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  • Top Most Influential People in AI : Driving the Future of Technology

    In this era, Artificial Intelligence isn’t just a tech buzzword anymore. AI has also become a crucial part of our lives. From the apps on our phones, AI has integrated into our routines almost without us noticing. In healthcare, it’s spotting diseases faster than doctors. In classrooms, it’s helping students learn in completely new ways. And yes, it’s even drafting emails or articles in seconds when we’re too tired to do it ourselves.

    But here’s the thing, AI didn’t get here on its own. Behind all of these advances are real people making bold choices, taking risks, and in many cases, changing the rules as they go. Some of them are running billion-dollar companies. While others are standing up and asking tough questions about ethics and responsibility.

    In this article, we will walk through the Top 10 Most Influential People in AI, the thinkers, builders, and risk-takers deciding what the future of intelligence looks like.

    List of the Leading Game-Changers Behind the AI Revolution

    List of the Leading Game-Changers Behind the AI Revolution

    AI may be transforming industries at lightning speed, but it’s the people behind the technology who are truly shaping its future. From CEOs of trillion-dollar companies to rising innovators making AI more accessible, these leaders are driving the breakthroughs that impact our daily lives. Here’s a look at the top 10 most influential people in AI, the visionaries steering the direction of artificial intelligence.

    Name Position Company
    Matthew Prince Co-founder & CEO Cloudflare
    Elon Musk Founder xAI
    Sam Altman CEO OpenAI
    Jensen Huang CEO Nvidia
    Fidji Simo CEO of Applications OpenAI
    Mark Zuckerberg Founder & CEO Meta
    Andy Jassy President & CEO Amazon
    Allie K. Miller CEO Open Machine
    Ravi Kumar S CEO Cognizant
    Dario Amodei Co-founder & CEO Anthropic

    Matthew Prince

    Matthew Prince - Top Most Influential People in AI
    Matthew Prince – Top Most Influential People in AI

    Cloudflare’s co-founder and CEO, Matthew Prince, made headlines when he quickly moved to block AI crawler bots that were siphoning traffic away from news and media publishers. His firm stance positioned him as a strong defender of original content creators at a time when many were worried about how generative AI tools were using their work without credit. Prince’s move wasn’t just about protecting websites; it was about drawing a line on fairness in the digital age.

    As of February 2025, his leadership has also translated into personal success. With an estimated net worth of US$5.5 billion, Prince is officially recognized as the richest individual in Utah, a reflection of Cloudflare’s continued dominance in internet security and infrastructure.

    Elon Musk

    Elon Musk - Top Most Influential People in AI
    Elon Musk – Top Most Influential People in AI

    Elon Musk, the founder of xAI and co-founder of OpenAI, continues to play a defining role in the global AI conversation. He is not the part of Open AI anymore. Through his ventures, he pushes for alternatives to dominant players while also raising concerns about the risks of unchecked artificial intelligence. 

    His companies, along with his constant presence in public discourse, ensure that his voice carries weight in shaping the future of technology. According to Forbes, Musk’s net worth now exceeds $400 billion, cementing his position not only as one of the wealthiest people on the planet but also as one of the most impactful in steering AI’s trajectory.

    Sam Altman

    Sam Altman - Top Most Influential People in AI
    Sam Altman – Top Most Influential People in AI

    Sam Altman, the CEO of OpenAI, has been instrumental in transforming the company into one of the most influential players in the AI world. His focus on scaling infrastructure and shaping global policies has given OpenAI unmatched influence in the ecosystem. Under his leadership, OpenAI has become synonymous with innovation, regulation, and real-world impact. According to Forbes, Altman’s net worth stands at US$1.2 billion, highlighting his growing stature among the world’s top tech leaders.

    Jensen Huang

    Jensen Huang - Top Most Influential People in AI
    Jensen Huang – Top Most Influential People in AI

    As Nvidia’s CEO, Jensen Huang transformed graphics processors into the backbone of the AI revolution. His ability to secure massive infrastructure deals and navigate geopolitics has made Nvidia indispensable to the AI boom. Huang’s leadership ensures that nearly every major AI company relies on Nvidia chips for innovation. In 2025, Forbes ranked him the 6th-richest person in the world with a net worth of US$150 billion.

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    Fidji Simo

    Fidji Simo - Top Most Influential People in AI
    Fidji Simo – Top Most Influential People in AI

    She is currently serving as CEO of Applications at OpenAI. Fidji Simo focuses on making AI products scalable and commercially successful. Her earlier experience at Instacart and Meta gave her strong expertise in both product innovation and operational excellence. At OpenAI, she plays a key role in bringing AI tools into the hands of everyday users. According to Insider Trades, her net worth is estimated at US$70.75 million as of 2025.

    Mark Zuckerberg

    Mark Zuckerberg - Top Most Influential People in AI
    Mark Zuckerberg – Top Most Influential People in AI

    As founder and CEO of Meta, Mark Zuckerberg is embedding AI deeply into social platforms and the metaverse. His influence means billions of people interact with AI daily, often without even realizing it. Beyond consumer products, Zuckerberg is also pushing AI research into new frontiers of virtual and augmented reality. Forbes reported his net worth at US$221.2 billion in May 2025, ranking him the second-richest person in the world.

