Synopsis: Infosys’ partnership with Anthropic positions it at the center of a potential USD 300 to 400 billion AI services opportunity by combining Claude models with its Topaz platform to build agentic AI solutions. The move signals a strategic shift from traditional outsourcing toward outcome-led transformation and could strengthen its competitive position in the IT sector.
Amid growing fears that AI could disrupt traditional outsourcing, Infosys has taken a bold step by partnering with one of the world’s leading AI companies, positioning itself at the center of a potential USD 400 billion opportunity. Could this move mark the beginning of a new leadership cycle in the Indian IT sector?
What Happened?
Infosys recently announced a strategic collaboration with Anthropic, an artificial intelligence safety and research company, to develop and deliver advanced AI solutions for enterprises. The partnership will focus on helping companies across telecommunications, financial services, manufacturing, and software development adopt AI at scale. The collaboration will begin in the telecommunications sector with a dedicated Anthropic Center of Excellence, where the two companies will build and deploy AI agents tailored to industry-specific operations, before expanding to other sectors.
At the core of the partnership is the integration of Anthropic’s Claude models, including Claude Code, with Infosys’ Topaz AI platform. Infosys and Anthropic aim to go beyond simple automation and focus on driving real business transformation by combining advanced AI technology with deep industry expertise and large-scale engineering capabilities.
A major focus of the collaboration is on agentic AI, which refers to systems that can independently handle multi-step tasks instead of just responding to prompts. These AI agents can perform activities such as processing claims, generating and testing code, managing compliance reviews, and handling long, complex processes. Using tools like the Claude Agent SDK, the partnership will help companies build AI agents that can work continuously across workflows rather than just assisting with one-time tasks.
The collaboration will also support organizations in modernizing legacy systems by combining Infosys Topaz with Claude models to speed up migration and reduce the cost of updating older infrastructure. Building on these capabilities, Infosys and Anthropic plan to develop custom AI agents for specific industries and functions.
In telecommunications, AI agents will help improve network operations, customer lifecycle management, and service delivery. In financial services, they will assist with risk assessment, compliance reporting, and personalized customer interactions.
In manufacturing and engineering, Claude will help accelerate product design and simulations, reducing research timelines. In software development, teams will use Claude Code to write, test, and debug software, helping developers move faster from design to production. Infosys is already using Claude Code internally within its engineering teams to build expertise that can be applied to client projects.
Who Is Anthropic?
Anthropic is an American artificial intelligence company headquartered in San Francisco. It develops large language models under the Claude family and operates as a public benefit corporation focused on researching and building safe and reliable AI systems. The company aims to study AI safety at the technological frontier while deploying models that can be used responsibly by businesses and the public.
The company was founded in 2021 by former OpenAI researchers, including siblings Daniela Amodei and Dario Amodei, who currently serve as president and CEO. As of February 2026, Anthropic is estimated to be valued at around USD 380 billion.
What Is Claude & Infosys-Topaz?
Claude is a family of proprietary large language models developed by Anthropic, along with an AI assistant and a range of AI tools powered by these models. The Claude models, especially from the third generation onward, have consistently ranked among the top-performing generative AI systems available today and are widely used for enterprise applications that require strong reasoning, safety, and reliability.
Infosys Topaz is the company’s AI-first suite of services, solutions, and platforms built using generative AI technologies. It is designed to help enterprises and communities unlock new opportunities by combining advanced AI capabilities with real-world business applications.
Topaz uses Infosys’ applied AI framework to build an AI-first core that enables organizations to create intelligent solutions, improve efficiency, and drive value creation through connected digital ecosystems.
The INFY Strategy
Infosys recently unveiled its AI First Value Framework, which is designed to help enterprises adopt artificial intelligence at scale using its generative and agentic AI platform, Infosys Topaz. The company believes this shift represents a new phase for the IT services industry and could allow it to tap into an additional AI services opportunity estimated at USD 300 to 400 billion by 2030, according to a Nasscom-McKinsey report.
The framework reflects a two-part strategy. First, Infosys aims to capture new demand by offering AI-first services across key areas of enterprise transformation. Second, it plans to embed AI into its existing services to deepen client relationships and expand the share of business it handles for customers.
As part of this strategy, Infosys has identified six major areas where it sees growth opportunities. The first is AI Strategy and Engineering, where the company helps businesses design and implement AI platforms, architectures, and operating models tailored to their needs. By combining AI agents, proprietary tools, and third-party technologies, enterprises can move beyond experimentation and build unified AI-driven systems across their operations.
The second area is Data for AI, which focuses on preparing enterprise data for AI adoption. This includes building data platforms, organizing structured and unstructured information, and applying advanced data engineering techniques so companies can turn raw data into valuable insights that support analytics and real-time decision-making.
The third area is Process AI, where Infosys aims to redesign core business processes by integrating AI agents with human expertise. This allows companies to improve efficiency, enhance customer experience, and deliver better business outcomes across functions and industries.
The fourth area is Agentic Legacy Modernization, which uses AI agents to understand and upgrade older IT systems without disrupting operations. This helps companies reduce technical debt while improving flexibility and responsiveness to changing business needs.
The fifth area is Physical AI, where the focus is on embedding AI into physical devices and products. By using technologies such as digital twins, robotics, and edge computing, businesses can collect data from sensors, interpret signals, and take real-time actions to improve operations and create smarter products.
The sixth area is AI Trust, which ensures that AI systems are secure, ethical, and reliable. This includes building governance frameworks, risk controls, and security testing processes so organizations can scale AI responsibly while meeting regulatory requirements.
