Editorial illustration for Indian IT Firms Reframe Data Platforms as Strategic IP Amid Cloud Partnerships
Indian IT Firms Reframe Data Platforms as Strategic IP
Indian IT companies are frantically assembling data platforms they call proprietary. Most of it is made from someone else’s parts. They have built their AI ambitions on leased land.
There’s a quiet scramble to treat these platforms as intellectual property. But the scaffolding is rented from Microsoft, Amazon, and Google. The foundational tools come from other vendors.
A senior data scientist with 14 years in the trenches, Pravat Jena of Dell, says the showmanship is convincing. Firms are brilliant at pilots and proofs-of-concept. Actually running AI at scale is a different story.
The problem isn’t a lack of engineers. It’s a lack of grown-up operating models and real governance.
In his view, data platforms are increasingly treated as internal intellectual property, even as vendors continue to depend on cloud providers and specialist partners to fill gaps. Pravat Jena, a senior data scientist at Dell with 14 years of experience in data strategy, took a more sceptical view. He said most Indian IT firms remain "strong at pilots and PoCs (proofs-of-concept)," but only a subset are consistently ready for production AI at scale.
The limiting factors, he argued, are operating models and governance maturity rather than technical capability. "Most firms are not building core platforms fully in-house," Jena said. "They rely heavily on hyperscale-native stacks, vendor tools and partnerships, with limited proprietary differentiation." Both Datta and Jena agreed that data quality and governance remain the weakest layers in AI programmes.
Jena described governance frameworks as often existing "on paper," with uneven implementation across legacy systems and multi-cloud environments. The result is that AI systems scale slowly beyond controlled use cases. Datta noted that despite regulatory pressure from India's Digital Personal Data Protection Act and emerging AI governance guidelines, only a minority of enterprises feel adequately prepared to support scalable AI workloads.
According to a 2025 McKinsey report, while almost all companies worldwide invest in AI, only 1% believe they are at maturity.
That 1% figure tells you everything. Governance exists as a policy document, not as code. It crumbles when applied across decades of legacy systems and a messy multi-cloud reality.
New regulations are raising the floor. They’re forcing companies to look at the shaky foundations under their shiny AI projects. The industry’s big moment is here.
It has met a brutal audit. The real intellectual property won’t be a platform diagram. It will be the operational grit to run it.
Few have it.
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Common Questions Answered
How are Indian IT firms transforming their approach to data infrastructure?
Indian tech giants are reframing data platforms from simple service offerings into strategic intellectual assets. This shift represents a nuanced evolution in how major IT firms approach cloud partnerships and technology development, positioning custom data platforms as proprietary technologies with inherent value.
What challenges do Indian IT firms face in scaling production AI?
According to Pravat Jena, most Indian IT firms are strong at creating pilots and proofs-of-concept (PoCs), but struggle to consistently scale production AI. The limiting factors include operational complexities and gaps between initial project development and full-scale implementation.
How are data platforms now being viewed within Indian tech companies?
Data platforms are increasingly being treated as internal intellectual property rather than standard service offerings. This strategic approach reflects a broader shift where companies are looking to create proprietary technologies with unique value beyond traditional cloud-based services.
Further Reading
- Papers with Code - Latest NLP Research — Papers with Code
- Hugging Face Daily Papers — Hugging Face
- ArXiv CS.CL (Computation and Language) — ArXiv
