#FactCheck -AI-Generated Video Falsely Shows Sachin Tendulkar Promoting Investment Scheme
Executive Summary
A video featuring former Indian cricketer Sachin Tendulkar is being widely circulated on social media with the date “12-5-2026” displayed on the screen. In the viral clip, Tendulkar appears to promote an investment scheme, allegedly saying that people investing in the scheme today could earn Rs 80 lakh by the end of the day. Throughout the video, he is seen speaking about investment opportunities and financial returns. However, research conducted by CyberPeace Research Wing found that the video is AI-generated and misleading. The original footage was actually from an event marking the centenary celebrations of Sri Sathya Sai Baba.
Claim
A Facebook user shared the viral video on May 12, 2026, claiming that Sachin Tendulkar was endorsing a high-return investment scheme. The post quickly gained traction on social media platforms.
Fact Check
To verify the claim, we searched the internet using relevant keywords but found no credible media reports suggesting that Tendulkar had endorsed any such investment scheme. As part of our research, we extracted key frames from the viral clip and conducted a reverse image search. During the search, we found the original video uploaded on November 19, 2025, on the YouTube channel of IANS. According to the video description, Tendulkar was attending an event organized to mark the centenary year celebrations of Sri Sathya Sai Baba.
We further found a similar version of the same video uploaded on November 19, 2025, on the official Facebook page of Times Now, confirming that the footage was unrelated to any investment or financial scheme.
Conclusion
Our research found that the viral video has been manipulated using AI-generated audio or editing techniques to falsely portray Sachin Tendulkar promoting an investment scheme. The original video was from a public event related to Sri Sathya Sai Baba’s centenary celebrations and had no connection to any financial investment platform.
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Introduction
As AI becomes more deeply integrated into everyday life and industries, Google Cloud is increasing its investment in AI-ready data centres worldwide, with India emerging as a key part of its expansion plans. Thomas Kurian’s latest India visit highlighted Google Cloud’s expanding ambitions in the country. Beyond the $15 billion, 1GW Visakhapatnam data centre announced in October 2025, Google is planning a larger multi-year AI infrastructure push, backed by partnerships with major enterprises across banking, healthcare, and digital services. This reflects a shift where countries are not only competing to create advanced AI technologies but also to build the infrastructure needed to support and lead the future AI economy. But it's worth being precise about what "building infrastructure" actually means here because it is private, foreign-headquartered capital constructing facilities on Indian soil, under terms that remain largely opaque to the public that will depend on them. That distinction matters more than the investment headline suggests.
The Promise and Pressure of Google’s Full-Stack AI Strategy
For decades, data centres were mainly built to store information, host websites, and support cloud applications. The rise of generative AI has completely changed that role. Today's systems need massive computing power both to train models on huge datasets and to run them every time someone generates content or automates a task. It is distinguished from traditional workloads mainly due to relying on proprietary technologies like GPU or TPU, alongside advanced networking and dynamic storage systems that complement each other and work in unison. The efforts of Google to create its own TPUs are understandable as they played a vital role in a number of achievements made by Google DeepMind. Today, the companies, government entities, and people turning to AI solutions put enormous pressure on the processing of data.
The companies that are building this infrastructure are shaping ecosystems on which others will depend on. Google’s “full stack” approach that infers controlling everything from chips and AI models to cloud platforms and applications which may improve efficiency and reduce costs, but it also creates deeper dependence on a single provider. Like a hospital adopting an AI platform is not just purchasing software; over time, its data systems, workflows, and operations can become closely tied to the underlying cloud ecosystem.
This concern when viewed against the concentration of the global cloud market: Amazon Web Services, Microsoft Azure, and Google Cloud together control roughly two-thirds of global cloud infrastructure, making them the dominant gatekeepers of enterprise computing. As these same companies move upward into AI models and applications while controlling the compute layer beneath them, the debate is no longer only about market share, it is about control over the entire AI value chain.
