The well-established, globally recognised Indian IT services business model now faces existential threat. For years the model has been anchored in cost efficiency, labour arbitrage, operational rigour, and scaled delivery. It mastered execution, industrialized technology transformation, and became the digital backbone of global enterprises. In fact, very few industries reflect India’s global dominance as strongly. From capitalising on the internet boom of the 1990s to resoundingly navigating the Y2K transition, Indian IT has repeatedly turned technological inflection points into engines of growth, emerging stronger each time.
But the AI age is different. It is not just another technology wave, but a structural rupture. For the first time, the disruption is striking at the very core of the industry’s value engine: talent-based execution itself. The Indian IT industry was built on an activity-driven, people-intensive model where scale of effort determined scale of revenue. But AI is now dismantling that foundation. It is autonomously writing production-grade code, executing tests, resolving support tickets, generating documentation, and even performing analytical and advisory tasks, that too, faster, cheaper, and at scale.
For an industry long anchored in activity over outcomes, this is exponential disruption. The very work that powered the rise of the industry is being automated at speed. My research as part of my latest book Human Edge in the AI Age suggests that within five years, nearly 30% of global white-collar roles (~300 million jobs) could be impacted by AI, with up to 100 million at risk of automation. For India, where services sector drives more than half of GDP and employs nearly a third of the workforce, the exposure is structural and significant[1].
The warning signs are already visible. The release of new agentic AI tools by Claude Cowork, triggered a seismic market repricing that erased hundreds of billions in value. A stark proof on how swiftly AI breakthroughs can upend the foundations of the technology industry. As AI matures and autonomously executes workflows, the traditional people-intensive services model faces eventual obsolescence.
Reimagining the value model: From Activity to Outcomes
The industry can no longer rely on past laurels and established operating models if it has to remain relevant. The activity-driven, execution-centric model that powered three decades of extraordinary growth has shifted from being a competitive advantage to a structural vulnerability.
A decisive pivot toward outcome-oriented operating models is now imperative. As AI compresses technical effort, effort itself is no longer a proxy for value. Delivery excellence, while essential, is no longer sufficient.
Clients are demanding measurable business impact such as revenue expansion, new product innovation, dynamic pricing, sharper underwriting accuracy, lower fraud losses or a more resilient supply chain. Domain depth must translate into end-to-end accountability, anchored in outcome-based engagement models and shared KPIs.
Technology enablement is now table stakes. Business transformation is the mandate.
From Incrementalism to Reinvention
The shift from activity to outcome orientation requires a fundamental redesign of the industry’s value creation engine.
The first imperative is to move from projects to platforms and solutions. The traditional model sells discrete project engagements – build this system, migrate that application, test this release. AI compresses the effort required for each of these initiatives, shrinking project-based billing. The pivot is to develop AI-native platforms where business context, data infrastructure, and AI capabilities are wired together to deliver business outcomes and not just deliver technology building blocks.
As AI absorbs execution work, the workforce model itself must be fundamentally reimagined. As AI matures, and workflows become autonomous, the role of humans will continue to shrink in scale but also become increasingly complex. In the AI era, technical skills might become less critical. Instead, capabilities such as deep domain expertise, first-principles problem solving, and creative thinking will emerge as true differentiators. Humans must reimagine the enterprise, redefining workflows and operating models, while AI executes, optimizes, and scales with precision.
An outcome-driven business cannot be built on a services mindset alone. It demands product centric approach grounded in an entrepreneurial mindset – embracing risk, experimenting boldly and driving change in complex business environments to create new business value. This is a profound leap from maximizing utilization to maximizing impact.
It also calls for a structural overhaul of the industry’s economic foundations. The IT services industry has always been a P&L driven business, optimizing for margins and linear revenue growth. But outcome ownership demands upfront investment, higher risk, and non-linear thinking.
In essence, the industry must master a difficult duality: embracing a product-first mindset while preserving the delivery excellence that earned its credibility. That means operating at two-speeds, that enables rapid experimentation and IP creation on one hand, and high-quality execution at scale on the other.
Reinvent now, or Risk Irrelevance
This disruption is undeniably a historic challenge but it is also a once-in-a-generation opportunity. The Indian IT industry has over time built some formidable strengths: global reputation in delivery excellence, deep technology capability, rich business and domain expertise, operational rigor and a tech-forward workforce. It is now time to leverage them as launchpads to build the new competitive edge.
But let us be absolutely clear: the magnitude of this challenge is enormous and the window to act is rapidly closing. We cannot rely on the playbook of past technology waves. If AI is treated as business as usual, the industry will not just slow down, its very foundation will crumble.
This is not a gradual evolution. It is a decisive reset.