    Andy Jassy

    Andy Jassy - Top Most Influential People in AI
    Andy Jassy – Top Most Influential People in AI

    Amazon’s President and CEO, Andy Jassy, is driving the company toward becoming one of the most AI-centric businesses globally. From foundational models to robotics and logistics, AI is central to Amazon’s future under his leadership. Jassy’s vision emphasizes AI integration across both consumer services and enterprise operations. As of January 2025, his net worth was estimated at nearly US$500 million, reflecting his steady rise as a corporate leader.

    Allie K. Miller

    Allie K. Miller - Top Most Influential People in AI
    Allie K. Miller – Top Most Influential People in AI

    As CEO of Open Machine, Allie K. Miller is pushing for AI tools that are practical, user-friendly, and widely accessible. Known for championing innovation, she is among the rising stars making AI adoption easier for individuals and businesses alike. Her leadership is helping shift AI from research labs to real-world use cases. Media reports estimate her net worth at around US$36 million in 2024.

    Ravi Kumar S

    Ravi Kumar S - Top Most Influential People in AI
    Ravi Kumar S – Top Most Influential People in AI

    As CEO of Cognizant, Ravi Kumar S is promoting the idea of the “sentient enterprise,” where AI and humans work seamlessly together. He has introduced platforms like Agent Foundry and Synapse to accelerate generative AI adoption across industries. His focus remains on democratizing AI access and making expertise more widely available. As of June 30, 2025, Kumar held 54 stocks with a net worth exceeding INR 898.9 crore.

    Dario Amodei

    Dario Amodei - Top Most Influential People in AI
    Dario Amodei – Top Most Influential People in AI

    As co-founder and CEO of Anthropic, Dario Amodei has made safety and alignment central to AI development. His company is now one of the most important voices in the global conversation on responsible AI. Amodei is widely respected for advocating innovation that doesn’t compromise on human values or ethics. In 2025, Forbes estimated his net worth at US$3.7 billion, reflecting Anthropic’s growing influence.

    Conclusion

    Artificial Intelligence has rapidly moved from being a futuristic concept to an everyday reality that shapes how we work, communicate, and even think about the world around us. The ten figures we explored are not only building cutting-edge technologies but also shaping the policies, ethics, and commercial models that determine AI’s global impact. 

    Some, like Jensen Huang and Sam Altman, are focused on scaling the infrastructure that fuels this revolution, while others, like Dario Amodei and Matthew Prince, are setting boundaries around safety and fairness. Leaders such as Mark Zuckerberg, Fidji Simo, and Andy Jassy are integrating AI into platforms billions of people use daily, while rising stars like Allie K. Miller are making AI more accessible for individuals and businesses alike.

    As we move deeper into 2025, one thing is clear: AI’s story is still being written, and these influential minds are holding the pen. The way they balance innovation with responsibility will decide not only the future of artificial intelligence but also the future of humanity’s relationship with technology itself.

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    FAQs

    Who are the top 10 most influential people in AI?

    The top 10 AI leaders include Matthew Prince, Elon Musk, Sam Altman, Jensen Huang, Fidji Simo, Mark Zuckerberg, Andy Jassy, Allie K. Miller, Ravi Kumar S, and Dario Amodei.

    Why is Jensen Huang considered a leader in AI technology?

    Nvidia’s CEO Jensen Huang transformed GPUs into the backbone of AI. Almost every AI company depends on Nvidia’s hardware, making him essential to the global AI boom.

    How is Mark Zuckerberg using AI at Meta?

    Mark Zuckerberg is embedding AI into Meta’s platforms, including Facebook, Instagram, WhatsApp, and the Metaverse. His work allows billions of people to interact with AI daily.

  • Sarvam AI to Receive First IndiaAI Mission Grant Worth INR 220 Crore

    Sarvam AI, a AI startup based in Bengaluru and founded by Vivek Raghavan and Pratyush Kumar, is progressing toward being the first beneficiary of the IndiaAI Mission. This mission is the flagship initiative from the Indian government to aid and boost the development of AI that is made and owned in India. As per several industry insiders, Sarvam AI is expected to receive support to the tune of about INR 220 crore. This support is expected to come mostly in the form of having nearly 4,000 top-tier Nvidia H100 GPUs available free of cost for a period of six months. These GPUs are among the best available for training AI models.

    Indigenous Models for Indian Voices

    Sarvam has already advanced in this area, having founded a language model with 2 billion parameters last year. This model, when put to the test in the context of Indian languages, was found to yield results that outperformed those of several globally recognized language models. Sarvam’s model used tokenization techniques that were lauded for their efficiency and precision, enabling the generation of prompt regional language responses with far greater ease than had been the case up to that point.

    Sarvam in the process of scaling up both his infrastructure and the model itself. The AI company is working on a new version of its language model that will come equipped with 70 billion parameters and will be capable of functioning in both Indian languages and English.

    Government’s Grand AI Vision

    The Mission IndiaAI, with support exceeding INR 10,000 crore, has been conceived to set in motion the domestic innovation ecosystem in artificial intelligence. Its primary focus, stated quite clearly, is on three components: on the one hand, it wants to create the very necessary IndiaAI compute capacity; on the other hand, it aims to establish an IndiaAI Innovation Centre; and, finally, the datasets required for AI in India, which are currently lacking, should be made available through the IndiaAI Datasets Platform. The agencies that set up this mission seem to have realized that AI requires large-scale computing facilities and have set about trying to create one.

