Google’s annual developer conference, I/O 2026, held on 19 May at the Shoreline Amphitheatre in Mountain View, California, was dominated by one theme: the transformation of Gemini AI from a standalone chatbot into the intelligence layer powering every Google product. CEO Sundar Pichai opened the keynote by declaring that Gemini is now processing over 2 billion queries per day across Google’s ecosystem, a figure that underscores how deeply AI has been embedded into the company’s core services.

The announcements spanned search, productivity, mobile, wearables, and developer tools, but the central narrative was clear. Google is betting its future on AI that can reason in real time, conduct deep research, and take action on behalf of users, moving beyond simple question-and-answer interactions toward a model of AI as a persistent, proactive assistant.

Real-Time Reasoning: Gemini Thinks Before It Answers

The most technically significant announcement was the introduction of real-time reasoning in Gemini. Unlike previous AI systems that generate responses word by word in a single pass, the upgraded Gemini can pause, consider multiple approaches, evaluate evidence, and revise its thinking before delivering an answer. This chain-of-thought process happens in seconds but produces dramatically more accurate and nuanced responses.

In a live demonstration, a Google engineer asked Gemini to analyse a complex legal contract and identify potential risks. The AI visibly worked through the document section by section, flagging ambiguous clauses, comparing them against standard legal templates, and producing a structured risk assessment. The entire process took approximately 15 seconds, a task that would take a human lawyer significantly longer.

Real-time reasoning also improves Gemini’s performance on mathematical problems, scientific questions, and coding challenges, areas where getting the right answer requires systematic thinking rather than pattern matching. Google reported that reasoning-enabled Gemini scores 15 to 20 per cent higher on advanced mathematics benchmarks compared to the non-reasoning version.

Deep Research Mode: Multi-Step Investigations on Demand

Google also unveiled a Deep Research mode within Gemini that can conduct multi-step investigations on complex topics. When a user asks a question that requires synthesising information from multiple sources, Deep Research mode breaks the query into sub-questions, searches across the web and Google’s knowledge graph, evaluates source credibility, and assembles a comprehensive report with citations.

The feature is designed for professionals and students who need thorough, well-sourced answers rather than quick summaries. In a demonstration, a researcher asked Gemini to investigate the environmental impact of lithium mining in South America. The AI produced a detailed report covering extraction processes, water usage, local community effects, regulatory frameworks across different countries, and recent academic studies, all within about 30 seconds.

Deep Research mode represents Google’s response to a growing concern about AI-generated content: the tendency of chatbots to produce confident but shallow answers. By conducting genuine research and citing sources, Gemini aims to provide the depth and reliability that users need for serious work.

AI-Powered Google Search: The Next Generation

Google Search is receiving its most significant overhaul in years, with Gemini AI now deeply integrated into the search experience. The new AI-powered search goes beyond the AI Overviews that were introduced in 2024, offering more interactive, conversational search experiences that adapt to the user’s intent in real time.

Users can now ask follow-up questions, refine their searches through conversation, and receive answers that combine web results, knowledge graph data, and AI-generated analysis. The search interface can present information in different formats, such as tables, timelines, or comparison charts, based on what best suits the query.

Google’s head of search explained at I/O that users are now submitting longer, more detailed queries that reveal deeper context and intent. This shift is fundamentally changing how search engines must operate, moving from matching keywords to understanding and fulfilling complex information needs.

Gemini Across Google’s Ecosystem

Beyond search, Gemini AI is being woven into virtually every Google product. In Google Workspace, Gemini can now draft documents, create presentations, analyse spreadsheets, and schedule meetings based on natural language instructions. The integration is particularly powerful in Gmail, where Gemini can summarise email threads, draft contextually appropriate replies, and even flag messages that require urgent attention.

Google Maps is getting AI-powered navigation that goes beyond turn-by-turn directions. Gemini can now understand requests like “find a quiet restaurant near my hotel that serves vegetarian food and is open late,” processing multiple constraints simultaneously to deliver personalised recommendations.

On Android, Gemini is becoming the default AI assistant, gradually replacing Google Assistant for complex tasks while maintaining backward compatibility for simple voice commands. The transition reflects Google’s broader strategy of making Gemini the single AI brain across all its platforms and devices.