Why Location Matters and Why It Isn't Enough
In traditional internet services, a delay of a few milliseconds rarely mattered. However, future AI applications like autonomous vehicles, AI-assisted diagnostics, automated factory robotics will demand near-instant decision-making and cannot always depend on servers thousands of kilometres away. Regional data centres reduce that latency, which matters especially for India, where hundreds of millions are expected to interact with AI-powered services in the coming years. There is also the question of data sovereignty, and this is where the infrastructure narrative gets ahead of the regulatory reality. Governments worldwide are increasingly concerned about where citizens' and companies' data is stored and processed and local data centres are presented as the answer, but physical proximity does not automatically translate into legal accountability. Google has acknowledged that it bills cloud revenue through whichever global entity corresponds to the data centre being accessed which means an Indian client's spending on Google Cloud infrastructure inside India may still not be booked, taxed, or contractually governed as an Indian transaction. Google Cloud India Pvt. Ltd reported just ₹2,065.4 crore in FY25 revenue, strikingly disconnected from the scale of a $15 billion facility and its roster of major Indian clients. Servers on Indian soil do not by themselves guarantee that India captures the tax base, the leverage, or the oversight that "data sovereignty" implies.
This gap is widened by where India's own data protection framework stands. The Digital Personal Data Protection (DPDP) Act, 2023 leaves retention periods and purpose limitation loosely specified under Sections 8(7) and 12, and its enforcement rules are still being finalised. When hospitals or banks process data through a foundation-model platform like Gemini Enterprise, questions like where processing occurs and what audit trail exists for cross-border flows are not resolved by a local data centre's presence. At present, they rely mostly on vendor assurance rather than independent verification.
Economic Opportunities: More Than Just Servers
AI data centres are often imagined as buildings filled with computers, but their economic impact extends further, into energy systems, construction, engineering, semiconductor supply chains, and skilled technical work. Countries hosting these facilities can benefit from investment and job creation, while local businesses gain access to AI tools without building expensive infrastructure of their own.
For India, expanded AI infrastructure could support ambitions to become a global technology hub, and could narrow the gap in access to high-performance computing that has historically disadvantaged smaller companies and researchers. That potential is real. But it should be weighed against the terms on which it arrives, whether the economic value generated is captured domestically through tax revenue and enforceable local accountability, or whether India functions primarily as a hosting site while value accrues elsewhere. The current revenue-booking structure suggests the latter is, at minimum, a live risk rather than a settled question.
The Environmental Challenge of AI Expansion
However, what remains less discussed is the environmental cost behind this expansion from its impact on the power grid and water required for cooling to clearing use of renewable energy. A 1GW facility, the scale for the Visakhapatnam project is comparable to the output of a mid-sized power plant dedicated entirely to compute demand. As models grow larger and adoption accelerates, this level of energy and water consumption has become one of the central concerns of the global AI infra. As much attention as the investment figures receive, the sustainability issue behind such large-scale infrastructure deserves equal visibility.
The Future: AI Infrastructure as National Infrastructure
The expansion of Google Cloud's AI data centres show a change in how the world views computing. Data centres are no longer invisible facilities operating in the background; they are becoming strategic infrastructure comparable to power grids and telecom networks. That comparison should prompt that infrastructure this consequential is usually made subject to public oversight, licensing conditions, and accountability mechanisms proportionate to its importance which is missing so far. Google Cloud's investment and the compute capacity it brings will lower barriers for Indian enterprises and researchers who have long lacked access to frontier-scale infrastructure. Against this backdrop, India needs to develop the regulatory, tax, and competition frameworks to ensure that the foundation serves the country hosting it, rather than the company that owns it.
Beyond Compute: The Emerging Question of AI Sovereignty
The next phase of the AI race may not be defined only by who builds the most capable models, but by who governs the infrastructure, standards, and decision making systems that those models depend upon. As advances in artificial general intelligence and discussions around superintelligence move from research laboratories into policy circles, control over compute resources is becoming a matter of strategic importance comparable to control over energy reserves or communication networks. Nations that rely entirely on external providers for advanced AI infrastructure may eventually find themselves dependent not merely for technology services, but for economic productivity, public administration, healthcare delivery, and national security capabilities. For India, the challenge is therefore larger than attracting investment. It is about ensuring meaningful domestic participation in ownership, governance, talent development, and oversight so that the intelligence systems shaping the future remain aligned with national priorities and public interest.
