupted customer support roles, and this trend is likely to continue and expand in areas such as digital marketing, sales, software development and client servicing.

Five Critical Hurdles Facing India's GenAI Ecosystem

• Lack Of Startups In GenAI Foundation Models: Among the 50+ Indian GenAI startups we identified for this report, all focus on the application layer, primarily developing apps using models like ChatGPT, with none involved in creating GenAI foundation models.
• High Expense Of GenAI Model Training: The hardware and infrastructure costs for training large language models are prohibitively high, as exemplified by the need for 285K CPUs and 10K Nvidia GPUs to train GPT-3.
• Issues Of Bias and Inaccuracy: Biases inherent in the data can be passed on to models trained on large datasets. A major challenge lies in ensuring the fairness and reduction of bias in the content generated.
• Legal And Regulatory Challenges: In recent years, the Indian government has been regulating emerging tech sectors like fintech, social media, and online pharmacies. Regulations concerning intellectual property, privacy, and content generation rights are likely to be enacted.
• Concerns Over Deepfake And Misinformation: Deepfakes, which are convincingly realistic forgeries generated by models, present ethical issues related to misinformation, privacy, and potential malevolent uses.

For more such Insightful research, Follow RISHABH BHARDWAJ

Subscribe my Newsletter for more research content -https://www.dhirubhai.net/newsletters/7082976100817006592/

Happy reading and please drop your feedback in the comment section. ??