Developer Tools and APIs

For developers, I/O 2026 brought several important announcements. The Gemini API now supports function calling, allowing developers to build applications where the AI can interact with external services and databases. There are new SDKs for Android, iOS, and web development that make it easier to integrate Gemini into third-party applications.

Google also introduced Gemini Code Assist 2.0, an upgraded coding assistant that competes directly with GitHub Copilot and other AI coding tools. The new version offers improved code generation, better understanding of project context, and the ability to run and test code within the development environment.

Perhaps most significantly, Google announced that Gemini models can now run on-device for certain tasks, using the processing power of modern smartphones and laptops rather than relying entirely on cloud servers. This on-device capability reduces latency, improves privacy, and enables AI features to work offline.

What Google I/O 2026 Means for India

India is a critical market for Google, with hundreds of millions of users across Search, YouTube, Android, and Google Pay. Several I/O announcements had India-specific relevance, including improved Hindi and regional language support in Gemini, enhanced Google Pay AI features for the Indian market, and the audio glasses announcement that could eventually launch in India. Google’s investment in AI infrastructure in India, including data centres and research labs, suggests that many of the features announced at I/O 2026 will reach Indian users relatively quickly, making this one of the most consequential Google events for the Indian technology ecosystem in recent years.

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The Gemma 4 family includes two variants: gemma-4-26b-a4b-it, a 26-billion parameter model with a 4-billion active parameter mixture-of-experts architecture, and gemma-4-31b-it, a 31-billion parameter dense model. Both are designed for efficient deployment across a range of hardware, from cloud GPU clusters to consumer-grade machines, making advanced AI capabilities more accessible than ever.

What Makes Gemma 4 Different

Gemma 4 builds on the foundation laid by its predecessors — Gemma 1, 2, and 3 — but introduces several architectural improvements that set it apart. The mixture-of-experts (MoE) design in the 26b-a4b variant means that only a fraction of the model’s total parameters are active during any given inference, dramatically reducing computational costs while maintaining output quality comparable to much larger models.

The 31-billion parameter dense model, meanwhile, is optimised for tasks requiring deep reasoning, code generation, and multi-step problem solving. Benchmarks published by Google indicate that Gemma 4 outperforms several proprietary models on standardised tests for mathematical reasoning, coding accuracy, and factual question-answering.

Crucially, Gemma 4 is released under an open licence, allowing developers to fine-tune, deploy, and build commercial applications on top of the models without licensing fees. This stands in contrast to the closed-source approach adopted by competitors such as OpenAI, whose models are accessible only through paid APIs. For India’s AI startups like Sarvam AI, which recently raised $350 million at a $1.5 billion valuation, the availability of powerful open-source models reduces costs and accelerates innovation.

Deep Research Tools Get Major Upgrade

On 21 April 2026, Google released two new Deep Research agents: deep-research-preview-04-2026, designed for speed and efficiency in client-facing applications, and deep-research-max-preview-04-2026, built for maximum comprehensiveness in automated context gathering and synthesis. Both agents support collaborative planning, visualisation, MCP (Model Context Protocol) server integration, and File Search capabilities.

The Deep Research tools are designed for knowledge workers, analysts, and researchers who need to synthesise information from multiple sources quickly and accurately. In practical terms, a financial analyst could use Deep Research to compile a comprehensive report on a company’s competitive landscape in minutes rather than hours, while a journalist could use it to cross-reference facts across dozens of sources before publishing.

Implications for India’s AI Ecosystem

India is one of the largest and fastest-growing markets for AI adoption, with the government’s IndiaAI Mission and Nvidia’s $2 billion AI supercluster deployment creating the infrastructure backbone for large-scale AI development. The availability of Gemma 4 as an open-source model is expected to catalyse several trends.

Startups and SMEs

Indian startups that previously relied on expensive API calls to proprietary models can now self-host Gemma 4, reducing per-query costs by up to 80 per cent. This is particularly relevant for vernacular AI applications — chatbots, translation tools, and voice assistants in Indian languages — where high query volumes make API costs prohibitive.

