The tech sector has been in the eye of the storm lately, and Anthropic has been at the centre of it all. There were concerns about AI disrupting jobs after the US AI major launched its enterprise AI tools. Recently Anthropic released a report examining how AI is being used and what it may mean for the labour market. Motilal Oswal analysed the Anthropic report and questioned the gap between theoretical adoption and actual usage
Motilal Oswal said, “The large gap between AI’s theoretical capability and its observed usage is partly due to enterprise implementation constraints.” According to the leading domestic brokerage house, “greenfield deployment enables faster AI adoption than brownfield set-ups.”
AI adoption led by digital-native firms
Motilal Oswal stated that AI adoption is currently concentrated among new-age technology companies.
Their analysis of API calls for Claude and token usage for OpenAI shows that software engineering “is ground zero for AI invasion – 50% of all API calls target software engineering.”This makes it the biggest use case for AI tools.
Are legacy players slowing the adoption rate?
Additionally, Motilal pointed out that “AI is currently being used only by cloud-first/AI-native enterprises. Of the top 20 token users for OpenAI, 90% are new-age companies.”
They believe that this substantiates their point that “AI deployment today is easier in greenfield environments. Large enterprises operate differently. Most of them run on systems built over 20-30 years, with applications that are layered, integrated, and customised.”
According to them, “In such brownfield environments, deploying AI at scale requires integration with legacy stacks, data cleanup, and governance alignment.”
As a result, deploying AI at scale in such environments requires complex integration with existing systems, data clean-up and governance alignment.
IT maintenance spending limits AI expansion
The report also highlighted that around 60–80% of enterprise IT budgets still go toward maintaining existing systems.
This means organisations often need to modernise their technology infrastructure before they can unlock large-scale productivity gains from AI. Without addressing legacy complexity, scaling AI beyond pilot projects remains difficult, the report suggests.
Conclusion
Motilal Oswal in its report suggests that while AI capabilities are advancing rapidly, its real impact on the labour market will likely unfold gradually rather than through sudden disruption. Enterprise adoption depends not just on what AI can do, but on how easily organisations can integrate it into their existing systems and workflows.