Rajat Bansal

Has anyone watched "𝗛𝘂𝗺𝗮𝗻𝘀 𝗶𝗻 𝘁𝗵𝗲 𝗟𝗼𝗼𝗽" on Netflix? (Original track in Hindi with subtitles). A tribal woman takes a job at a rural data-labelling centre, tagging images and videos to train AI systems for global clients. It’s a powerful reminder that behind every "intelligent" model sits real people, often in low-paid, low-visibility roles. The movie surfaces hard questions about power in the AI supply chain: who truly benefits from AI, and who bears the cost in time, stress, and cultural dislocation? It shows how AI is never truly autonomous—it is shaped by the judgements, constraints, and lived realities of the humans who create and label its data. It underlines something we all know but sometimes understate in practice: good AI needs good data, and good data demands care for the people producing it. For those of us building AI in large enterprises, this documentary has two critical implications for our governance frameworks:   • 𝗗𝗶𝗴𝗻𝗶𝘁𝘆 𝗮𝗻𝗱 𝗔𝗴𝗲𝗻𝗰𝘆: "Human in the loop" cannot just mean a cheap, invisible workforce for model training; it must mean ensuring human dignity, agency, and voice all along the lifecycle.  • 𝗘𝘅𝗽𝗮𝗻𝗱𝗲𝗱 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆: Responsible AI is as much about labour, equity, and inclusion as it is about models, safety, and governance. At Lloyds Banking Group, we were one of the earliest in the industry to establish a Responsible AI and Ethics function. We continuously refresh our thinking to ensure the highest standards of ethics, supported by a monthly Data and AI Ethics Committee. Suzanne Iris Brink, PhD Belinda Doshi Ranil Boteju Nataliya Tkachenko-Love, PhD Andy Weller Mugad Oumgari

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What if India's next $10 billion infrastructure thesis isn't payments, identity, or commerce — but trust? UPI moves $2T+ annually. Aadhaar authenticates 70M+ times daily. ONDC is scaling its category. Each became infrastructure not because of a single product, but because of an underlying shared rail. The next rail is trust. Fifty million Indian businesses are now legally obligated under DPDPA. India has ~2,000 trained DPOs. Demand by 2027: 50,000 to 100,000. Three things make this an investable infrastructure thesis — not just another SaaS play: ONE: STATUTORY DEMAND, NOT DISCRETIONARY DPDPA is not optional. Every business processing personal data must comply. The TAM isn't "companies who care about privacy." It's the entire formal Indian economy. TWO: IMPORTED TOOLS CANNOT REACH THIS MARKET OneTrust, TrustArc, BigID are priced for Fortune 1000. India needs trust infrastructure at MSME pricing, with Indian regulatory grammar, supporting Indian languages. None of the global players will build this. None. THREE: EXPORTABLE TO EVERY DPI-ADOPTING NATION UPI is now live in 7 countries; Aadhaar-style stacks are being built in 15 more. A trust infrastructure designed for India can become the default for Singapore, Indonesia, Sri Lanka, Mauritius, UAE, and the broader Global South. THE DEFENSIBILITY: → Regulatory specificity (DPDPA architecture, not GDPR ported) → Network effects (consent records, vendor DPAs, certification cohorts) → Data moat (consented audit-evidence corpus) → Distribution moat (system-integrator partner ecosystem) → AI moat (Indian-language classification, DPDPA-trained DPIA models) The category we are building is not "Indian OneTrust." It is India's Digital Trust Infrastructure — the operating layer for privacy, trust, governance, and responsible data use. If you operate at the intersection of infrastructure capital, regulation, and India scale — I would like to meet you. What's your read on India's next infrastructure layer? — Rajendra Bodda Founder, DPOAssist360 · CISO + CDAIO #DPOAssist360 #VentureCapital #IndiaTech #InfrastructureInvesting #DPI

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Oracle, PayPal, Uber Cut Jobs in India; Is Al to Blame? 2026 is turning into a brutal year for white-collar workers. From PavPal and Uber to Oracle and Microsoft, companies are cutting jobs, restructuring teams and investing billions in Al. The message is becoming harder to ignore: the money isn't necessarily disappearing - it's moving from people to technology. And for workers, the consequences go beyond losing a job. Re-entering the workforce can mean lower salaries, weaker bargaining power and an urgent need to upskill Because the Al revolution may not simply replace iobs. It could redefine what makes a worker valuable. The question is no longer whether work will change. It's whether workers can change fast enough.

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Everyone’s talking about scaling GCCs. But not enough people are talking about stabilizing them. Because scale without structure is just speed without steering. As more organizations rush to expand their India footprint, the real differentiator won’t be headcount or square footage, it’ll be infrastructure maturity and operational resilience. Q) Can your data centers, networks, and systems really handle what your strategy promises? Q) Can your culture, governance, and leadership match the velocity of your growth? These are not future questions. They are this quarter’s questions. Returning to Hyderabad this weekend (Desh Wapsi) to reconnect, relearn, and reimagine what the next phase of GCC growth should truly look like. #GCC #Leadership #DigitalTransformation #Infrastructure #IndiaGrowth #Hyderabad #ReturningToIndia Achyut Menon "AK" Amrish Kumar Supriya Sethi (She/Her/Hers) Susheel Kumar Vishnu BG Vishwanadh Raju Viswanathan K S

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