Enterprise Adoption

Large Indian enterprises in banking, healthcare, and manufacturing are increasingly deploying AI for fraud detection, diagnostics, and supply chain optimisation. The government’s evolving AI governance framework, which mandates transparency and accountability in AI deployment, is easier to comply with when organisations have full access to model weights and can audit the AI’s decision-making process.

Research and Academia

India’s premier research institutions, including IITs, IISc, and the Indian Statistical Institute, have been constrained by the cost of accessing frontier AI models. Gemma 4’s open licence removes this barrier, enabling researchers to experiment with cutting-edge architectures and contribute to the global AI research community on equal footing.

The Broader AI Landscape in April 2026

Google’s releases come amid intense competition in the AI industry. OpenAI continues to develop its GPT series, Anthropic has expanded its presence in India with a new Bengaluru office, and Meta’s Llama models remain popular in the open-source community. The robotics frontier is also advancing rapidly, with Google releasing an updated Gemini Robotics ER 1.6 model on 14 April with improved spatial reasoning and instrument-reading capabilities.

For India, the convergence of open-source AI models, government-backed infrastructure, and a vast pool of engineering talent creates a unique opportunity to become a global AI powerhouse. The challenge lies in translating technological capability into real-world impact — solving problems in agriculture, healthcare, education, and governance that affect hundreds of millions of people. Gemma 4 and the Deep Research tools are not the destination, but they represent a significant step on the journey towards an AI-powered India.

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Together, these events signal a new era in India’s relationship with artificial intelligence: one where the government is simultaneously welcoming global AI investment while asserting sovereignty over how Indian data and content are used. For AI, this represents the most significant policy shift since India’s Digital Personal Data Protection Act of 2023.

The Copyright Royalty Framework: What India Is Demanding

The DPIIT’s proposed framework, circulated to stakeholders on April 16, gives major AI companies — including OpenAI, Google, Meta, and Anthropic — 30 days to formally accept or negotiate terms for a structured royalty system. The proposal was developed in consultation with the Ministry of Electronics and Information Technology (MeitY), the Ministry of Information and Broadcasting, and representatives from India’s publishing, music, and film industries.

Key provisions of the draft framework include a mandatory licensing requirement for all AI models trained on copyrighted Indian content (text, images, audio, video), a royalty rate structure ranging from 0.1 percent to 2 percent of an AI company’s India-specific revenue (depending on the volume and nature of copyrighted content used), the creation of a centralised “AI Content Licensing Authority” under DPIIT to manage royalty collection and distribution, and a mandatory content audit requirement where AI companies must disclose training data sources for any model deployed in India.

The Delhi High Court’s ongoing case of ANI vs OpenAI — where India’s largest news agency sued OpenAI for using its content to train ChatGPT without permission — served as the immediate catalyst. The court has reserved judgment, but the DPIIT framework appears designed to pre-empt a purely judicial resolution by establishing a regulatory mechanism. As previously reported in Which of the 6 Best Indian Mobile Brands Will Work for You?, the intersection of AI and copyright is becoming a defining issue for India’s tech landscape.

Anthropic Opens Bengaluru Office: Claude Comes to India

In a move that underscores India’s growing importance as an AI market, Anthropic officially inaugurated its Bengaluru office on April 18, 2026. The office — located in the Outer Ring Road tech corridor — will serve as Anthropic’s Asia-Pacific engineering hub, focusing on localizing Claude for Indian languages, developing enterprise AI solutions for the Indian market, and conducting safety research tailored to India’s diverse linguistic and cultural context.

Anthropic CEO Dario Amodei, who attended the launch virtually, described India as “one of the most exciting AI markets in the world” and announced that Claude would receive dedicated support for Hindi, Tamil, Telugu, Bengali, and Marathi within Q3 2026. The company plans to hire 200 engineers in Bengaluru by year-end, with starting salaries for senior AI researchers reportedly exceeding ₹80 lakh per annum.

The Bengaluru office makes Anthropic the fourth major Western AI company to establish direct operations in India, joining OpenAI (which partnered with Tata Group in 2025), Google DeepMind (which expanded its Bengaluru presence in 2024), and Microsoft (through its extensive Azure AI infrastructure). For Tech, this influx of AI investment is transforming India’s technology ecosystem at an unprecedented pace.

