How enterprise cloud is transforming in India with AI-native innovation?

India’s cloud computing market is in a dynamic phase of reinvention. What began as a race to migrate workloads has matured into a mission to build business-centric, AI-native ecosystems. Enterprises are no longer content with lift-and-shift approaches; they seek measurable outcomes, integrated governance, and innovation at scale.

The enterprise cloud landscape is also being transformed by Global Capability Centres (GCCs), which are evolving from back-office units to digital innovation hubs. With the rise of Generative AI, FinOps, and edge computing, India is emerging as both a consumer and creator of cutting-edge cloud technologies.

In this context, DQ Channels spoke with Amit Maheshwari, Head of Cloud Practice at EPAM Systems India, who shared how EPAM differentiates its offering through AI-driven frameworks, platform engineering, and outcome-led managed services, helping enterprises reimagine what cloud can do.

EPAM’s differentiation: beyond lift-and-shift in enterprise cloud

“EPAM’s value proposition surpasses traditional cloud migration. We focus on enabling true business-centric, cloud-native innovation,” Maheshwari explained.

EPAM’s cloud strategy and advisory service is designed to help clients build a Cloud Centre of Excellence (CCoE) that ensures strong governance, accelerated adoption, and continuous innovation. Complementing this are AI-driven frameworks that automate discovery, assessment, migration and optimisation.

“Our AI-native platform engineering framework provides the capability to build highly optimised cloud infrastructure on Zero Trust Architecture,” he added. “It integrates DevOps pipelines, agentic workflows, and multi-cloud strategies, while our AI-native cloud security framework ensures adherence to Zero Trust principles.”

At the heart of EPAM’s ecosystem lies its proprietary AI 360 Transformation Framework, which blends deep industry expertise with agentic capabilities to deliver tangible business value.

“Our cloud accelerators integrate with the EPAM AI Run Framework, modernising applications into containerised micro-services powered by AI-driven decision making,” said Maheshwari.

The story doesn’t end at deployment. EPAM’s AI-enabled FinOps layer provides a single-pane platform to optimise costs across hybrid and multi-cloud environments, offering a natural-language interface for querying costs and implementing optimisation recommendations directly.

Empowering every user through AI simplicity

One of EPAM’s most distinctive innovations is its focus on AI-driven accessibility.

“By leveraging natural language interfaces, we remove technical barriers,” Maheshwari said. “Any team member, whether a developer, business analyst or project manager, can interact with complex workflows through simple English commands.”

EPAM’s proprietary agentic frameworks drive this, enabling even non-technical users to derive actionable insights, thereby accelerating productivity and adoption across enterprises.

Managed cloud services: from projects to outcomes

The conversation then shifted to managed services, where EPAM is redefining delivery models.

“We are transforming from project-led to outcome-led models, prioritising measurable business impact over resource-based billing,” Maheshwari said.

EPAM’s value-driven approach focuses on automation and productivity. “Our co-managed operations, through the CCoE model, include not just technologists but also experts from security, finance, risk, and compliance, ensuring a holistic governance structure from day one.”

Looking ahead, Maheshwari expects this model to evolve rapidly. “We’re moving toward AI-native operations, from managing cloud infrastructure to orchestrating AI-enabled SDLC, AIOps and autonomous IT operations,” he said.

This includes LLM-driven data management, Zero Trust Network Architecture, and AI-driven observability platforms for proactive monitoring and hyper-care.

“In the next few years, we’ll expand our shared responsibility model, strengthen FinOps for continuous optimisation, and automate governance to enhance security and compliance,” he added.

Governance and skill: tackling AI integration challenges

Integrating AI workloads into cloud environments is not without challenges. Maheshwari pointed to two critical areas, architecture and skills.

“A major hurdle is transitioning from legacy data warehouses to intelligent, real-time data platforms that can feed AI workloads,” he said.

EPAM’s solution lies in its AI Factory approach, which builds composable infrastructure and governance components that help clients move AI products from proof of concept to production.

“We use partnerships with cloud hyperscalers, data-lake providers, and Snowflake to deliver scalable AI infrastructure,” he noted.

On the governance side, EPAM’s AI governance and security framework embeds data privacy, model security and Responsible AI principles from the design stage.

“Our framework enforces compliance monitoring, risk assessment and guardrails against issues like data poisoning or denial-of-service attacks,” Maheshwari explained.

He also highlighted EPAM’s commitment to AI literacy and talent development. “We’re re-skilling engineers and leaders across levels, ensuring familiarity with leading LLM tools like GitHub Copilot, Cursor and Claude.”

Collaborations with hyperscalers, ISVs and GCCs

Maheshwari stressed that collaboration is core to EPAM’s innovation strategy.

“Our partnerships with AWS, Azure and GCP help us deliver vertical-specific AI solutions with low latency and superior user experience,” he said.

EPAM also integrates with leading ISVs such as Salesforce, Oracle and SAP, and partners with emerging AI start-ups to embed their tools into its engineering stack.

Beyond metros, EPAM is working to extend its reach into tier-2 and tier-3 cities by co-creating solutions with GCCs.

“India now hosts over 2000 GCCs; we work with more than 55 of them,” he shared. “The main gap today is the scarcity of deep AI engineering talent. Our global delivery model, spanning 50+ countries, ensures we bring the right skills from anywhere to meet our clients’ transformation needs.”

EPAM’s toolkit of accelerators, he added, helps GCCs scale and innovate faster, reducing design-to-deployment cycles and fostering a culture of rapid experimentation.

Adapting to Indian realities: compliance, cost and the edge

Indian clients, both local firms and GCCs, are increasingly focused on data localisation, compliance, and cost optimisation.

“Flexibility and rapid adaptability are the top asks,” said Maheshwari. “Clients must adhere to national laws on data residency and privacy, while managing costs efficiently.”

EPAM addresses this through low-latency distributed architectures and multi-region hybrid solutions that balance business SLAs with cost considerations.

He also emphasised the rise of edge computing: “For AI and IoT use cases, we’re designing solutions that process data closer to the user, improving speed and efficiency.”

“We’re also investing in sovereign cloud patterns, ensuring mission-critical infrastructure for government and regulated industries remains entirely within India’s jurisdiction,” Maheshwari added.

Future bets: Gen AI and competent edge computing

When asked about future priorities, Maheshwari was clear:

“Generative AI is our single most important strategic investment,” he said. “We’re helping enterprises move beyond experimentation to operationalise Gen AI and take innovations to production.”

EPAM is investing heavily in its Agentic AI Run Platform, developing playbooks for the software development lifecycle and expanding its AI 360 Transformation Framework.

“Our engineers are being trained on the latest models, agent-to-agent communication, and model context protocols,” he said.

The company is also betting on intelligent edge computing for sustainability and cost reduction. “Distilled LLMs, the stripped-down versions, save bandwidth, reduce energy use, and provide more reliable performance,” Maheshwari noted.

Quantum computing remains a “watch space,” with EPAM maintaining exploratory interest.

Conclusion: AI-native cloud as India’s next frontier

EPAM’s approach reflects the maturity of India’s enterprise cloud market, a shift from migration to modernisation, automation, and intelligence. By combining AI-driven frameworks, platform engineering and co-managed operations, EPAM Systems India is helping businesses evolve from cloud adoption to cloud innovation.

“The challenge is not technology, it’s finding the right use case, ensuring security and building the right talent,” Maheshwari concluded. “AI and cloud are converging to create a new foundation for digital enterprises, and India is at the centre of that change.”

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