India's startups turn to AI applications in 2026 after missing infra boom

Venture investors and startup executives are betting on services, enterprise tools in 2026 after missing the infrastructure boom

India largely missed the first phase of artificial intelligence’s global boom — the lucrative infrastructure and model-building layer dominated by Silicon Valley giants. Now, the country’s venture investors are betting the next phase will play to local strengths.

 

The shift from AI infrastructure to applications and enterprise services could favour India’s deep engineering talent and experience managing complex service architectures, according to investors and startup executives. With nearly 50 venture-backed tech companies now publicly traded and commanding up to $150 billion in market value, India’s startup ecosystem has matured considerably. The question is whether it can translate that foundation into AI success.

 

 

“It is now a consensus view that India will see a whole host of new AI-first successes in the application and services layers — and that should start happening in the next two years,” said Nitin Sharma, partner at venture capital firm Antler India.

 

Ganesh Gopalan, co-founder and chief executive at deep-tech firm Gnani.ai, said 2026 will be the year AI agents move from conversation to action and become embedded into core enterprise workflows. Enterprises are demanding systems that understand context and act autonomously inside operational environments.

 

“As we look to 2026, this momentum accelerates. Agentic systems will become the default operating layer for customer operations, risk and service workflows,” said Gopalan. Small language models will drive higher precision and lower latency in regulated environments.

 

Karan Kirpalani, chief product officer at AI cloud infrastructure platform Neysa, said business leaders are no longer willing to deploy ‘black box’ AI models they cannot control or explain.

 

“At Neysa, we see companies realising that they need to look under the hood. They want to own their technology, not just rent it,” said Kirpalani. “The winners in 2026 will not be the ones who just jumped on the bandwagon; they will be the ones who treated AI like a utility, building it with safety, cost control and a solid engineering foundation from day one.”

Capital markets signal maturity

Public markets have rewarded venture-backed, tech-first companies in India, while private capital has grown more disciplined, setting the stage for AI-led value creation.

 

India’s technology ecosystem demonstrated unprecedented maturity in 2025, with nearly 50 venture-backed companies now publicly traded and commanding $130 billion to $150 billion in market capitalisation. Multiple venture funds achieved the rare milestone of single investments returning entire funds, validating a model that has operated under persistent scepticism in Indian markets.

 

Sharma of Antler said the shift stands in stark contrast to U.S. and Chinese portfolios, where technology exposure accounts for 30 to 40 per cent or more. Domestic allocation to venture capital funds is expected to increase substantially as these public offerings demonstrate that Indian venture capital can produce healthy returns.

 

Despite India’s deep talent pool, the country has been conspicuously absent from the concentrated value creation at the infrastructure and model layers over the past three years. This lag has produced an “epicentre effect”, with many of the strongest AI founders relocating to the Bay Area — a brain drain Sharma considers “unfortunately an inevitable phase”.

 

The challenge extends beyond geography. While more founders want to build for global customers from day one, AI has made it harder for Indian founders to scale global businesses without close proximity to U.S. customers. The technology has increased speed and competition, concentrated funding in the Bay Area, and minimised the cost arbitrage that once favoured Indian operations.

 

“This is why we invested a lot of energy into a new initiative called Antler Embark, for Indian or APAC founders who want to build in the US and access global markets early,” said Sharma.

Services and applications: India’s opening

The nature of AI deployment, however, may play to Indian strengths in 2026. Large enterprises will still need partners to manage complexity as underlying model layers remain fluid.

 

Indian founders’ experience managing services architectures could enable a new category of hybrid services-software companies with higher margins than traditional outsourcing.

 

Sharma predicts Indian enterprise AI spending, particularly in banking, financial services and insurance, will exceed expectations, with voice AI serving as a significant wedge. When one of India’s largest enterprises, Bajaj Finance, disburses $600 million in consumer loans annually almost entirely through voice AI, it signals an inflection point.

 

“In this case, it happens to be powered by our portfolio startup Navana AI,” said Sharma.

 

Multilingual voice AI adoption should catalyse broader generative AI implementation within Indian enterprises.

 

Arrowhead, a voice-AI startup, develops sales agents for financial services that conduct conversations for up to 20 minutes, achieving up to 50 per cent higher conversions than human agents. It serves over 50 customers across India and Southeast Asia.

Consumer AI: The missing breakthrough

While quick commerce has exploded and companion apps have seen rapid adoption in 2025, the Indian ecosystem still awaits a breakthrough consumer experience — something genuinely novel with tangible utility. Sharma of Antler said education appears most promising for 2026: personalised learning or test preparation at lower price points with better outcomes, enabled by improved memory context, ambient AI and reduced voice AI costs.

 

Other sectors ripe for disruption include dating, where current app experiences remain broken, particularly in India; democratised money management at price points where robo-advisory historically failed; and employment pathways for blue-collar and grey-collar workers.

The funding cycle continues

Investors expect AI funding to continue flowing strongly through 2026, supported by policy tailwinds, interest rates conducive to growth investments, strong retention in generative AI products, and the absence of competing narratives.

 

Sharma said OpenAI and Anthropic appear positioned as consensus $1 trillion IPO candidates. His casual assessment: 2027 might mark when the sustained boom faces challenges, absent black swan geopolitical events or breakthrough architectures that raise questions about the long-term value of scaling large language model infrastructure.

 

The overall venture investment ecosystem, after collapsing from $40 billion post-Covid to approximately $10 billion in 2023, has stabilised with stronger fundamentals. Seed and Series A activity increased significantly in 2025, driven by companies that built prudently in the absence of liberal late-stage capital.

 

For an ecosystem that has worked five years to build credibility through disciplined capital deployment and public market success, 2026 represents the moment when India’s AI story shifts from absence to emergence — not in foundational models, but in applications and services where Indian strengths can translate into lasting value.