Until now, artificial intelligence (AI) tools have largely been viewed as software that assists employees. However, an announcement by US-based AI company Anthropic that its latest AI capabilities can independently handle complex office tasks with minimal human intervention has created a stir in the global technology sector. Following these developments, IT stocks have seen pressure both internationally and in India. Market participants note that this is among the sharpest periods of uncertainty for IT shares since the COVID-19 disruptions of March 2020.
It is no longer just investors who are worried. A larger question is now being asked across industries: will companies really need human resources in the same numbers in the future?
How this differs from ChatGPT and others
American AI startup Anthropic expanded its Claude platform and launched Claude Cowork in late January with new agent-style features designed to execute multi-step tasks autonomously. The company introduced a range of tool integrations that allow Claude Cowork to plan, decide, and act across workflows, rather than merely respond to prompts.
Existing AI tools such as ChatGPT, Gemini, and Grok function primarily as responsive systems. They generate answers, write content, or assist with coding, but they rely heavily on user instructions and continuous guidance. Anthropic’s approach is different. Claude Cowork is positioned as an AI that behaves more like an experienced office worker, capable of understanding objectives and completing tasks end to end.
In practical terms, this makes Claude Cowork closer to a digital assistant that executes work, rather than a tool that only provides suggestions.
How it works
Anthropic has demonstrated Claude Cowork’s ability to interact with computer systems by opening folders, reading documents, locating relevant files, making edits, and organizing information systematically. With the help of its newly introduced tools, Claude Cowork can shift roles and assist in areas such as legal review, marketing and finance analysis, data interpretation, and research support.
Users do not need to explain every step. For example, a command such as reviewing multiple contracts and identifying those nearing expiry can be executed without continuous human supervision.
Why this is a challenge for Indian IT companies
A significant portion of Indian IT companies’ revenue comes from clients in the US and Europe. These firms primarily offer software development, testing, and maintenance services, employing large teams of engineers to deliver projects.
There is growing concern that advanced AI systems from companies like Anthropic could reduce the volume of outsourced work. Indian IT companies largely operate on a labor-based billing model, where clients are charged based on the number of engineers and billable hours involved.
As AI accelerates coding, testing, and documentation, fewer engineers may be required for the same workload. If productivity rises sharply, client spending could decline, putting pressure on revenues and margins. This shift could also impact employment, especially as global tech companies increasingly adopt AI-driven cost optimization strategies.
What lies ahead
Industry experts believe future demand will shift toward consulting, platform-based solutions, and high-value problem-solving roles rather than routine coding and testing. Stock markets tend to price in future risks, and the recent sell-off in IT stocks reflects uncertainty over how quickly companies can adapt.
Analysts caution that technological change will only accelerate, forcing IT firms to rethink business models, pricing structures, and workforce strategies.
Will jobs be lost?
Anthropic’s newly introduced tools are designed to handle tasks that were previously performed by professionals or specialized software. These include:
- Legal assistance tools: Used for contract review, including NDAs, risk identification, and compliance checks. Following these developments, shares of some legal technology firms reportedly came under pressure, reflecting investor concerns about long-term disruption.
- Finance tools: Assist with accounting entries, audit preparation, and financial reporting.
- Data analysis tools: Generate SQL queries, extract data from databases, and convert it into visual dashboards.
- Biological research support: Helps researchers in early-stage analysis and data organization.
These capabilities suggest that AI could reduce reliance on expensive software, outsourcing teams, and even certain specialist roles, especially for routine and repetitive tasks.