References
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Introduction
India's Competition Commission of India (CCI) on 18th November 2024 imposed a ₹213 crore penalty on Meta for abusing its dominant position in internet-based messaging through WhatsApp and online display advertising. The CCI order is passed against abuse of dominance by the Meta and relates to WhatsApp’s 2021 Privacy Policy. The CCI considers Meta a dominant player in internet-based messaging through WhatsApp and also in online display advertising. WhatsApp's 2021 privacy policy update undermined users' ability to opt out of getting their data shared with the group's social media platform Facebook. The CCI directed WhatsApp not to share user data collected on its platform with other Meta companies or products for advertising purposes for five years.
CCI Contentions
The regulator contended that for purposes other than advertising, WhatsApp's policy should include a detailed explanation of the user data shared with other Meta group companies or products specifying the purpose. The regulator also stated that sharing user data collected on WhatsApp with other Meta companies or products for purposes other than providing WhatsApp services should not be a condition for users to access WhatsApp services in India. CCI order is significant as it upholds user consent as a key principle in the functioning of social media giants, similar to the measures taken by some other markets.
Meta’s Stance
WhatsApp parent company Meta has expressed its disagreement with the Competition Commission of India's(CCI) decision to impose a Rs 213 crore penalty on them over users' privacy concerns. Meta clarified that the 2021 update did not change the privacy of people's personal messages and was offered as a choice for users at the time. It also ensured no one would have their accounts deleted or lose functionality of the WhatsApp service because of this update.
Meta clarified that the update was about introducing optional business features on WhatsApp and providing further transparency about how they collect data. The company stated that WhatsApp has been incredibly valuable to people and businesses, enabling organization's and government institutions to deliver citizen services through COVID and beyond and supporting small businesses, all of which further the Indian economy. Meta plans to find a path forward that allows them to continue providing the experiences that "people and businesses have come to expect" from them. The CCI issued cease-and-desist directions and directed Meta and WhatsApp to implement certain behavioral remedies within a defined timeline.
The competition watchdog noted that WhatsApp's 2021 policy update made it mandatory for users to accept the new terms, including data sharing with Meta, and removed the earlier option to opt-out, categorized as an "unfair condition" under the Competition Act. It was further noted that WhatsApp’s sharing of users’ business transaction information with Meta gave the group entities an unfair advantage over competing platforms.
CyberPeace Outlook
The 2021 policy update by WhatsApp mandated data sharing with Meta's other companies group, removing the opt-out option and compelling users to accept the terms to continue using the platform. This policy undermined user autonomy and was deemed as an abuse of Meta's dominant market position, violating Section 4(2)(a)(i) of the Competition Act, as noted by CCI.
The CCI’s ruling requires WhatsApp to offer all users in India, including those who had accepted the 2021 update, the ability to manage their data-sharing preferences through a clear and prominent opt-out option within the app. This decision underscores the importance of user choice, informed consent, and transparency in digital data policies.
By addressing the coercive nature of the policy, the CCI ruling establishes a significant legal precedent for safeguarding user privacy and promoting fair competition. It highlights the growing acknowledgement of privacy as a fundamental right and reinforces the accountability of tech giants to respect user autonomy and market fairness. The directive mandates that data sharing within the Meta ecosystem must be based on user consent, with the option to decline such sharing without losing access to essential services.
References
Introduction
In today’s digital world, data has emerged as the new currency that influences global politics, markets, and societies. Companies, governments, and tech behemoths aim to control data because it accords them influence and power. However, a fundamental challenge brought about by this increased reliance on data is how to strike a balance between privacy protection and innovation and utility.
In recognition of these dangers, more than 200 Nobel laureates, scientists, and world leaders have recently signed the Global Call for AI Red Lines. Governments are urged by this initiative to create legally binding international regulations on artificial intelligence by 2026. Its goal is to stop AI from going beyond moral and security bounds, particularly in areas like political manipulation, mass surveillance, cyberattacks, and dangers to democratic institutions.
One way to address the threat to privacy is through pseudonymization, which makes it possible to use data valuable for research and innovation by substituting personal identifiers for artificial ones. Pseudonymization thus directly advances the AI Red Lines initiative's mission of facilitating technological advancement while lowering the risks of data misuse and privacy violations.
The Red Lines of AI: Why do they matter?
The Global Call for AI Red Lines initiative represents a collective attempt to impose precaution before catastrophe, which was done with the objective of recognising the Red Lines in the use of AI tools. Thus, anything that unites the risks of using AI is due to the absence of global safeguards. Some of these Red Lines can be understood as;
- Cybersecurity breaches in the form of exposure of financial and personal data due to AI-driven hacking and surveillance.
