The World Is Spending Billions on AI — Here Is Who Is Winning, Who Is Falling Behind, and Where India Fits

There is a global race happening right now, and unlike most geopolitical competitions, this one's rules are being written in real time. Governments, corporations, and universities across the world are spending extraordinary sums to ensure that they are not left behind in the age of Artificial Intelligence.

Here is where things stand today, as of April 2026.

OpenAI's 0 Billion Infrastructure Push

OpenAI — the company behind ChatGPT and the broader generative AI wave that began in late 2022 — has been on an aggressive infrastructure expansion drive. Reports described its latest push as a "0 billion shortcut to real-time AI" — a reference to the company's investment in data centre infrastructure and specialised AI chips designed to reduce the latency between a user's query and the model's response.

Real-time AI — where a model responds in milliseconds, not seconds — matters for enterprise applications: customer service, financial trading, medical diagnostics, and real-time translation. The company that gets to true real-time AI at scale first will have a structural advantage in enterprise contracts.

Sam Altman participated in India's AI Impact Summit in February 2026 alongside PM Modi and Mukesh Ambani — a signal that OpenAI sees India as a significant market and partner, not just a user base.

Also Read: India's Data Centre Boom: Why States Are Competing for Digital Infrastructure

NVIDIA's Vera Rubin Platform

At CES 2026, NVIDIA unveiled its next flagship AI chip platform, codenamed "Vera Rubin" — following the Blackwell architecture. The Vera Rubin platform introduces what NVIDIA describes as radical improvements in processing power and memory bandwidth, built specifically to handle the massive scaling requirements of next-generation AI models.

In plain terms: today's largest AI models require enormous amounts of computation to train and to run. The current generation of chips is hitting limits. Vera Rubin is the response to that — designed so that the models of 2027 and 2028 can be trained in months rather than years.

NVIDIA's dominance in AI chips has made it one of the most valuable companies in the world. Its market cap fluctuates with AI sentiment, but the underlying demand for its products — from every major AI lab in the US, China, Europe, and India — has not softened.

Google's Gemini Gets a Mental Health Update

Google announced an update to its AI assistant Gemini focused on mental health support, crisis response, and user safety. The update is grounded in clinical research — Google states that the system is trained on best practices from mental health professionals and can assist users in crisis with appropriate signposting to resources.

This is a significant use case. Mental health affects over 1 billion people globally, according to WHO data. In India, access to mental health professionals is deeply unequal — urban centres have some access, rural areas have almost none. An AI system that can provide reliable first-response mental health support in multiple Indian languages could be genuinely transformative.

Google also extended MedGemma 1.5 to Indian health startups — see the India AI article for more detail on this.

Also Read: IndiaAI Mission: Building the Digital Rails of the Economy

The US-China AI Race: Where It Actually Stands

The AI competition between the US and China is the defining technology rivalry of this decade. Here is the honest picture.

The US leads in large language models, foundation model research, and the frontier of generative AI. OpenAI, Google DeepMind, Anthropic, Meta AI, and others are running the most capable AI systems in existence.

China leads in AI-assisted manufacturing, surveillance technology integration, and the sheer scale of deployment of AI in government and industrial applications. Chinese companies — Baidu, Alibaba, Tencent, and a cluster of newer players — released a series of multimodal AI models around the Lunar New Year 2026, demonstrating significant advances in video generation and Mandarin-language reasoning.

The US has attempted to limit China's access to advanced AI chips through export controls. This has had real effects — Chinese labs cannot access NVIDIA's top-tier GPUs. But China has responded by accelerating domestic chip development, with companies like Huawei and new semiconductor startups attempting to fill the gap.

The honest assessment: export controls have slowed China, but not stopped it. Both nations are now operating in parallel tracks.

AI Governance: India's Pitch for a Seat at the Table

India hosted a high-level global AI governance summit in New Delhi in early 2026, bringing together world leaders and technology executives to push for a unified international framework for AI safety. The core argument India made: the rules for AI governance should not be set exclusively by the nations that currently lead AI development (US, China, EU). Developing nations — which will be among the most affected by AI's disruption to labour markets — deserve a voice.

Discussions at the summit covered deepfakes, automated warfare, equitable access to AI benefits, and the specific risks AI poses to democratic institutions. India's PM Modi framed this as "AI for Global Common Good" — a slogan with genuine resonance in the Global South.

The Digital Personal Data Protection Act (DPDPA) that India passed is also being watched globally as a model for how emerging economies can regulate data without stifling innovation. Whether it achieves that balance will become clearer as its implementation deepens in 2026.

Enterprise AI Adoption: What the Numbers Show Globally

84% of enterprises globally expect AI-powered low-code and no-code platforms to scale inside their businesses within the next 18 months, according to recent industry data. The shift is from "AI as experiment" to "AI as operational infrastructure."

TCS, one of India's largest IT services companies, announced a multi-dimensional strategic partnership with OpenAI to drive AI-powered innovation across enterprise, consumer, and social sectors. Pine Labs — the merchant commerce platform — embedded OpenAI APIs into its core global merchant ecosystem. These are not press release announcements. These are structural changes to how large enterprises in India and globally run their operations.

Wipro announced one of its largest deals, worth over billion, with Olam Group — a deal that centres on AI-driven operational transformation.

The AI Job Question in 2026

The anxiety about AI and employment is real, and it should not be dismissed. But the picture is more nuanced than "AI takes all jobs."

Infosys CEO Salil Parekh said the company has generated more than 28 million lines of code using AI tools — code that would previously have required proportionally more developer hours. HCLTech is focusing AI revenues as a separate metric now. TCS reported 13.5% attrition; Infosys 12.3%; HCLTech 12.4%. The IT sector is not collapsing. It is transforming.

The jobs that disappear are primarily routine, codifiable tasks. The jobs that grow are in AI oversight, model evaluation, prompt engineering, data curation, and high-level problem definition. India's challenge is training its enormous workforce for the second category fast enough to absorb those displaced from the first.