    Competition and Collaboration in the AI Arena

    Alongside Sarvam, other startups like Soket AI Labs, Gnani.ai, and Gan.ai are also in the fray. Soket AI Labs has proposed a massive 120-billion parameter open-source Indic LLM under the EKA Project, while Gnani.ai is focused on conversational AI, aiming to develop speech-to-speech models for customer service. Gan.ai, known for AI-powered video personalization, has also submitted its proposal. The urgency to support such projects has been amplified by rapid advancements in countries like China, whose DeepSeek model spurred India’s resolve to build its own foundational AI technologies.

    Currently, India is advancing large-scale language models, and it aims to have several of them ready by year-end. Hence, the timeline fits well with the government’s ambition to have a more significant presence in the global artificial intelligence race.

  • Why AI’s Greatest Breakthroughs Depend on Women—and What Happens If We Are Left Behind

    This article has been contributed by Chaitra Vedullapalli, Co-Founder & President, Women In Cloud.

    I want to take you into the future. A world where artificial intelligence governs every part of our lives. Medicine. Finance. Education. Security. Even governance itself. AI has become the architect of the modern world. It is making decisions, shaping economies, and redefining what it means to work, to learn, and to create.

    And yet, there is something missing in this future.

    A critical voice. A perspective that should be there, but isn’t.

    Women.

    As AI advances, women are being left out of the conversation. The data speaks for itself. Today, only 22 per cent of AI professionals worldwide are women. Less than two per cent of venture capital funding for AI startups goes to female-led teams. 2% of women leaders are part of the decision-making of AI’s future. The datasets used to train AI systems are overwhelmingly built on male-dominated perspectives.

    If we are not careful, we are building a future where AI will reflect only part of humanity—a world that is optimized for the privileged, for the well-represented, and for those who already hold power.

    Because here’s the truth: AI is only as good as the perspectives that shape it.

    And if women are not at the table designing AI systems, then those systems will be built on inequality, bias, and missed potential.

    The Moment I Understood the Power of Access

    Early in my career at Oracle, I had a moment that changed my trajectory. I was working as a consultant, doing good work but unsure how to break into leadership. Then one day, my manager, Ron introduced me to Jacqueline Woods. She was leading global pricing and licensing at Oracle, reporting directly to the CEO of Oracle.

    That introduction changed everything. Moving from a consultant role into the senior manager in the global office under Jacqueline’s leadership was more than just a promotion—it was a profound shift in how I saw the world. I learned how software is sold, packaged, and priced. I saw how technology could create access, and how systems were built to determine who wins and who gets left behind.

    Most importantly, I realized that access isn’t just about talent. It’s about having someone willing to unlock the door for you. Jacqueline didn’t just mentor me—she sponsored me. She gave me access to the rooms where decisions were made. And that access became the foundation of my journey in technology, leadership, and economic empowerment.

    Now imagine if that door had never been opened. Imagine if no one had given me access to that level of understanding, that seat at the table.

    That is exactly what is happening to women in AI today.

    The Consequences of Being Left Behind

    We are entering an era where AI will determine who gets hired, who gets approved for loans, and who gets access to healthcare. These are not just technical questions—they are deeply human ones.

    And yet, the teams building these systems are not reflective of the people they serve.

    When women are not involved in AI leadership, the consequences are real. We see it in healthcare algorithms that misdiagnose women’s symptoms because the training data was based on men. We see it in hiring systems that favour male applicants because they were trained on decades of male-dominated resumes. We see it in financial algorithms that reinforce economic inequality because they were designed without a nuanced understanding of women’s financial realities.

    These are not abstract problems. These are life-altering barriers.

    And here’s what happens if we don’t fix this:

    AI will accelerate inequality, widening the gap between those who have access to opportunity and those who do not. It will embed biases so deeply into our systems that they become nearly impossible to undo. It will shape economies, policies, and industries in ways that reinforce the status quo, rather than challenge it.

    And the worst part? Many people won’t even realize it’s happening.

    Because once AI is embedded into the fabric of society, its decisions will feel invisible. It will feel like the natural order of things. And that is the real danger—not just exclusion, but normalization.

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    The Path Forward: A Roadmap for Change

    The good news is that this future is not inevitable. We can change it.

    But it requires action. Deliberate, strategic action to ensure that women are not just participants in the AI revolution—but leaders of it.

    First, we must ensure that women are in decision-making roles in AI. That means hiring more women in technical fields, but it also means putting women in executive leadership, policy-making, in investment positions. AI is not just about coding. It is about influence. And we need women in the rooms where AI strategies are being decided.

    Second, we need to make AI education accessible to women at all levels. AI is moving too fast for us to rely on traditional academic pipelines. We need industry-led programs, boot camps, fellowships, and executive training that allow women to enter AI from all disciplines—whether they are engineers, economists, policymakers, or entrepreneurs.

    Third, we must confront the bias within AI itself. That means requiring companies to audit their AI systems for gender and racial bias. It means making algorithmic transparency a priority. It means demanding that AI reflects the complexity and diversity of the world it is meant to serve. And finally, we must fund women-led AI innovation. Less than two per cent of AI venture capital funding goes to women-led startups. That is not a pipeline problem. That is a decision problem. Investors must make a conscious effort to fund AI solutions built by and for diverse populations.

    The Responsibility of Leadership

    If you are in this room today, you are in a position of influence. Whether you are leading a company, investing in AI, or shaping policy, you have the power to change the trajectory of this future.

    This is not just about ethics. This is about innovation and access. Because the most powerful AI breakthroughs will come from diverse teams solving problems in ways that a homogenous group never could.

    So, I ask you: What role will you play in shaping this future?

