Technology Consulting

Organisations with strong automation foundations adapt faster to change. Autonomous agents act across multiple enterprise systems simultaneously - a single bad decision can cascade across finance, procurement, HR, and customer data in seconds; the blast radius is far larger than a traditional software bug.

Clients who invested in test automation as a programme asset - not just a project expense - consistently recover faster from change: upgrades, regulatory shifts, and new AI feature rollouts all move faster.

As AI becomes embedded in everyday work, the real differentiator will be the ability to combine strong leadership accountability with clear visibility into AI costs and outcomes. Organisations that treat AI as a business transformation agenda - not just a technology initiative - will be best positioned to unlock sustainable value and measurable returns.

India currently has over 150 data centres with about 1.5 GW operational capacity as of early 2026, including emerging AI-focussed facilities driven by GPU deployments. The capacity to surpass 1.8 GW by the end of 2026 and reach over 8 GW by 2030 is fuelled by a shift toward AI-ready infrastructure encompassing hyperscale, specialised hardware like GPUs, software platforms, and edge computing.

Standard data centres currently yield Ebitda margins of 20-30%, while AI-optimised centres, with premium pricing for high-performance compute, are expected to achieve margins in excess of 50% due to elevated demand and utilisation.

Industrial manufacturing organisations are increasingly wanting to leverage technology as a force multiplier aligned with business strategy to unlock significant value. In India, government incentives on digital infrastructure, coupled with rising adoption of AI, are creating a strong foundation for transformation.

Organisations that invest in robust data foundations, scalable platforms, and workforce upskilling, while strengthening cybersecurity and ecosystem partnerships, will be best positioned to drive sustainable growth and resilience in a rapidly evolving global landscape.

The narrative that infrastructure constraints will hold India back is fundamentally outdated. Through a unique blend of state-enabled public digital rails and aggressive private innovation, India is crafting a third pathway in global AI.

We are optimising at every single layer of the sovereign stack - scaling targeted compute pools, engineering domain-specific models tailored to localised institutional complexity, and leveraging our legacy in semiconductor talent to dominate chip design and hardware packaging. We aren't just navigating around constraints; we are productising our solutions, turning localised public service breakthroughs in healthcare, finance, and agriculture into scalable digital and physical exports for the rest of the world.

AI has moved to the core of enterprise strategy, driving transformation beyond efficiency. With India’s Digital Public Infrastructure scaling and AI talent expanding rapidly, the focus now is execution.
Being AI first is not about experimentation. It is about aligning AI with core business priorities and embedding it across the value chain. As Agentic AI reshapes roles and workflows, enterprises must act with intent.

Three priorities stand out:

• Scale from pilots to enterprise wide deployment
• Treat trust as a strategic differentiator
• Build a truly AI native workforce and culture

The shift is clear. The question is no longer whether to adopt AI, but how fast and how well it can be scaled for impact.