Many Indian enterprises rushed to the cloud, promising agility, scale, and lower costs – yet find rising bills, stalled migrations, and unclear returns. The problem is not the cloud itself but mismatched expectations, lift-and-shift migrations that never modernised, fragmented vendor ecosystems, and hidden costs. Boards now demand measurable ROI with clear metrics. Recovering value requires early FinOps, outcome-led design, selective modernisation, disciplined governance, and investment in cloud talent and platform engineering to turn cloud spend from a drain into predictable business value.
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The Data that Should Worry Leaders
The global and India’s research reflect a clear picture. The cloud analyses (2023-24) from McKinsey estimate that approximately $3 trillion of business value is at stake when companies use the cloud effectively, although many are unable to realise this benefit because migration is only the beginning, not the end.
Reports on the Indian public cloud market indicate it is expected to grow significantly in the near future, with projections reaching $30 billion by the end of the 2029s. However, according to the IDC global report in late 2024, 60% of cloud buyers reported that their IT infrastructure needed substantial changes, and 82% had to modernise their cloud systems. Gartner warns that by around 2028, approximately 25% of organisations will be dissatisfied with their cloud programmes due to unrealistic expectations and uncontrolled expenses. These figures are not arbitrary; they are the reason why boardrooms are now laser-focused on cloud ROI.
Common Failure Modes that Kill ROI
Cloud computing in large businesses is often equated with cost reduction, but the reality is more complex. Many projects adopt a lift-and-shift strategy, migrating legacy virtual machines (VMs) to the public cloud without refactoring. This can lead to inefficiencies in compute, oversizing, data egress costs, and unmanaged SaaS sprawl, all of which increase costs. Shadow IT and uncontrolled AI pilots also introduce unexpected storage expenses and GPU costs. A 2025 global survey by Crayon, conducted by Sapio Research, found that 94% of IT decision-makers failed to control cloud expenses.
Another challenge is talent: there are few organisational skills to develop cloud-native architecture, implement FinOps, and automate cost controls. Finally, a disconnect often exists between cloud initiatives and measurable business benefits, such as revenue growth, faster time-to-market, or improved unit economics, suggesting that increased IT spending does not always translate into tangible advantages for business leaders.
Examples that Highlight the Problem
The trends are similar across industries. Migrating core workloads without re-architecture has led to higher operational costs, stateful transactions and heavy I/O strain systems, while telecoms with regional latency requirements experienced poorer performance in user-facing applications because edge strategies were not considered during migration.
Manufacturing companies found their operational technology integrations to be more expensive and slower than anticipated. Success stories often conceal trade-offs: a retailer may boast about rapid feature releases yet still face squeezed margins due to the costs of cloud data processing during peak periods. These trend patterns show that the issue is not purely technical but primarily business and organisational.
Fixes that Work: Governance, FinOps and Outcome-led Design
The actions that ultimately lead to the recovery of ROI are familiar but challenging. First, establish FinOps: cross-functional teams of finance, engineering, and product that allocate costs, set budget commitments, and optimise budget use. Second, adopt an outcome-focused approach: define target KPIs such as revenue per feature, latency improvements, and cost per transaction, and choose a migration path accordingly. Third, implement selective modernisation: refactor high-workload systems such as data platforms and customer-facing services and use hybrid or on-premises solutions for latency-sensitive or regulated systems.
In 2023, McKinsey published an analysis arguing that generative AI and cloud-native services can deliver substantial value, but only when paired with disciplined cloud economics. Vendors and consultancies are responding: Deloitte’s 2025 Near Zero Cost Migration programmes aim to ease migration friction and accelerate surface ROI by integrating SAP, AWS, and migration tooling within a funding scheme.
People, Process and Culture of Continuous Optimisation
The technical tooling is an aid, but the culture drives the process. Operating cadences: Large organisations often lack the disciplined rhythm, sprint cadence, cost-review dashboards, and cloud-spend accountability required for cloud economics. It is crucial to train and retain cloud architects, integrate platform engineering to offer reusable services, and motivate product teams to manage unit economics.
Both Gartner and IDC emphasise how automation (auto-scaling, rightsizing) and platform teams can deliver sustained improvements; organisations that institutionalise these practices turn cloud expenditure into predictable, business-aligned costs.
Why Scale Still Beats Stagnation
The cloud has been the most powerful tool for agility, global scale, and AI-driven innovation. However, with large businesses in India, the difference between a cost centre and a value-adding operation powered by the cloud is often seen as rigid.
This often turns migration into a strategic project with clear goals, emphasising early FinOps adoption and governance. It also involves investing in internal talent and platform engineering, and using hybrid setups when they are cost-effective. Those who succeed in achieving lasting benefits will turn existing disappointments into long-term gains; those who do not will fall short.