    Will you be the leader who ensures women are at the forefront of AI? Will you be the investor who funds the next generation of women-led AI companies? Will you be the policymaker who ensures AI systems are built with fairness and accountability?

    Or will you look back in ten years and realize that we let the most powerful technological revolution of our time be shaped by only half of humanity?

    The future of AI is not just about technology. It is about who holds the power to shape it.

    And if women are not part of that equation, then AI’s greatest breakthroughs will never reach their full potential.

    The question is not whether women belong in AI. The question is whether AI can truly succeed in its truest potential and economic impact without them.

    And the answer is clear.

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  • Monetizing AI: Business Models That Work (And Those That Don’t)

    This article has been contributed by Nida Sahar, CEO, Nife.io.

    In 2017, a small AI startup had what seemed like an unbeatable product: a powerful deep-learning model that could generate human-like text. Investors were excited, the demo was impressive, and the hype was real. But there was a major challenge—they had no clear monetization strategy. 

    After months of experimentation, they launched a subscription product, but user churn was high. They then attempted to license their model to enterprises, but the sales cycle was too slow. Finally, they pivoted to an API model, which allowed them to scale revenue quickly. 

    That startup was OpenAI. 

    Their journey reflects a challenge every AI company faces: Having powerful technology is not enough—without the right business model, even the most advanced AI products will fail. 

    Three Proven AI Monetization Strategies 

    AI startups typically choose among three primary monetization strategies, each with advantages and challenges. 

    1. Subscription-Based AI: The SaaS Model 

    A common approach to AI applications is the subscription-based SaaS model. Whether it’s an AI-powered tool for marketing, automation, or data analysis, many companies opt to charge users a monthly or annual subscription. 

    When Subscription Works Best 

    • The product provides continuous value (e.g., Grammarly enhances writing daily).
    • A freemium-to-premium conversion strategy is effective (Jasper AI monetized free users by offering premium marketing features). 
    • The target audience consists of individuals or small businesses that are unlikely to commit to enterprise contracts. 

    Challenges of Subscription AI 

    • High churn rates: If users do not perceive ongoing value, retention becomes difficult.
    • Customer acquisition costs: Scaling an AI SaaS product requires significant investment in marketing and customer education.
    • Compute costs: AI-driven SaaS products often have higher infrastructure costs than traditional SaaS, which can eat into margins. 

    Case Study: Grammarly & Jasper AI 

    Grammarly successfully leveraged the freemium model, allowing users to test the product before upgrading to paid plans. Jasper AI found a profitable niche in marketing, charging users based on AI-generated content. 

    Both succeeded because they solved a specific, recurring pain point rather than simply offering an interesting AI feature. 

    2. API-Based AI: The Developer-Focused Approach 

    Instead of building an end-user application, some AI startups monetize by offering API access to their models, allowing developers and businesses to integrate AI into their own products. 

    When APIs Work Best 

    • Developers need off-the-shelf AI without the cost of in-house development. ● The AI model is expensive to build but relatively cheap to scale (Deepgram optimized infrastructure to make speech recognition cost-effective). 
    • Enterprises prefer usage-based pricing over fixed subscriptions. 

    Challenges of API Monetization 

    • Cloud costs can escalate if you don’t carefully structure pricing; usage growth can lead to unsustainable infrastructure costs. 
    • Commoditization risk: Open-source alternatives and competitors can drive prices down, leading to a race to the bottom. 

    Case Study: OpenAI & Deepgram 

    OpenAI successfully implemented pay-per-use pricing, which allowed it to generate significant revenue while maintaining accessibility. Deepgram positioned itself as a cost-effective alternative to major cloud providers by optimizing infrastructure and pricing aggressively. 

    APIs are scalable, but success depends on controlling costs and maintaining differentiation in a competitive market. 

    3. Enterprise AI: Selling to Large Organizations 

    Enterprise AI focuses on selling AI solutions directly to businesses, often through customized deployments or large-scale integrations. This model is common in industries like finance, healthcare, cybersecurity, and government contracting.

    When Enterprise AI Works Best 

    • The AI product solves a critical business problem that organizations cannot solve internally (e.g., Palantir provides intelligence solutions to government agencies).
    • Customers require custom AI models that are not easily replaced by off-the-shelf solutions. 
    • The company has the resources to withstand long sales cycles (often 12+ months).

    Challenges of Enterprise AI 

    • Sales cycles are long: Closing enterprise deals can take a year or more, creating cash flow challenges for early-stage startups. 
    • Customer acquisition requires direct sales efforts, which can be expensive and complex. 
    • Procurement processes are slow and bureaucratic, making it difficult to scale quickly. Case Study: Palantir & C3.ai 

    Palantir built a successful AI business by securing large government contracts before expanding into the private sector. C3.ai focused on industry-specific AI applications, such as energy and supply chain optimization, allowing them to differentiate from general-purpose AI platforms. 

    Enterprise AI can be highly profitable, but it requires significant capital, patience, and a strong sales team. 

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    What Doesn’t Work? 

    While some AI business models have proven successful, others have consistently failed.

    1. “Cool Tech Without a Business Model” 

    Many AI startups focus too much on research and product development without a clear go-to-market strategy. Having a high-performing model is not enough; it needs to be packaged, priced, and distributed effectively. 

    2. “Subscription Models with High Churn” 

    If users do not see continuous value from an AI product, they will cancel their subscriptions quickly. AI tools that are used sporadically or fail to integrate into users’ workflows often struggle to retain customers. 