India Mandates AI Curriculum From Class 3: The Education Push

Complementing its regulatory and investment moves, India’s Ministry of Education announced on April 15 that AI education will be mandatory in all CBSE and state board-affiliated schools starting from Class 3, effective academic year 2027-28. The curriculum, designed by IIT Madras in collaboration with NCERT, will introduce age-appropriate concepts including basic computational thinking and pattern recognition for Classes 3-5, introduction to machine learning concepts and simple coding for Classes 6-8, hands-on AI project building and ethical AI discussions for Classes 9-10, and advanced AI and data science electives for Classes 11-12.

The initiative builds on the National Education Policy 2020’s emphasis on 21st-century skills and represents the most comprehensive AI education mandate by any major country. IIT Madras Director V. Kamakoti stated: “India has 250 million school-going children. If even 10 percent become AI-literate, we will have the largest AI-skilled workforce on the planet within a decade.” RBI Digital Rupee Crosses 10 Million Wallets as India’s Fintech E

The Sovereign AI Movement: BharatGen and Beyond

India’s AI ambitions extend beyond regulation and education. The government’s “Sovereign AI” initiative, announced in the February 2026 Union Budget with a ₹10,500 crore allocation, is accelerating rapidly. The flagship project — BharatGen, a large language model trained exclusively on Indian language data — received its single largest tranche of funding (₹1,058 crore) in April 2026, with IIT Bombay leading the development consortium.

Sarvam AI, India’s most prominent AI startup, closed a $350 million funding round at a $1.5 billion valuation in April 2026, making it the poster child of India’s sovereign AI movement. The company’s Sarvam-1 model, trained on 22 Indian languages, is being deployed across government services including the DigiLocker platform and the upcoming Census 2026 digital portal. As covered in BSNL Orders 20,000 New 4G Sites as Jio Airtel and Vi Prepare Mid-, India’s startup ecosystem is increasingly aligned with national technology priorities.

Meanwhile, the government has funded 12 sovereign AI projects through MeitY’s AI Mission, spanning healthcare (AI-powered malnutrition detection by IIT-AIIMS Jodhpur), agriculture (crop disease prediction for smallholder farmers), and language technology (real-time translation for 22 scheduled languages).

Global Implications: How India’s AI Framework Could Set a Precedent

India’s simultaneous moves on copyright royalties, AI education, and sovereign AI development are being closely watched by other emerging economies. Brazil, Indonesia, and South Africa have all expressed interest in India’s approach, which balances market openness with regulatory sovereignty — a contrast to the EU’s restrictive AI Act and the US’s largely hands-off approach.

For global AI companies, the message is clear: India’s 1.4 billion-person market is open for business, but on India’s terms. The 30-day deadline for the copyright royalty framework response means that by mid-May 2026, the world will know whether OpenAI, Google, and their peers are willing to accept India’s conditions — or whether the country’s ambitious AI vision will face its first major international confrontation.

The coming months will be pivotal. India’s ability to simultaneously attract AI investment, protect its creative economy, and build sovereign AI capabilities will determine whether the country becomes the world’s most important AI market after the United States and China — or whether bureaucratic complexity and regulatory uncertainty slow its remarkable momentum.

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From Demos to Deployment: AI Impact Summit 2026 India Showcases Real-World Applications

The most striking feature of the summit was the absence of vaporware. Autonomous drones demonstrated live crop-disease scanning above a simulated agricultural plot inside the venue. Wearable devices designed for frontline health workers showed real-time vital monitoring and AI-assisted diagnosis. Industrial robots performed predictive maintenance routines on mock assembly lines, illustrating how manufacturers are already reducing downtime by 30 per cent.

Language technology drew particular attention. Multiple exhibitors displayed tools that translate court judgments, government circulars, and educational content into Indian languages with accuracy rates exceeding 95 per cent. For a country with 22 scheduled languages and hundreds of dialects, this capability addresses a fundamental accessibility gap.

India’s sovereign AI ecosystem, which includes startups such as Krutrim and Sarvam AI, featured prominently. These companies demonstrated large language models trained specifically on Indian datasets, offering domain expertise in agriculture, legal services, and healthcare that global models often lack.

