The India AI Impact Summit 2026 has been running for four days in New Delhi, and Day 4 just delivered the announcements that actually matter for businesses building with AI. Google CEO Sundar Pichai confirmed a full-stack AI hub in Visakhapatnam as part of a $15 billion infrastructure investment. OpenAI CEO Sam Altman told the audience that AI costs are "expected to fall dramatically" in the next 14 months. And Jio announced a staggering 10 trillion rupee (roughly $115 billion) commitment to AI infrastructure.
Strip away the summit pageantry, and the message is straightforward: the physical backbone for AI is scaling faster than most businesses realize, and the cost of using it is about to drop. (For context on the summit's opening days, see our earlier coverage: What the Biggest AI Event of the Year Means for Your Business.)
Google's Vizag AI Hub: What "Full-Stack" Actually Means
When Pichai says "full-stack AI hub," he is describing something more ambitious than another data center. The Visakhapatnam facility will include gigawatt-scale compute capacity and a new international subsea cable gateway. The subsea cables are part of Google's broader America-India Connect Initiative, which includes four new fiber optic cable systems between the US and India.
For businesses, this matters in two concrete ways. First, gigawatt-scale compute means Google is building the kind of capacity that can serve millions of concurrent AI workloads. As these facilities come online, the supply constraints that currently keep GPU pricing elevated will ease. Second, subsea cable infrastructure reduces latency for AI API calls. If you are running customer-facing AI applications, lower latency means faster responses and better user experiences.
This is not Google's only major infrastructure play. The $15 billion figure covers investments across India, with additional compute capacity planned in regions including Thailand and Malaysia. The pattern is clear: Google is distributing AI compute globally, not concentrating it in a handful of US data centers.
Altman's Cost Prediction: What the Numbers Could Look Like
Sam Altman's statement at the summit was pointed. He noted that OpenAI has already reduced costs by a factor of approximately 1,000 since GPT-4's launch, and he expects costs to come down dramatically again in the next 14 months. "If costs come down dramatically, I think that helps the Global South the most," he said.
This is not empty optimism. The trajectory is visible in real pricing data. When GPT-4 launched in 2023, input tokens cost $30 per million. Today, competitive models offer similar or better performance at fractions of a penny per token. The next round of cost reductions, driven by more efficient architectures, better hardware utilization, and the infrastructure buildout happening at summits like this one, could make AI API calls effectively negligible for routine business operations.
For small and mid-sized businesses, this changes the math on projects that were previously too expensive to justify. Automated customer support, document processing, real-time translation, personalized marketing -- all of these become more viable as per-token costs approach zero. The businesses that start building these workflows now, even at current prices, will be positioned to scale when costs drop further.
Superintelligence Talk: Separating Signal from Noise
Altman also made headlines by predicting that "early versions of true superintelligence" could emerge by the end of 2028. He suggested that AI systems could eventually outperform humans as scientists and even as CEOs.
Business owners should take this with appropriate calibration. Whether or not superintelligence arrives on that timeline, the practical takeaway is that AI capabilities are improving faster than most planning cycles account for. The tools available to your business in 18 months will be substantially more capable than what exists today. Building internal AI literacy and infrastructure now creates the organizational capacity to adopt those tools when they arrive.
Anthropic CEO Dario Amodei was also at the summit, reinforcing the consensus that the next few years will see rapid capability gains. The fact that the CEOs of OpenAI, Google, and Anthropic all traveled to the same event to make the same essential point -- AI is getting better and cheaper, fast -- is itself a signal worth paying attention to.
The Infrastructure Investment Wave
The headline numbers from the summit are staggering. Google's $15 billion. Jio's 10 trillion rupee commitment. These sit alongside Microsoft's previously announced $50 billion Global South AI infrastructure plan. Combined, the world's largest technology companies are pouring well over $100 billion into AI infrastructure outside the United States.
This matters for businesses everywhere because infrastructure investment drives down costs and increases access. More data centers mean more available compute. More subsea cables mean lower latency. More competition among cloud providers means better pricing. The era of AI being an expensive luxury accessible only to enterprises with deep pockets is ending.
What This Means for Your Business Right Now
Here is the practical playbook based on what came out of Day 4:
- Audit your AI spending. If you are paying for AI APIs or cloud compute, costs are heading down. Structure your contracts and vendor relationships with flexibility to renegotiate as pricing drops.
- Start building, even if it is small. The cost trajectory means today's experimental projects become tomorrow's production workloads. A chatbot that costs $200 a month to run today might cost $20 in 18 months.
- Watch the infrastructure map. As Google, Microsoft, and others build out compute in new regions, latency and data residency options will improve. This opens doors for businesses with customers in markets that currently have limited AI infrastructure.
- Invest in your team's AI literacy. The capability curve is steep. Businesses that build internal knowledge now will adopt new tools faster when they arrive.
The summit wraps up this week, but the infrastructure commitments announced here will shape the AI landscape for years. The companies building today, while costs are still declining, will have the biggest advantage when those costs bottom out.
Need help building AI workflows that scale with falling costs? BaristaLabs helps small and mid-sized businesses integrate AI tools that deliver real results -- without the enterprise price tag. Get in touch to start a conversation.