Indian IT’s Inevitable Evolution: From Headcount to Impact
Indian IT is undergoing a profound shift, from manpower-intensive service delivery to AI-powered productivity, productisation, and platformisation. Traditionally, Indian IT firms acted as backend enablers. However, the distinct boundary between service and product is eroding fast. Industry leaders and emerging players agree that Indian IT companies can no longer rely on traditional models. According to Suhas AR, associate practice leader, HFS Research, a new approach called ‘services as software’ (SaS) is rapidly gaining ground, going beyond SaaS (software-as-a-service). In this model (SaS), services turn into AI-infused, packaged, modular offerings, allowing firms to scale outcomes, rather than just headcount. While startups have already embraced this shift, larger firms are still rooted in conventional delivery models.“This convergence between service and product models will become more visible and essential by 2028–2030. While this transition is already being discussed at the boardroom level in major Indian IT firms, the actual implementation on the ground is still limited, with most companies continuing to depend on traditional service delivery models,” Suhas said. India’s proven ability to build products like UPI and DBT—designed for its own unique needs and scaled successfully—stands as a template for how it can lead globally in this next evolution. As Saurabh Gupta, president (research and advisory services), HFS Research, puts it, “We are entering an era of services-as-software (SaS), a transformative model where delivering outcomes no longer depends on traditional, manpower-intensive services but is driven primarily by advanced technology, reducing human intervention and maximising efficiency.” SaS differs from the mainstream software-as-a-service (SaaS) and productisation. SaaS refers to cloud-based software applications delivered on a subscription basis. It focuses on standardised software solutions with minimal customisation or human involvement. Productisation involves turning services or expertise into repeatable, packaged offerings that can be scaled like products. In contrast, services-as-software blends services and software into a unified solution, embedding automation, AI-driven workflows, and intelligent platforms that replace manual service tasks and continuously deliver personalised value. Gupta says that this evolution enables faster delivery, cost-effectiveness, and scalability, allowing businesses to access pre-built solutions and data-driven insights that help them adapt quickly and achieve more impactful outcomes. AI is Accelerating Providing historical context, Viswanathan KS, an independent digital transformation advisor, draws parallels to the early 2000s when Indian IT moved from a linear model—where more work meant more people—to a non-linear model enabled by remote infrastructure. That evolution, marked by increased efficiency and talent reallocation (e.g., moving L1 engineers to L2 or L3 roles), paved the way for the current wave of platformisation. Companies like Wipro, Infosys, and TCS began transforming service code into reusable, licensable platforms years ago. AI is now accelerating this shift. Routine tasks like basic coding are increasingly automated, enabling engineers to focus on higher-order design and programming logic. Viswanathan explains that products like Tally, which once required full implementation support, now come pre-configured and user-ready, mirroring how service delivery itself is becoming automated, parameterised, and offered like software. Prakash Rajagopalan, head of technology consulting at Tiger Analytics, affirms that AI is pushing firms to deliver more value with fewer people. The industry is moving from headcount-based billing to impact-based outcomes. Those who hire AI-native talent and adopt an AI-first mindset are building integrated, outcome-driven offerings that are more agile and client-focused. However, this shift comes with real challenges. He urges companies to manage legacy service contracts while modernising delivery. Reskilling is crucial—not only in AI tools, but in problem-solving, solution architecture, and business strategy. Rajagopalan notes that the human-in-the-loop will remain vital but must now operate as a strategic consultant, not a task executor. HCL Technologies CEO C Vijayakumar had underscored the urgency. “The business model is ripe for disruption,” he said, pointing out that linear scaling is outdated. HCL has tasked its teams with a bold vision: doubling revenue with half the headcount. It signals a decisive break from Indian IT’s traditional growth playbook. Ready-to-Use Solutions Beyond India, the transformation is part of a global trend. According to Foundation Capital’s essay on ‘AI Service as Software’, enterprise buyers now expect ready-to-use AI agents instead of custom integrations, forcing service providers to rebuild their delivery pipelines from the ground up. Accenture, for instance, has restructured its entire services model under a new unit called Reinvention Services, led by Manish Sharma, which integrates consulting, technology, operations, and creative services into one AI-first framework. Meanwhile, Indian firms like LTIMindtree are operationalising the shift. The company recently launched its AI-powered business unit, Blueverse, employing over 300 AI agents to drive decision automation and insights delivery. This marks a clear signal that the industry is already moving from theory to execution. Mind the Gaps Yet, a notable gap in the current discourse is the limited visibility into the evolving expectations of enterprise clients. While it’s clear that buyers are seeking measurable outcomes, value-based pricing, and greater delivery assurance from AI-powered services, these demands are often underrepresented in industry conversations. Reports suggest that high upfront costs are slowing AI adoption, and clients are increasingly pushing for accountability tied to real-world impact rather than abstract promises. As agentic AI reshapes delivery, truly understanding and integrating client perspectives, especially around ROI, flexibility, and risk-sharing, will be critical for Indian IT firms to remain trusted partners. Additionally, regulatory challenges around AI governance, privacy, and observability are yet to be concretised. As global frameworks like the EU AI Act and India’s upcoming Digital India Act (replacing the Information Technology Act) come into play, Indian IT will have to adapt swiftly. Talent remains another pressure point. While upskilling initiatives exist through firms’ internal academies and programs like NASSCOM’s FutureSkills, India’s education and skilling systems still lag in preparing professionals for AI-centric roles that require both domain understanding and systems thinking. However, India’s Graduate Skill Index 2025 report by Mercer | Mettl indicates that 46% of graduates are now employable in AI and machine learning positions, showcasing a significant improvement in proficiency in these technical skills.Jaspreet Bindra, CEO of AI&Beyond, believes that AI is dismantling Indian IT’s headcount-driven model, enabling IP creation, automation, and outcome-focused growth. According to him, jobs will evolve rather than disappear—routine roles will diminish as demand for AI-savvy specialists increases. Continuous learning will drive Indian IT’s shift from a service-oriented industry to a platform powerhouse. For Indian IT, what worked for the last 30 years won’t work for the next five or in the future. The firms that adapt fastest, by reimagining delivery, retraining talent, and re-centring clients, will lead the global AI era.
Tech companies are transforming through AI-led productisation, demanding client-centric delivery, regulatory readiness, and talent with deep tech-business integration.
Tech companies are transforming through AI-led productisation, demanding client-centric delivery, regulatory readiness, and talent with deep tech-business integration.
["AI", "Indian IT companies", "Indian IT industry", "SaaS"]
["Go", "agentic AI", "machine learning", "AWS", "AI", "Scala", "Git", "Indian IT industry", "SaaS", "analytics", "Rust", "Indian IT companies", "R"]
["AI", "machine learning", "analytics", "agentic AI", "AWS", "R", "Go", "Rust", "Scala", "Git"]
Bala is a journalist covering Indian tech companies and startups from Bengaluru.