Anthropic’s services move is a signal that AI labs are beginning to industrialise the very layer IT services firms were counting on to defend.
Anthropic has formally announced a new enterprise AI services company and said its applied AI engineers will work alongside the new firm’s engineers to identify high-impact use cases, build custom solutions, and support customers over time. Reuters has also reported that both Anthropic and OpenAI-linked ventures are exploring acquisitions of AI services firms to deepen deployment capability.
Indian IT services firms have been assuming that while AI labs would build the models, the real enterprise value would still sit in implementation, integration, customisation, and deployment.
That assumption now looks far less safe.
The timing could not be worse for the incumbents. Indian IT enters this moment with muted growth, rising investor anxiety, and limited AI monetisation at scale. TCS has already posted its first annual revenue decline since listing. Other majors have flagged subdued spending and delayed ramp-ups.
AI-related revenue still accounts for less than 5% of total income for some of these firms.
Just as AI labs are moving up the stack toward implementation and outcomes, the IT industry is still trying to find its footing in the AI era.
Much of the industry response still feels tactical rather than
transformational. The industry has spent too much time talking about coding productivity,
certifications, and AI usage metrics — and too little time reinventing operating models, delivery
economics, and the roles clients will actually value in an AI-first world.
‘50,000 people certified on a tool’ is not a drumroll statement.
Awareness does not automatically translate into capability, and capability does not automatically translate into client value.
It is not over. But it will require honesty before action.
Indian IT still has real advantages — client trust, tool neutrality, enterprise depth, and scale talent pools that most AI labs do not.
But advantages do not convert themselves.
If the industry is serious about AI transformation, it must:
- Not underestimate change management and mindset shift
- Stop obsessing over usage metrics and mistaking certifications for capability
- Solve for confused clients by simplifying, not adding jargon
- Build for serious talent shifts — not default to layoffs
Rethink the moat. Revise the operating model. Redefine capability. Reignite client relationships.
That is where the next chapter will be written.
Let’s build it with intent.