India’s AI Product Moment: A Structural Shift in Tech Creation
Over the past year, India’s technology landscape has entered an unmistakable transition. What was once a predominantly services-led success story is now witnessing an accelerated push towards AI-native product creation, particularly from deep-tech startups. According to one recent analysis, the Indian AI market is projected to reach around US$13.05 billion in 2025, up from US$9.51 billion in 2024. From a financial viewpoint, India’s IT & ITES sector, historically driven by export-linked service revenues, is now seeing rising investments flow into AI product innovation. According to an IDC report, AI spending in India is expected to generate an economic impact of over US $115 billion by the end of 2027.
This structural shift is critical. The new cohort of deep-tech ventures is not limiting itself to application-layer AI tools; instead, it is targeting model-building, domain-specific agents, cybersecurity automation, AI-led code generation, and sectoral intelligence systems. This movement up the value chain is important because it places Indian companies closer to IP ownership—a long-term lever for economic value creation.
Deep-Tech Startups Moving Up the Value Chain
A defining pattern visible in 2025 is the shift from service wrappers to full-stack AI products:
⦿ Vertical AI products in fintech, healthcare, logistics, and compliance automation.
⦿ AI engineering tools designed to support DevOps, cloud optimisation, and cybersecurity—areas where Indian IT traditionally offers services but now seeks platform ownership.
⦿ Edge-AI innovation, supported by the semiconductor and embedded-systems ecosystem, enabling startups to target manufacturing, retail, and mobility use-cases.
⦿ Enterprise AI co-pilots trained on secure, domain-bound data sets, appealing to global clients seeking customisable automation.
From an industry standpoint, this movement reduces long-term dependence on labour-arbitrage revenues and expands the scope for annuity-driven subscription models, thus strengthening revenue predictability.
Economic & Financial Implications for India’s IT & ITES Ecosystem
The macroeconomic backdrop adds important context. The broader IT & BPM industry in India is projected to become a US$350 billion industry by 2026 and contribute roughly 10 % of India’s GDP. Meanwhile, generative-AI adoption in the Indian IT industry is projected to boost productivity by up to 43-45 % over the next five years.
Key implications include:
⦿ Capital-allocation shifts: Startups and mid-size IT firms are allocating a larger share of annual capex towards model-training, data infrastructure, and GPU leasing rather than traditional facility expansion.
⦿ Revenue-recognition complexity: AI platforms built on usage-based pricing introduce new considerations for cross-border tax, transfer-pricing, and intellectual-property treatment.
⦿ Margin-profile evolution: While early-stage model development elevates costs, long-term scalability improves gross margins, making AI products financially appealing once customer adoption stabilises.
⦿ Domestic economic relevance: AI products are becoming exportable digital assets, enhancing India’s technology trade balance and reducing reliance on head-count-driven export billing.
From a workforce productivity and skilling perspective, the transition from service-delivery to product-creation demands higher-order capabilities and tighter controls around data-quality, model-risk, and product-lifecycle management.
Regulatory & Compliance Considerations in an AI-First Environment
From a compliance perspective, the evolving digital regulatory environment in India demands attention. The rollout of the Digital Personal Data Protection Bill (DPDP) rules and ongoing amendments to the Information Technology Act 2000 require startups to strengthen data-governance, security protocols, and audit trails.
For enterprises integrating AI products, this means:
⦿ Building transparent model documentation.
⦿ Ensuring auditability of automated decision-making systems.
⦿ Managing cross-border data transfer in alignment with DPDP obligations.
⦿ Implementing cybersecurity measures aligned with the emerging Computer Emergency Response Team (India) (CERT-In) guidelines.
These compliance obligations carry financial significance, affecting risk disclosures, internal controls, and contractual conditions for global clients.
The Road Ahead
In my view, India’s AI product revolution is no longer a peripheral trend- it is a structural reorientation of the country’s technology economy. As deep-tech startups continue moving up the value chain, the IT & ITES sector stands to gain through stronger IP creation, new export channels, improved margin structures, and reduced dependence on legacy business models.
The next phase—spanning 2025 to 2027—will likely determine whether India can position itself not just as the world’s technology workforce, but as a global producer of AI-native digital infrastructure, enterprise platforms, and domain-specific intelligence systems. I look forward to continued dialogue on these emerging developments.
Uploaded On: 
Author: 
