IT stocks witnessed sharp losses on Friday, April 10, with the Nifty IT index crashing almost 3% after Anthropic introduced a preview of its new model, Mythos, which is being positioned as a significant leap over earlier models such as Claude Opus on coding and security benchmarks. Meanwhile, TCS logging its since listing, despite Q4 recovery, also dampening the sentiment.
In comparison, the Indian stock market rose over 2%, following gains in global equities, despite concerns over the fragile two-week US-Iran ceasefire deal.
Almost all constituents were in the red. Coforge was the top loser, declining 3.5% I nthe Nifty IT index, while Infosys, Mphasis and TCS also rose over 3% each. Meanwhile, LTIMindtree, HCL Tech, and Persistent Systems were up between 2-2.5% each, and Tech Mahindra added around 1.8% in today’s deals. Meanwhile, Wipro and L&T Tech were the only 2 stocks in the green, up 0.5% and 1.4%, respectively.
What is Anthropic’s latest development?
Instead of a full-scale public rollout, the company has opted for a controlled deployment through Project Glasswing, Anthropic’s most advanced cybersecurity-focused model, granting access to a closed group of partners including Amazon Web Services, Apple, Broadcom, Google, JPMorgan Chase, Microsoft and NVIDIA.
The Mythos model is being positioned as highly advanced in identifying and fixing cybersecurity vulnerabilities, with capabilities that reportedly outperform both human experts and existing automated tools. The system is also capable of identifying and exploiting vulnerabilities across major operating systems and web browsers when directed by users, highlighting both its potential and associated risks.
At its core, Mythos is a next-generation AI system focused on cybersecurity and deep code analysis.
Impact on IT services
IT stocks have come under renewed pressure, as fresh concerns around earnings add to already elevated fears of AI-led disruption.
Back in February, the Nifty IT had fallen around 20% after a global tech sell-off, triggered by worries that AI start-ups—especially following developments from —could disrupt traditional IT services. The fear was that AI could reduce demand for outsourcing by automating coding and enterprise functions.
The current sell-off, however, is being driven by evidence of this slowdown, after Tata Consultancy Services reported a decline in dollar revenue despite a stronger dollar. This indicates weaker client spending, reinforcing concerns that AI disruption may already be impacting growth for legacy IT firms.
The IT major posted a 0.5% decline in full-year revenue in dollar terms to $30.08 billion, alongside a 3.5% rise in net profit. In the fourth quarter, revenue grew 1.5% sequentially to $7.62 billion, indicating a mild pickup in momentum toward the end of the year. Much of the annual decline was driven by weakness in its India business, whose revenue fell 32% during the period.
Meanwhile, it reported a 12.2% year-on-year (YoY) rise in consolidated profit for Q4 at ₹13,718 crore, and its consolidated revenue rose 9.6% YoY to ₹70,698 crore in Q4FY25.
What is Mythos different?
Amid the latest advancements in capabilities, analysts believe the evolution of models like Mythos could have meaningful implications for IT services and enterprise adoption trends.
According to Motilal Oswal Financial Services, “We see this as a meaningful development. It builds on Anthropic’s recent product launches cadence and could represent the next step in pushing the AI frontier.”
MOSL noted that Mythos builds on the significant capability gains seen in Opus, which, upon its release in Feb’26, had triggered a sharp selloff in tech and SaaS stocks. While the current rollout may not have a similar market impact, it further expands AI’s edge over humans across coding, ERP, and now cybersecurity.
The brokerage further added that Mythos reflects the rapid advancement of AI capabilities beyond coding into areas like cybersecurity, while highlighting that adoption remains easier in greenfield, cloud-first environments. In contrast, legacy-heavy enterprises face slower adoption due to integration, data cleanup and governance requirements, with 90% of top OpenAI token users being new-age companies, underscoring the scaling challenge.
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