The rapid ascent of generative artificial intelligence has sparked a fierce debate across the global technology sector regarding the long term viability of traditional IT services providers. As enterprise clients increasingly experiment with cutting edge models from startups like Anthropic, some market analysts have suggested that the era of the large scale technology consultancy may be drawing to a close. However, the leadership at Cognizant Technology Solutions is now pushing back against this narrative, arguing that the perceived threat to industry giants is significantly overblown.
Babak Hodjat, the Chief Technology Officer for AI at Cognizant, believes that while the landscape is shifting, the foundational role of the service provider remains more critical than ever. According to Hodjat, the integration of advanced models like Anthropic’s Claude into business workflows is not a simple plug and play process. Large corporations face immense hurdles involving data privacy, legacy system compatibility, and the sheer complexity of scaling AI across diverse global departments. These are areas where established firms possess decades of institutional knowledge that small AI labs simply cannot replicate.
Investors have been particularly skittish about the sector, fearing that automated coding and self healing networks might reduce the headcount requirements that drive revenue for firms like Cognizant, Infosys, and Tata Consultancy Services. This anxiety has been reflected in fluctuating stock prices and cautious quarterly earnings forecasts. Yet, the reality on the ground suggests a different trajectory. Rather than replacing the service layer, AI is acting as a catalyst for a new wave of modernization projects that require human oversight and strategic implementation.
The partnership between Cognizant and Anthropic serves as a primary example of this new ecosystem. By embedding Claude’s capabilities into its internal operations and client facing solutions, Cognizant aims to increase efficiency rather than succumb to obsolescence. The goal is to move up the value chain, transitioning from manual infrastructure management to high level AI orchestration. Hodjat emphasizes that the sheer volume of data within a Fortune 500 company requires a sophisticated intermediary to ensure that AI outputs are accurate, ethical, and secure.
Furthermore, the complexity of the modern regulatory environment provides a natural moat for large IT firms. As governments around the world introduce disparate frameworks for AI governance, multinational corporations need partners who can navigate these legal minefields. A standalone AI model can generate content or code, but it cannot ensure that a global supply chain remains compliant with the European Union’s AI Act or various regional data residency laws. This compliance layer is becoming a major revenue driver for the traditional IT services sector.
There is also the matter of the productivity paradox. While AI can certainly speed up individual tasks, it often creates a secondary need for more rigorous testing and validation. As more code is generated by machines, the demand for expert human review increases to prevent the accumulation of technical debt. Cognizant’s leadership argues that this shift actually expands the addressable market for IT services, as clients now require help managing the massive influx of automated outputs.
Ultimately, the narrative of disruption is often more dramatic than the reality of corporate adoption. History has shown that when transformative technologies like cloud computing or mobile internet first emerged, the initial forecast was the death of the incumbent. In each instance, however, the incumbents that successfully pivoted ended up larger and more integrated into their clients’ operations than before. Cognizant appears confident that the AI revolution will follow this historical pattern, transforming the nature of their work without eroding the necessity of their existence.
