Anthropic has released a new artificial intelligence (AI) model, Mythos, which has the potential to reshape parts of the IT services value chain, particularly in cybersecurity and software engineering, believe analysts at Motilal Oswal Financial Services (MOFSL).

For the Indian IT services, the brokerage thinks AI-led disruption will not have an immediate impact on the sector, but the pressure to evolve will intensify going ahead.

Firms that can integrate domain-specific AI into their service offerings will benefit, while those reliant on traditional, labour-driven models may face gradual erosion of value, it said.

What is Mythos - Anthropic's latest AI model?

Anthropic's latest preview model, Mythos, highlighted a significant leap over its earlier Claude models, combining advanced coding capabilities with high-end cybersecurity intelligence.

According to MOFSL, the model is being rolled out in a controlled manner under "Project Glasswing", with access restricted to a select group of global technology and enterprise players.

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The brokerage described Mythos as "stronger than earlier models like Claude Opus on coding and security benchmarks".

"It is extremely large-scale (reported to be in the highest compute class) and trained specifically for deep code understanding, vulnerability detection, and exploit simulation," the brokerage said.

Mythos, the report said, identified a "27-year-old vulnerability in OpenBSD" that had remained undetected despite multiple testing cycles.

MOFSL noted that Mythos is "extremely good at identifying and fixing cybersecurity vulnerabilities," in some cases exceeding human capabilities.

The implications are far-reaching for enterprise IT environments, where security testing remains labour-intensive and fragmented.

"Traditional vulnerability assessment relies on engineers + tools. Mythos could reduce effort in testing and audit layers. Secondly, old systems are difficult to fully scan and understand. Mythos might help process codebases and identify deep issues. Lastly, bugs surviving 10-20 years is not uncommon in large systems. Mythos has shown the ability to find such issues overnight," MOFSL highlighted.

Controlled rollout reflects dual-use risks

That said, Motilal Oswal said the cautious deployment through "Project Glasswing" reflects the risks associated with the model. According to reports, Anthropic has halted the public rollout of Claude Mythos due to safety concerns.

As per a company statement the model can bypass containment measures and act beyond its intended limits.

"The model is powerful enough to both find and exploit vulnerabilities, so it is being deployed carefully to test, secure, and build safeguards first," MOFSL said.

Implications for Indian IT services

For Indian IT services firms, MOFSL believes the development is less about immediate disruption and more about gradual structural change.

The brokerage said that while Mythos does not "immediately disrupt the entire security services stack," it signals "effort compression" in areas such as testing and vulnerability assessment.

"Mythos builds on big gains in capabilities on Opus, which, released in February 2026, sent most tech/SaaS stocks tumbling down. While this release may not have the same impact on IT stocks, it further expands the list of things AI can do better than humans - coding, ERP, and now cybersecurity," it said.

Mythos' roll out shows shift towards domain-specific AI

Unlike Claude Opus, which is a general-purpose model, Mythos is highly specialised. MOFSL sees this as part of a broader transition where "AI is moving from horizontal models to domain-specific execution layers."

For Indian IT firms, this implies a need to build domain expertise around AI deployment rather than relying solely on generic capabilities. Partnerships with AI providers, already visible across companies like Infosys, Accenture and Cognizant, are likely to deepen as enterprises demand tailored solutions.

AI, LLM, and AI Agents/Tools partnerships by leading IT companies

Adoption gap may cushion near-term impact

Despite rapid advances in model capabilities, enterprise adoption remains uneven. MOFSL notes that deploying AI in large organisations is challenging due to legacy systems, data silos and governance constraints.

"AI deployment today is still easier in greenfield environments," the report states, adding that legacy-heavy enterprises require significant integration and clean-up before AI can be scaled.

This lag in adoption could provide a buffer for Indian IT companies in the near term, even as the long-term direction points towards increased automation and productivity-led disruption.

=============== Disclaimer: View and outlook shared belong to the respective brokerages/analysts and are not endorsed by Business Standard. Readers' discretion is advised.

Anthropic Mythos AI: What it means for Indian IT stocks and cybersecurity