Global Tech Giants Stake Their Claim in India’s AI Future

Google operated one of the largest pavilions at the summit, highlighting climate modelling, extreme weather prediction, regional language tools, and an AI cricket coach tailored for Indian users. The cricket coach, which analyses batting technique through smartphone video, generated long queues and social media buzz throughout the event.

Microsoft showcased secure AI platforms designed for governance and enterprise adoption. Its demonstration of AI-powered land records management attracted interest from state government officials seeking to digitise property registration systems. Nvidia drew crowds with live GPU-powered robotics demonstrations and industrial AI systems that process sensor data in real time.

Other global players, including OpenAI, Qualcomm, Amazon Web Services (AWS), and Schneider Electric, positioned their platforms for scale in India. The common theme was cost efficiency and regulatory compliance, two factors that will determine which platforms win enterprise contracts in a price-sensitive market.

Indian Conglomerates Showcase AI at Scale

Domestic industry matched the international presence. Tata Group demonstrated AI applications across manufacturing and mobility, including a predictive quality control system deployed at Tata Steel plants. HCLTech focused on enterprise AI and secure data systems, presenting case studies from banking and insurance clients who have integrated AI into customer service workflows.

Reliance Industries highlighted AI use cases in telecom, retail, and cloud infrastructure. Its Jio Platforms division revealed that AI-driven network optimisation has reduced dropped calls by 18 per cent across its 5G network in the past six months. The latest gadget innovations in India increasingly rely on on-device AI processing, a trend that Reliance is positioning to exploit through its affordable smartphone partnerships.

Country pavilions from Japan, the United Kingdom, and Germany added an international dimension, hosting bilateral discussions on AI standards, data-sharing frameworks, and joint research initiatives. Japan’s pavilion focused on robotics for elderly care, a technology area where India sees growing demand as its population ages.

The Rs 10,000 Crore IndiaAI Mission Takes Shape

Government officials used the summit to provide an update on the Rs 10,000 crore IndiaAI Mission, announced in the 2024 Union Budget. The mission aims to build sovereign AI infrastructure, including compute capacity, datasets, and a national AI marketplace. As of February 2026, the government has deployed 10,000 GPUs across four data centres and onboarded 150 startups onto its compute subsidy programme.

IT Minister Ashwini Vaishnaw stated at the summit that “India will not be a consumer of AI built elsewhere. We will build, train, and deploy AI that understands Indian contexts.” The minister announced a new round of grants targeting AI applications in agriculture, healthcare, and education, with a combined allocation of Rs 2,500 crore for the 2026-27 fiscal year.

The emphasis on sovereignty reflects geopolitical realities. With the United States, China, and the European Union pursuing distinct regulatory approaches, India is carving its own path. The country’s draft AI governance framework, expected to be finalised by June 2026, will mandate transparency in algorithmic decision-making and require impact assessments for AI systems used in public services.

Challenges Remain Despite the Optimism

For all the excitement, the summit also surfaced persistent challenges. India’s AI talent pipeline remains narrow: according to a NASSCOM report released at the event, only 12 per cent of Indian engineering graduates have skills directly applicable to AI and machine learning roles. The gap between research output and commercial deployment also persists, with many university projects failing to transition into scalable products.

Data quality is another concern. Several panellists noted that India’s public datasets are fragmented, inconsistently formatted, and often outdated. Without reliable training data, even the most sophisticated models underperform. The government’s push to create open datasets through the India Datasets Platform is a positive step, but progress has been slower than anticipated.

Energy consumption is an emerging issue as well. Training large AI models requires enormous computational power, and India’s data centres are not yet fully powered by renewable sources. Environmental advocates at the summit called for a green AI mandate that ties compute subsidies to renewable energy commitments.

What Comes Next for India’s AI Ambitions

The AI Impact Summit 2026 demonstrated that India has moved decisively from aspiration to action. The combination of government investment, corporate commitment, and startup innovation creates a foundation that few countries can match at India’s scale. The real test will come in the next 12 months as pilot projects move into production and the regulatory framework takes shape.

For investors, the signal is clear: AI in India is no longer a future bet but a present reality. For citizens, the promise is equally tangible — from faster government services to better healthcare in rural areas. Whether India can execute at the speed its ambitions demand will define the next chapter of its technology story.

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