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Become A Startup Insider With Inc42 Plus
Join our exclusive community of business leaders &makers for in-depth tech stories and intelligence on India’s tech economy you won’t find elsewhere.
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The world is still recovering from the crazy days when OpenAI CEO Sam Altman was fired after a board coup and rehired after staff support and a nudge from its biggest investor, Microsoft. Ironically, the chaos that ensued is part of the massive disruption triggered by generative AI (GenAI).
Unlike traditional artificial intelligence that mostly makes sense of large amounts of data, the ‘generative’ power of the new AI threatens to topple the innovation landscape, work processes and the entire economy. In essence, most businesses and industries are left gasping by its potential impact on manufacturing and services, productivity and efficiency as the next epoch of enterprise revolution takes over.
While business leaders try to assess the overall impact of GenAI, India has geared up fast to become a part of the new ecosystem. The country boasts more than 70 native GenAI startups backed by 80+ Indian institutional investors and $440 Mn+ in funding since 2019. And here’s the cherry on the top – Adobe recently acquired Bengaluru-based AI video creation platform Rephrase.ai. India’s generative AI market, valued at more than $17 Bn, is undoubtedly making its mark.
To dive deep into the nuances of the ongoing tech revolution and address the concerns of industry stakeholders, Inc42 and Google Cloud organised a roundtable titled Generative AI, Cloud And Startups: A Power Trio Redefining India’s Techscape!
The session covered various critical topics, including:
- Decoding the real-world impact of GenAI
- Strategies to tackle market-entry challenges posed by generative AI
- Navigating the changing landscape of workforce skills
The roundtable brought together technology decision-makers from diverse industry segments. Among them were Avneesh Goel, SVP (product & technology) at Awfis; Prince Singh, house owner (product) at OneBanc; CredFlow CTO Shalabh Aggarwal; Nitin Jain, cofounder & CBO at Oxyzo; Rajan Nagina, head of AI practice at Newgen Software; Deepak Mishra, VP (data science) at FarMart; Naman Khator, lead of solutions architect at QueueBuster; Souparno Bagchi, COO at BalanceHero India, and Gurpiar Sibia, head of customer engineering at Google Cloud.
The session was moderated by Vishal Agarwal, partner at EY and currently leading its data analytics practice.
The Road Ahead: Embracing GenAI Opportunities And Navigating Challenges
In the past decades, cloud technology has transformed how startups and enterprises work, scaling up operations, unlocking innovations and accelerating business success. Within India’s burgeoning startup ecosystem, ranked third globally behind the US and China, cloud-native startups have emerged as a global SaaS (software as a service) hub and rapidly expanded into critical areas like IaaS (infrastructure as a service), PaaS (platform as a service) and BaaS (banking as a service).
Per a Bessemer Venture Partners report, among the VC-funded Indian startups in 2022, 20%, or 468, were cloud and SaaS entities. Cloud spending also grew by nearly 22% that year, almost equal to the entire continent of Europe. This indicates how cloud computing, in its many avatars, is rising even when the funding winter has paused frenzied growth activities across the ecosystem.
Interestingly, artificial intelligence (AI) has been an innovative component in cloud play for service enhancements. Now, the country’s mature tech ecosystem is breaking frontiers to become a part of the ongoing tech revolution – generative AI.
“I am most excited about the rise in productivity that it [GenAI] ensures across different divisions of an organisation, be it marketing, content or [software] development. And I think that is perhaps the most mature use case right now where the risk is under our control,” said Deepak Mishra of FarMart.
But adopting technology can be challenging, be it a decades-old ecosystem like enterprise cloud or the latest GenAI breakthrough. For instance, a significant concern in an ML-driven tech landscape is model collapse. This occurs when an AI model trained on synthetic data generates progressively less diverse and more repetitive outputs (even LLM or large language models can fall prey to it).
“I think we cannot let go of the human angle around it, and that applies to everything AI. If we allow AI to learn from itself [and create], it will eventually lead to a self-collapse,” said Shalabh Aggarwal, CTO of CredFlow.
Watch the roundtable titled Generative AI, Cloud And Startups: A Power Trio Redefining India’s Techscape to gain more insights.
