India’s technology sector has entered an unusual period of volatility following Anthropic’s recent rollout of Claude Cowork—positioned as an enterprise-ready “digital worker” capable of autonomously executing multi-step professional tasks. Introduced on January 16 and expanded with 11 workflow plug-ins on January 30, the tool has drawn attention for its ability to perform several categories of work traditionally handled by large offshore teams.
The market response was immediate. On February 3 and 4, the Nifty IT index posted its sharpest decline since the pandemic years, with leading firms such as Infosys, TCS, Wipro, HCLTech, LTIMindtree and Coforge registering meaningful single-day losses. In total, close to Rs 2 lakh crore in market value was erased, reflecting investor concerns about how agentic automation may influence demand for outsourcing and enterprise software services.
Early analyses suggest that Cowork’s capacity to directly interact with enterprise systems, automate routine knowledge tasks, and bypass certain layers of integration work may alter the economics of outsourced delivery. This includes potential shifts from effort-based billing towards outcome-linked models, as well as reduced reliance on large delivery teams for structured, repeatable tasks.
Investment bank Jefferies described the moment as a “SaaSpocalypse”, reflecting concerns that AI agents may undercut the traditional value of outsourced IT and SaaS platforms. Globally, the episode is being viewed as a sign of how rapidly AI is transitioning from an assistive tool to a potential substitute for conventional software development and IT services models.
Cutting against the panic, former Infosys CEO Vishal Sikka argued the AI shift isn’t abrupt but long in the making. In an X post on February 4, 2026, he wrote that calling today’s AI disruption “sudden makes me smile,” noting he’s spent “28+ years” across software and AI. He framed the impact as uneven, borrowing Melanie Mitchell’s “jagged frontier” to explain why routine, well-defined work is accelerating first while judgment-heavy tasks remain harder to automate—an interpretation that aligns with the kinds of workflows now being targeted by agentic tools.
Meanwhile, the Economic Survey’s caution about AI’s impact on India’s services-led economy has taken on new relevance in light of Claude Cowork’s release. “With AI-driven productivity gains not translating to job growth, there's a risk of disrupting the middle class and the services-led economy,” says Jaspreet Bindra, co-founder of AI&Beyond. He highlights concerns around job displacement, the widening gap between productivity and employment, and implications for long-term economic stability.
In this evolving environment, organisations are reassessing long-term contracts, pricing structures and delivery models as agentic automation becomes more capable—and more credible.
“There is mounting evidence that organizations are moving away from traditional multi-year transformation deals towards shorter-term, pilot-led contracts spanning three to twelve months,” says DD Mishra, VP Analyst at Gartner. These shorter cycles reflect the increasing risk of locking into multi-year deals when AI capabilities—and their broader implications—are advancing at an unusually rapid pace.
Mishra adds, “The advancement in agentic AI and multi-agent systems underscores a shift from expecting prolonged deployment cycles to prioritizing rapid prototyping and agile integration.” Short-term pilots, he explains, give enterprises the ability to test operational effectiveness, integration complexity and scalability without committing to long-term contracts during a period of heightened technological uncertainty.
On large deals, Mishra notes that the emerging playbook increasingly favours hybrid structures, “where mega-deals are disaggregated into several modular engagements, each with clearly defined performance metrics and iterative review points.” He adds that large deals now incorporate “embedded AI co-pilots” that support operational continuity and process optimisation across sales, pricing, integration and support functions. “These agents are deployed across workstreams to accelerate proposals, monitor performance, and guide adjustments in real time.”
Organisations are also demanding clearer proof of value before approving large-scale programmes. As Mishra notes, “With only a small percentage achieving cost savings from AI initiatives, enterprises prefer short pilots to prove or disprove the value proposition before scaling up.”
Despite concerns around a “SaaSpocalypse,” several industry leaders remain optimistic about the opportunities opened up by AI-led shifts.
The changing technological landscape is prompting businesses to rethink not only efficiency but also long-term competitiveness. “The nature of the technological shifts indicates that every business is looking for opportunities, not only to get higher efficiency using AI, but more importantly, reimagine their whole business model using AI, to stay relevant to the end customers,” says Nitin Rakesh, CEO of Mphasis. He adds, “While seemingly disruptive, this also brings about one of the most exciting growth opportunities. Enterprise tech environments are complex and have been built over multiple generations of technology cycles.”
This transition is also reshaping talent needs across the industry. “While AI automates repeatable tasks, it is also creating new demand in areas like AI engineering, data, cloud and applied domain skills,” says Ritwik Batabyal, CTO & Innovation Officer at Mastek Global. He notes that this shift requires a renewed focus on reskilling and upskilling existing employees, along with stronger collaboration between industry and academia to build relevant training programmes.
Rakesh points out that while tools from companies such as Anthropic and OpenAI are increasingly powerful, “…they are just that, tools, unless they have the enterprise context and are engineered to operate within these complex environments.” According to him, firms like Mphasis are already seeing an expanding addressable market as new areas of technology and business spending emerge, “while ensuring that we are able to ingest these tools in our solution offerings.”
“AI is a powerful utility, foundational infrastructure, not a finished product that can simply replace industry software,” says Bhanu Chopra, founder and managing director of AI-powered SaaS solutions provider RateGain. According to Chopra, “a decade ago, many believed cloud infrastructure would move up the stack and replace enterprise applications. What actually happened was the opposite: cloud became the foundation, and SaaS exploded on top of it, because compute and storage don’t equal workflows, adoption, or business results.”
He argues that AI is likely to follow a similar pattern. Models do not automatically understand industry context. “That context is why vertical SaaS exists. And switching costs are real: SaaS is embedded into complex systems and day-to-day workflows, so replacing it is far harder than generating content or insights,” he adds.
Where AI will have the most transformative impact, Chopra says, is in strengthening SaaS rather than replacing it. “It will be between vertical SaaS companies that deeply embed AI into real industry problems and those that treat it as a bolt-on feature. AI isn’t the product. It’s the accelerator.”
First Published: Feb 12, 2026, 12:14
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