Why Infosys Is Partnering With The Technology That Could Replace It
Indian IT stocks recently saw a sharp sell-off as investors became worried about how artificial intelligence could affect the traditional IT services business model. The weakness was not limited to one company, stocks such as Oracle Financial Services, Coforge, L&T Technology Services, and Mphasis also declined, showing that the concern was across the entire sector. Much of this anxiety was triggered by US-based AI startup Anthropic, which launched new tools for its Claude AI agent that can automate tasks across legal, sales, marketing, compliance, and data analysis, areas that have long been key sources of work for IT services companies.
These developments have raised fears that rapid advances in AI could reduce the need for large project teams, custom software development, and labor-heavy outsourcing models that have supported the growth of India’s IT industry for decades. Experts say the worry is not about immediate earnings, which remain strong for most companies, but about the long-term outlook. As AI improves productivity, investors fear it could slow growth, increase competition, and put pressure on margins over time.
Against this backdrop, Infosys’ decision to partner with Anthropic can be seen as a strategic move to adapt to disruption rather than fight it. Instead of competing directly with advanced AI model providers, the company is choosing to work alongside them and integrate their technology into its own platforms. This allows Infosys to position itself as a partner that helps businesses adopt AI at scale. The move reflects a broader shift in strategy, from protecting the traditional services model to actively participating in the next phase of enterprise technology transformation.
Why Anthropic Partnership Is Important
The partnership with Anthropic gives Infosys access to frontier artificial intelligence capabilities without having to invest billions of dollars into building its own foundation models. Anthropic’s Claude models are designed for complex enterprise use cases, particularly in regulated industries where reliability, safety, and governance are critical.
By integrating these models into its existing platforms, Infosys can focus on what it historically does best, combining technology with deep industry expertise while leveraging cutting-edge AI to deliver more sophisticated solutions. This helps the company remain competitive with global consulting firms that are also building strong AI ecosystems.
More importantly, the collaboration accelerates Infosys’ broader shift from a traditional services model toward solution-led and outcome-based offerings. The IT services industry has long relied on scaling large teams and billing for effort, but AI is fundamentally changing that equation by enabling automation and productivity gains.
By working with Anthropic, Infosys can build agentic AI solutions that automate complex workflows, modernize legacy systems, and redesign business processes, positioning itself as a transformation partner rather than just a technology implementer. This transition is critical as clients increasingly demand measurable outcomes rather than manpower-driven delivery.
The partnership also strengthens Infosys’ ability to compete for a share of the rapidly expanding AI services market, which is expected to grow significantly over the next decade. As enterprises adopt AI at scale, they require partners who can combine advanced technology with integration capabilities and domain knowledge.
By embedding Anthropic’s models within its broader AI ecosystem, Infosys is building a flexible platform strategy that allows it to adapt as technologies evolve while maintaining strategic relevance with clients. Ultimately, the collaboration is less about adopting a single technology and more about positioning Infosys at the center of enterprise AI transformation.
Why It Could Make Infosys The Strongest Player On Dalal Street
India’s big IT companies are not ignoring AI anymore, they are actively building around it, but in different ways. TCS is using its biggest strengths: scale, delivery depth, and financial durability. It is pushing a “full-stack” pitch that runs from infrastructure to AI-led solutions, and it has announced a strategic investment in a 1 GW AI data centre in India to support “sovereign AI,” a theme becoming important as enterprises and governments worry about data control.
Some analysts even point to an annualised AI revenue run-rate of about USD 1.8 billion, and argue TCS can absorb pricing pressure better than peers because it can industrialise delivery at scale. At the same time, the market also notes that much of TCS’ AI is “embedded” inside projects rather than sold as a clearly separated product line, which means the benefit may show up more in win rates and efficiency than in clean AI revenue reporting.
HCLTech is taking a different route by focusing on engineering-heavy and infrastructure-intensive AI work, where AI meets networks, cloud systems, and industrial environments. Its pitch is that enterprises don’t just need models, they need secure, resilient systems and integrations across messy real-world.
HCL has been pushing its AI Force platform to automate parts of software development such as coding, testing, and documentation, and it has spoken about productivity improvements for clients using such tools. It has also been expanding capabilities in certain verticals, including telecom, where integration and execution complexity are high.
Wipro, on the other hand, is still viewed more as a turnaround story even though it is spending aggressively. It has committed USD 1 billion over three years toward AI, data and analytics, trained a large part of its workforce on AI skills, and positioned initiatives such as ai360, Lab45, and Wipro Ventures investments in AI startups as its growth engines. But analysts still see its AI monetisation as less visible and its growth as lagging peers so far.
This is the key debate investors are tracking: AI will definitely be used, but the real question is who captures the economics. If AI reduces effort, clients will ask for lower prices, which can hit revenue even if project volumes rise. That is why vendors are trying to move up the value chain into outcomes, platforms, managed AI operations, while also using AI internally to protect margins. In that environment, what matters most is whether AI is actually helping companies win larger deals, expand client spending, and defend profitability.
Infosys’ partnership with Anthropic fits into this competitive picture in a very specific way. While TCS is building a full-stack infrastructure-to-solutions story and HCLTech is leaning into engineering-heavy deployments, Infosys is trying to strengthen the “brain” layer of its AI strategy by working with a leading model provider known for enterprise-grade reliability and safety.
The combination of Infosys’ client access and execution scale with Anthropic’s Claude models could help Infosys push deeper into agentic AI, where systems do multi-step work across long workflows rather than just assisting humans with small tasks. If that translates into repeatable industry solutions and larger transformation deals, it can create differentiation that is easier to defend than generic AI productivity claims. But to truly become the strongest player on Dalal Street, Infosys still has to prove it can convert this into measurable outcomes: more large deal wins, clearer monetisation, and margin resilience even as AI pushes pricing lower.
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