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DeepSeek AI and Indian IT: Our view on the impact

Pivot from brute capex to cost-efficient AI platforms could benefit Indian IT

* DeepSeek, a Chinese AI startup, has developed the R1 model, which rivals leading AI reasoning models such as OpenAI's O1. Using a Mixture-of-Experts (MoE) architecture, R1 activates only 37 billion of its 671 billion parameters during processing, significantly reducing computational costs and energy consumption while maintaining top-tier performance. Remarkably, DeepSeek achieved this with a development cost of around USD6m (although this is being debated), defying industry norms, which take about 10x the price to achieve similar results. Further, by making R1 fully open-source, DeepSeek has not only increased access to cutting-edge AI but also intensified global competition, pushing U.S. companies to rethink their strategies and investments. While most stock prices for most chip makers have reacted negatively as this implies much lower compute than earlier anticipated, we believe this could shift focus from capex to cost efficient AI platforms, possibly benefitting Indian IT.

GenAI and Cloud: How does Indian IT make the most of this?

* Services spending generally seems to follow the big-tech capex cycle (just like during the cloud adoption phase), and we could see something similar with AI. Back then, IaaS was merely a starting point, with hyperscalers differentiating themselves through PaaS and SaaS offerings.

* Similarly, LLM may lose its edge as the primary moat. Just as PaaS and SaaS, built around basic compute infrastructure, became the true kingmakers, interfaces built around LLMs are likely to become kingmakers.

* Indian IT can play a significant role in this evolution by driving platform engineering and outsourced engineering capabilities, enabling enterprises to design, build, and scale these interfaces effectively. This could position Indian IT as a key player in the low-cost GenAI wave.

Services, not LLM, to be the kingmaker

* We have argued in our thematic report (Technology: Bounce-back! Charting the path to revival for IT services – page 16) that spending in high-tech may resume in earnest once major hyperscalers shift their focus from capex investments to building platforms and interfaces (exhibits 4 & 5). DeepSeek may accelerate this trend, as it is becoming increasingly clear that LLM superiority is short-lived— whether it is ChatGPT, Gemini, or DeepSeek, the quality of output is converging.

* As a result, attention and spending are likely to pivot toward the services and platforms built around these LLMs rather than the models themselves. This shift presents a significant opportunity for Indian IT to drive platform engineering, integration, and outsourced AI services, positioning it as a key enabler in the evolving AI ecosystem

Auto ER&D: Lessons from the Chinese (and Tesla's) invasion of EVs

* Indian IT and outsourced engineering often take a backseat during capex cycles but become integral to the value chain once the focus shifts from innovation to cost optimization.

* A clear example of this was the capex and R&D squeeze faced by auto OEMs during 2020-2023 (exhibit 3). As EVs and SDVs became the industry's focal point, led by Tesla and Chinese players like BYD, European automakers faced intense pressure to innovate despite constrained R&D budgets. This necessity to drive technological advancements while managing costs led to a surge in outsourced ER&D, positioning Indian IT as a key enabler in the evolving automotive landscape.

* A similar dynamic is unfolding in AI, where DeepSeek’s innovation has demonstrated that cutting-edge AI can be developed at a fraction of the cost. As the AI ecosystem prioritizes efficiency over brute-force compute, enterprises will need to optimize spending on platforms, software, and infrastructure. This shift is likely to drive a wave of outsourced services spending, with Indian IT playing a central role in enabling cost-efficient AI development and deployment.

What does this development mean for data centers?

* As AI applications move closer to end-users through smartphones, IoT devices, and edge data centers, we expect this to drive even greater demand for data centers. With India generating 28% of the global data but holding only a 1% share of global data centers, the need for more localized infrastructure is clear.

* The shift toward distributed and edge computing will require more localized infrastructure to support the increasing volume of data. Thus, we do not foresee any major risks to the overall growth of data center expansion due to DeepSeek's advancements.

* Colocation data centers, in particular, should feel less of an impact than hyperscale data centers. The nature of colocation services, where providers lease racks and manage their own hardware, means that these facilities can remain more flexible and adaptable to changing demands, such as AI-driven data workloads, without needing massive shifts in infrastructure.

* In the long term, we believe DeepSeek’s developments will be a net positive for the industry as demand for new hardware and additional space is expected to increase.

View on stocks

* We believe it is too early to ascertain the impact on individual stocks, as GenAI currently remains a small proportion of the overall deal TCV. We will keep monitoring this story further.

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