    3. “APIs Without Pricing Control”

    APIs can be profitable, but only if usage-based pricing accounts for infrastructure costs. If an API model scales usage without sufficient margins, the company can end up losing money as it grows. 

    4. “Enterprise AI Without Sufficient Funding” 

    Many startups attempt to sell AI to enterprises without realizing how long and expensive the process is. Without strong financial backing, these companies often run out of capital before closing enough deals to sustain operations. 

    Pricing AI Products: Key Strategies 

    Selecting the right pricing model is critical for AI monetization. The most successful companies use one or a combination of the following approaches: 

    1. Usage-Based Pricing (Best for APIs & Enterprise AI) 

    • Charges customers per API call, token processed, or data analyzed.
    • Example: OpenAI’s pricing scales based on usage. 

    2. Tiered Subscription Pricing (Best for SaaS AI) 

    • Offers multiple pricing plans based on feature access or limits. 
    • Example: Jasper AI charges higher fees for businesses, generating more AI content. 

    3. Freemium-to-Paid Conversion (Best for Consumer AI) 

    • Provides free access to basic features, with paid upgrades for advanced functionality.
    • Example: Grammarly’s free version drives user adoption before upselling premium features. 

    4. Enterprise Licensing (Best for B2B AI) 

    • Companies sell AI solutions as a one-time license or an annual contract.
    • Example: Palantir’s multi-million-dollar government contracts. 

    Key Takeaways for AI Founders and Investors 

    • Subscription AI can work, but retention is critical. 
    • API-first models scale quickly, but pricing and cloud costs must be managed carefully.
    • Enterprise AI is lucrative but requires capital, patience, and strong sales execution. 
    • A hybrid approach often provides the most stability and scalability. What’s Your Strategy? 

    The AI market is exploding, but monetization remains a major challenge. The most successful AI companies are not necessarily those with the best technology, but those that have a well-defined business model and execution plan. 

    For AI founders, the key question is not just, “What can we build?” but “How will we sell it?”.

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  • ZuperAI and KiranaPro Collaborate to Provide AI-Powered Retail Market Solutions

    Quick commerce platform KiranaPro has teamed up with B2B management platform ZuperAI to provide its users with AI-based retail market solutions, only days after enlisting PV Sindhu as an investor. In order to help consumers and merchants with product discovery, inventory optimisation, and supply chain efficiency, KiranaPro will incorporate ZuperAI’s “Matchmaking AI” technology as part of this collaboration. The connection would help businesses grow their business while also making it easier for users to find products. The fast commerce startup hopes to create a tailored shopping experience while bridging the gap between consumers and retailers. Deepak Ravindran, the founder and CEO of KiranaPro, stated that this partnership is revolutionary for AI-powered business, opening up new possibilities for accuracy, customisation, and operational effectiveness.

    Joining Network of ONDC

    The fast commerce company just joined ONDC, making it the first platform in India to access the nation’s network of more than 7 lakh registered merchants. Before expanding farther into Kerala, the ONDC-powered platform will first begin operations in Hyderabad and Thiruvananthapuram. KiranaPro was founded in 2024 by Ravindran and Dipankar Sarkar with the goal of transforming traditional kirana (retail) establishments by providing them with a flexible income model and an AI-driven interface that aids in managing their digital operations. KiranaPro links local mom-and-pop shops with consumers directly, in contrast to other quick commerce systems that rely on dark stores. Because of its collaboration with ONDC, the firm operates throughout India.

    Why Quick Commerce Companies are Keeping its Platform Hi-Tech and Updated?

    To increase its presence in the hyperlocal retail market, it also purchased Joper.app, a hyperlocal grocery delivery business, earlier this month. In addition to bolstering KiranaPro’s position in the hyperlocal commerce market, the acquisition of Joper.app guarantees local business owners superior tech-enabled solutions that enhance productivity and customer satisfaction, according to Deepak Ravindran, co-founder and CEO of KiranaPro. The action is in line with KiranaPro’s goal of enabling small merchants to take on the big rapid commerce titans. KiranaPro and the merchants collaborating with the brand will benefit from Sumit Gorai’s (founder of Joper.app) knowledge and insights on the mechanics of operating a retail business in India, which he frequently discusses on his YouTube channel.

    The growth coincides with intense competition in India’s fast commerce market. Leading companies like Zomato, Swiggy, and Zepto are rapidly growing their quick commerce services, which allow them to deliver food and household necessities in as little as ten minutes. These companies have recently introduced a number of rapid commerce services, such as Swiggy’s SNACC, Zomato’s Bistro, and Zepto Cafe, among many more. Additionally, Zomato’s Blinkit launched a 10-minute ambulance service last month. Notably, the three giants collectively recorded over $1 billion in revenue in FY24, and a survey indicates that sales in India’s rapid commerce sector have increased by 280% over the past two years.

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  • Beyond Major AI: How India is Shaping its Distinct AI Revolution?

    IT Minister Ashwini Vaishnaw stated that India aims to develop small language models (SLMs) to address “distinct” issues, in addition to a large language model (LLM). Vaishnaw stated that the government is examining its own digital models with smaller models that can address specific, distinct issues.

    During a virtual address at the Nasscom Technology and Leadership Forum 2025, the IT minister stated that the government is concentrating on generating a substantial quantity of non-personal and anonymised datasets for the training of domestically developed fundamental artificial intelligence (AI) models. Vaishnaw also enquired whether the country can establish a robust research foundation. India has established centres of excellence (CoEs), three of which are presently operational, with an additional one allocated in the budget.