- Occurrence of privacy invasions due to endless tracking.
- Generative AI can also help to create realistic fake content, undermining the trust of public discourses, leading to misinformation.
- Algorithmic amplification of polarising content can also threaten civic stability, leading to a demographic disruption.
Legal Frameworks and Regulatory Landscape
The regulations of Artificial Intelligence stand fragmented across jurisdictions, leaving significant loopholes aside. Some of the frameworks already provide partial guidance. The European Union’s Artificial Intelligence Act 2024 bans “unacceptable” AI practices, whereas the US-China Agreement also ensures that nuclear weapons remain under human, not machine-controlled. The UN General Assembly has adopted resolutions urging safe and ethical AI usage, with a binding and elusive global treaty.
On the front of data protection, the General Data Protection Regulations (GDPR) of EU offers a clear definition of Pseudonymisation under Article 4(5). It also describes a process where personal data is altered in a way that it cannot be attributed to an individual without additional information, which must be stored securely and separately. Importantly, pseudonymised data still qualifies as “personal data” under GDPR. However, India’s Digital Personal Data Protection Act (DPDP) 2023 adopts a similar stance. It does not explicitly define pseudonymisation in broad terms, such as “personal data” by including potentially reversible identifiers. According to Section 8(4) of the Act, companies are meant to adopt appropriate technical or organisational measures. International bodies and conventions like the OECD Principles on AI or the Council of Europe Convention 108+ emphasize accountability, transparency, and data minimisation. Collectively, these instruments point towards pseudonymization as a best practice, though interpretations of its scope differ.
Strategies for Corporate Implementation
For a company, pseudonymisation is not just about compliance, it is also a practical solution that offers measurable benefits. By pseudonymising data, businesses can get benefits, such as;
- Enhancing Privacy protection by masking identifiers like names or IDs by reducing the impact of data breaches.
- Preserving Data Utility, unlike having a full anonymisation, pseudonymisation also retains patterns that are essential for analytical innovation.
- Facilitating data sharing can allow organizations to collaborate with their partners and researchers while maintaining proper trust.
According to these benefits, competitive advantages get translated to clauses where customers find it more likely to trust organizations that prioritise data protection, while pseudonymisation further enables the firms to engage in cross-border collaboration without violating local data laws.
Balancing Privacy Rights and Data Utility
Balancing is a central dilemma; on one side lies the case of necessity over data utility, where companies, researchers and governments rely on large datasets to enhance the scale of AI innovation. On the other hand lies the question of the right to privacy, which is a non-negotiable principle protected under the international human rights law.
Pseudonymisation offers a practical compromise by enabling the use of sensitive data while reducing the privacy risks. Taking examples of different domains, such as healthcare, it allows the researchers to work with patient information without exposing identities, whereas in finance, it supports fraud detection without revealing the customer details.
Conclusion
The rapid rise of artificial intelligence has led to the outpacing of regulations, raising urgent questions related to safety, fairness and accountability. The global call for recognising the AI red lines is a bold step that looks in the direction of setting universal boundaries. Yet, alongside the remaining global treaties, practical safeguards are also needed. Pseudonymisation exemplifies such a safeguard, which is legally recognised under the GDPR and increasingly relevant in India’s DPDP Act. It balances the twin imperatives of privacy, protection, and data utility. For organizations, adopting pseudonymisation is not only about ensuring regulatory compliance, rather, it is also about building trust, ensuring resilience, and aligning with the broader ethical responsibilities in this digital age. As the future of AI is debatable, the guiding principles also need to be clear. By embedding techniques for preserving privacy, like pseudonymisation, into AI systems, we can take a significant step towards developing a sustainable, ethical and innovation-driven digital ecosystem.
References
https://www.techaheadcorp.com/blog/shadow-ai-the-risks-of-unregulated-ai-usage-in-enterprises/
https://planetmainframe.com/2024/11/the-risks-of-unregulated-ai-what-to-know/
https://cepr.org/voxeu/columns/dangers-unregulated-artificial-intelligence
https://www.forbes.com/sites/bernardmarr/2023/06/02/the-15-biggest-risks-of-artificial-intelligence/