    Digital Public Infrastructure Acting as a Catalyst

    Vasihnaw emphasised that structured data derived from state-supported digital public infrastructure (DPI) will enable India to “distinguish itself” in the forthcoming months and years in the AI competition. Vaishnaw observed that the Centre is utilising AI throughout the India Stack, including services like Digi Yatra, Aadhaar, and UPI. The Minister stated that the outcomes had been exceptional. The efficacy of DPI can be amplified by factors of 10, 15, or even 100, and we incorporate AI in this process.

    This will be a significant advantage for us due to our existing foundation. In a virtual fireside chat, Vaishnaw announced that Japan has granted a patent for UPI’s “gateway system.” A distinguished media site reported that the IT minister indicated the nation intends to shift from a services-orientated economy, particularly in IT services, to a product-centric powerhouse in sectors including semiconductors, AI, and consumer electronics. He stated that India’s aspirations in AI surpass simple service delivery or application creation. India might have confined itself to being a hub for use cases and application service provision, but the nation aspires to achieve far greater ambitions.

    Government’s Future Plan in the AI Sector

    The minister stated that the Centre is pursuing a comprehensive AI strategy, which encompasses the development of indigenous fundamental models, the creation of anonymised non-personal datasets for training, the establishment of centres of excellence for AI research, and the integration of AI education into institutions. The IT minister disclosed that 25 semiconductor products will be developed at the five upcoming semiconductor units in the country, where construction is currently ongoing.

    Regarding AI governance, Vaishnaw emphasised that the Centre will maintain a regulatory approach that fosters innovation rather than hinders it. “We must address the potential harm to society and regulate it; yet, we should not allow innovation to be suppressed as has occurred in numerous other nations,” he stated.

    This follows closely behind reports indicating that the Centre has received a minimum of 67 proposals for the development of a domestic AI basic model. The government has allegedly received offers for the development of 20 LLMs from domestic AI businesses, including Sarvam AI, CoRover, and Ola’s Krutrim.

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  • India Is Developing AI Governance Regulations: FM Sitharaman Nirmala

    Union Finance Minister Nirmala Sitharaman said at the 6th Convocation Ceremony of the Indian Institute of Information Technology (IIIT) Kottayam on 22 February that India is not only embracing AI but is also actively draughting regulations to guarantee its efficient governance. According to her, India is not only at the forefront of the use of artificial intelligence (AI), but it is also influencing its governance through stakeholder participation. The Minister underlined the government’s efforts to boost science, technology, and innovation as well as next-generation industries like drones and space.

    Commenting on this development, Rashmi Kulkarni, Co-Founder and Director- IndoAI Technologies Pvt. Ltd. stated, “Developing AI governance regulation in India is taking a step forward for responsible AI development. Defining a regulatory framework is essential for ensuring AI systems are transparent, secure and unbiased. We know now AI is going deeper into important sectors like authentication using face recognition, security and automation, well defined frameworks will be a plus to give clarity on the data privacy and compliance requirements. Finance Minister has taken the opportunity to set global standards by crafting AI regulations that will definitely encourage collaboration between policy makers and industry experts. To build trust in AI, a future proof framework of AI regulations will be the key and which will drive responsible AI development by the experts.”

    Echoing similar sentiments, Amit Chandel, Co-Founder and Chief Technology Officer, Olyv, told, “India is taking significant steps towards creating regulations for artificial intelligence (AI) governance, as envisioned by Finance Minister Nirmala Sitharaman. She emphasised the nation’s determination to not only embrace AI technologies but also their responsible application in different sectors. This move is essential for promoting innovation while protecting ethical standards. The Minister pointed out that India is at the forefront of AI adoption, with an emphasis on developing a framework that ensures transparency and accountability. She said, while highlighting the need for a structured approach to AI governance that India is formulating policies that will ensure AI is used responsibly and ethically, following the country’s national values. For tech leaders, this regulatory framework is crucial in helping to address risks involved in deploying AI, including bias and privacy.”

    Prime Minter Modi at AI Action Summit in Paris

    The Finance Minister mentioned Prime Minister Narendra Modi’s remarks at the recent AI Action Summit in Paris, which India and France co-chaired, when he discussed AI as a global issue rather than merely a domestic one. She emphasised how crucial it is that AI be moral, inclusive, and reliable. The Minister emphasised a number of important programs meant to encourage creativity and independence in India. She underlined the ‘India AI Mission,’ which was initiated with a budget of INR 10,300 crore to finance AI start-ups, create computing infrastructure, develop domestic AI skills, and attract AI talent. Furthermore, in 2023, three Centres of Excellence in Artificial Intelligence were announced, with a focus on Sustainable Cities, Healthcare, and Agriculture. This year’s budget also included a new Centre of Excellence for Education.

    Commenting on this development, Dipal Dutta, CEO – RedoQ said, “India’s decision to establish comprehensive AI governance regulations will mark a significant step in the country’s technological advancement. The country is already trying to take a leap in the AI sector with initiatives like the India AI Mission, which aims to boost the infrastructure development and set a foundation for responsible and ethical AI practices. With such initiatives, the country is ensuring that its AI ecosystem grows in a structured and sustainable manner. Prime Minisiter Modi’s recent participation in the Paris AI Summit highlights India’s commitment in engaging in global discussions on AI governance. The proactive stance will ensure that the country’s tech sector remains competitive as Western countries actively frame policies to regulate AI. Theregulatory clarity will encourage investment and allow Indian companies to scale AI-driven solutions with more confidence.”

    India’s Space and Technology Progression

    The Minister discussed India’s space technology developments, pointing out that IN-SPACe has inked more than 70 Memorandums of Understanding (MoUs) with non-governmental entities (NGEs) to facilitate space operations. In addition, she emphasised the National Green Hydrogen Mission, which was established in January 2023 with a five-year budget of INR 20,000 crore with the goal of making India a global centre for the production, use, and export of green hydrogen and its byproducts.

    Using programs like the India Semiconductor Mission (2021), the National Quantum Mission (2023), and the creation of a ‘Anusandhan’ corpus of Rs1 lakh crore for long-term funding of research in emerging fields, the Minister reaffirmed the government’s commitment to promoting research and innovation.

    She also emphasised the establishment of five National Centres of Excellence for Skilling to give young people industrial skills and the proposal for 10,000 PM Research Fellowships for technological research at IITs and IISc. India’s position in the Global Innovation Index has risen dramatically, she noted, going from 81st in 2015 to 39th in 2024. Additionally, the nation’s patent-to-GDP ratio has grown significantly, rising from 144 in 2013 to 381 in 2023.

    Furthermore, according to the World Intellectual Property Organization (WIPO) in 2023, India now ranks sixth globally in intellectual property registrations and seventh in terms of intangible asset intensity. India’s advancement towards greater innovation and independence is reflected in its increased Network Readiness Index ranking, which rose from 79th in 2019 to 49th in 2024.

    The Minister underlined that the government has gathered a lot of feedback from interested parties and is constantly developing regulations to guarantee AI gets the attention it needs. She underlined India’s proactive involvement in creating international AI regulations and confirmed the country’s leadership in AI adoption and governance.

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  • Mira Murati, Former CTO of OpenAI, Starts Startup for AI Research and Products

    Mira Murati has started her own artificial intelligence (AI) company, “Thinking Machines Lab,” over five months after leaving her position as CTO of OpenAI. The company’s objective, according to Murati, who announced the launch on X, is straightforward: develop AI by making it widely applicable and intelligible through sound foundations, open science, and real-world applications. The goal of the AI research and product startup is to close the current gaps in AI and increase the systems’ general capability, understandability, and customisability.

    Although AI skills have significantly improved, there are still significant gaps, according to the company’s blog post. The fast-developing capabilities of frontier AI systems are not well understood by the scientific community. The best research labs hold the majority of the knowledge on how these systems are educated, which restricts both the public conversation about AI and people’s capacity to use it efficiently. Furthermore, despite their potential, people still find it challenging to adapt these systems to their own needs and values.

    What Thinking Machine Lab will Offer?

    Rather than concentrating on creating completely autonomous AI systems, Thinking Machines Lab will create customised AI systems with sophisticated multimodal capabilities. According to the AI firm, it intends to regularly release technical papers, blog entries, and code that emphasise cross-industry human-AI collaboration. Many of the roughly 30 workers at Thinking Machines Lab have prior experience with firms like OpenAI, Google DeepMind, Character AI, and Mistral AI. After working with OpenAI for six years, Murati departed the company in September of last year. She stated that she was taking a break to “do her own exploration” at the time of her departure. She is Thinking Machines Lab’s CEO.

    Barret Zoph, the CTO of Thinking Machines Lab, left OpenAI in September of last year. The company’s principal scientist is John Schulman, who departed OpenAI for rival company Anthropic in August of last year. According to reports, Murati is negotiating to raise $100 million for her new AI business from unidentified VC firms. The corporation did neither confirm nor deny if it had raised money in its blog post.

    Growing Network of AI Startup

    The most recent addition to the already saturated AI startup market is Thinking Machines Lab. In the global competition to develop generative AI models, it will face off against industry titans including OpenAI, Anthropic, Meta, Google, and Microsoft. India’s increasing need for AI hardware and software has opened the door for a new wave of entrepreneurs that prioritise using GenAI technology in consumer and corporate applications over infrastructure development. India is home to more than 200 GenAI businesses, which have earned a total of $1.2 billion in funding since 2020, according to the report “The Rise of India’s GenAI Brigade.”

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  • ITU and DoT Collaborate on AI-Powered Digital Twins

    A strategic relationship aimed at improving AI-driven digital twin technologies has begun with the signing of a Letter of Intent (LoI) between the Department of Telecommunications (DoT) and the International Telecommunication Union (ITU). The goals of this partnership are to advance sustainable development, create international standards, and stimulate innovation in infrastructure planning. The LoI will lay the groundwork for a number of projects that will incorporate next-generation technologies—such as digital twins, AI-driven solutions, and IMT-2030 technologies—into frameworks that will help vital industries like healthcare, urban development, and transportation.

    In an effort to bolster India’s position as a global leader in digital connectivity, Dr. Neeraj Mittal, Secretary of the Department of Telecommunications, signed the LoI while on an official visit to Geneva. Dr. Mittal talked on India’s leadership in 5G and 6G technologies, AI for digital transformation, and cybersecurity frameworks in talks with ITU leadership, including ITU Secretary-General Ms. Doreen Bogdan-Martin.

    India Cementing its Strong Base in Telecommunication Field

    The ITU’s Partner2Connect program, which attempts to close the global digital gap, was another topic of debate. India reiterated its dedication to backing ITU projects, especially those pertaining to skill development and global connectivity.

    Dr. Mittal suggested during his visit that India host the ITU-Plenipotentiary Conference in 2030. Positive reactions were received to this suggestion, and more talks will take place at the next ITU Council Meeting. This plan has a strong basis thanks to India’s recent achievement in hosting the World Telecommunication Standardisation Assembly (WTSA-2024) in New Delhi. By hosting the conference, India would further solidify its position as a focal point for international policy discussions on ICT legislation and telecommunications, thus influencing the direction of global connectivity.

    An important development in the function of telecommunications is the partnership between the DoT and ITU. Next-generation mobile communication technologies are platforms for flexible and dynamic infrastructure planning, not just for connectivity. AI and digital twins can be used to deliver real-time, intelligent data that radically alters the planning, design, and implementation of infrastructure and cities. Better planning, monitoring, and management of infrastructure projects are made possible by digital twins, which provide virtual versions of actual systems, increasing sustainability and efficiency.

    What AI-driven Digital Twin Technologies can Offer?

    Pervasive intelligence can be produced by AI-driven digital twin technologies, enabling open, networked systems that transform stakeholder collaboration on infrastructure projects. These developments make it possible to approach infrastructure and urban planning with greater flexibility and responsiveness, resulting in solutions that are better able to adjust to shifting circumstances. By opening up new business models, this strategy makes it possible to provide scalable, data-driven solutions that support long-term growth in vital industries. By using a comprehensive approach, future infrastructure will be durable and innovative, able to adapt to changing needs.

     The LoI lists a number of important areas for cooperation. Knowledge sharing and capacity building will be a key focus, promoting the sharing of ideas from projects such as the ITU’s Citiverse platform and the DoT’s Sangam project. Better data integration and cross-sectoral cooperation will be made possible by this partnership. The creation of international standards through contributions to ITU-T Study Group 20, which focuses on digital twins, smart cities, and the Internet of Things, is another crucial topic. The objective is to develop international standards and procedures that guarantee the interoperability and scalability of AI-driven solutions. In order to verify the revolutionary potential of digital twin technologies, DoT and ITU will also set up sandbox environments for testing and trial initiatives. In order to promote more participatory government, AI-powered platforms will also be utilised to involve individuals in urban planning.

    Lastly, by customising solutions to fit the unique requirements of various nations, the partnership will concentrate on privacy-enhancing methods in ICT measurement and AI model integration for digital twins. This partnership ushers in a new era of global infrastructure planning that promotes sustainability and creativity. An important step towards building a more sustainable and interconnected future for global infrastructure is this alliance.

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  • India-Qatar Commerce Expanding Beyond Energy to Include AI and Semiconductors, According to Piyush Goyal

    On February 18, India’s Commerce Minister Piyush Goyal stated that the country wants to expand its commerce with Qatar beyond energy supplies to include semiconductors and artificial intelligence (AI). At the first meeting of the India-Qatar Business Forum on February 18, Goyal stated that while India welcomes energy products from Qatar, he believes that both countries are now looking to the future, with AI, the internet of things, semiconductors, and other technologies replacing energy as the mainstay of their trade.

    Piyush Goyal went on to say that sustainability, technology and entrepreneurship, and energy will be the cornerstones of the future India-Qatar collaboration. The State of Qatar’s Minister of Commerce and Industry, Sheikh Faisal bin Thani bin Faisal Al Thani, was also in attendance at the Forum in New Delhi.

    Signing of MoUs

    The Confederation of Indian Industry (CII) and the Qatari Businessmen Association (QBA) have inked two Memorandums of Understanding (MoUs); Invest India and Invest Qatar have also signed one. Additionally, Minister Goyal declared that the Joint Working Group on Trade and Commerce would henceforth be at the ministerial level.

    Petroleum goods, plastics, and aluminium products are among the main items that India imports from Qatar, while its exports to Doha include cereals, copper products, iron and steel items, fruits, and vegetables, among other things. As of April–November 2024, India has a $6.9 billion trade deficit with the other country.

    Encouraging Companies from Qatar to Invest in India

    Piyush Goyal also extended an invitation to Qatari businesses to participate in India’s expansion in smart city development, manufacturing, renewable energy, and infrastructure. Goyal went on to say that India’s Viksit Bharat 2047 and Qatar’s Vision 2030 will work together to create a far larger and more promising future for their respective populations. India offers an oasis of stability, predictability, and continuity, Goyal said, adding that the country’s industrial evolution is largely due to its dynamic economy, rich population, reforms, ease of doing business, and quality. Referencing Prime Minister Narendra Modi’s remarks, the minister said that confidence in India is more than ever in both major countries and worldwide forums. He also exhorted corporate executives to continue this collaborative and self-assured attitude. He continued by saying that India has a young population, a thriving economy, ongoing reforms, and a strong emphasis on industrial growth and ease of doing business.

    According to Dr. Ahmed Bin Mohammed Al Sayed, Qatar’s Minister of State for Foreign Trade Affairs, the country is eager to broaden its economic connections with India beyond the conventional oil and gas industry, concentrating on new ventures and investments. Dr. Al Sayed emphasised the significance of Sheikh Tamim Bin Hamad Al Thani, the Amir of Qatar, visiting India in an exclusive interview with an Indian media outlet. He underlined that the visit is a reflection of the two countries’ solid strategic collaboration in a number of areas.

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