Why ‘lift and shift’ used to work — and why it doesn’t anymore

A few years ago, “lift and shift” was the golden ticket to the cloud. It seemed simple: Pick up your workloads, move them from your on-premises data center into the cloud, and you’re done.

For a while, it even worked. Organizations were under pressure to cut costs and scale fast while striving to appear innovative, and lift and shift delivered quick wins — faster migrations, little need for rework, and that satisfying moment when the CIO could declare, “We’re in the cloud.”

But what used to be “good enough” is now holding organizations back.

How a quick fix becomes a long-term problem

Take a mid-sized insurer as an example. They decide to lift and shift their systems wholesale into the cloud. Thousands of workloads are moved overnight, with no rearchitecting or refactoring — just a quick change of address.

In the short term, it seems like progress. But within months, the cracks start to show:

• Costs are ballooning. What used to be fixed server costs have become unpredictable monthly bills. Without optimization or right-sizing, 24x7 workloads keep the meter running around the clock.
• Performance is lagging. Legacy applications are still monolithic and hard to scale. They haven’t magically become agile just because of the change in environment.
• Teams are struggling. Managing cloud operations requires new skills, different tools and new ways of thinking to avoid outages, misconfigurations and security gaps.
• Innovation is stalling. By simply moving workloads “as is,” the insurer has missed out on everything that makes the cloud transformative, including AI and automation.

Lift and shift might move your business forward temporarily, but it won’t modernize it — a crucial distinction explored in a new NTT DATA perspective, Cloud transformation in the age of AI: The evolution of lift and shift.

The world changed, and so did cloud expectations

When lift and shift first became popular, the cloud was mostly about efficiency. The goal was to save money and free up space. But today, it’s about capability — using cloud-native services, AI and automation to unlock new business models and faster innovation.

At the same time, the landscape has shifted dramatically. For instance, Broadcom’s 2023 acquisition of VMware changed licensing structures for many enterprises, making the cost of “standing still” painfully high. Organizations now face a clear choice: Adopt more of the bundled software to access greater value, modernize their infrastructure or pursue both paths in tandem.

Furthermore, data centers are in many cases seen as expensive real estate rather than assets. And with AI becoming integral to competitiveness, organizations can’t afford to be weighed down by outdated infrastructure.

The message is clear: The cloud is the new launchpad for transformation.

• ALSO READ → The next phase of cloud: Reimagining innovation with AI

From migration to transformation

So, what does this mean in practice?

Many organizations are working with expert service providers who can guide them on their journey to the cloud with best practices and tools like cloud transformation factories, where the focus isn’t just on moving workloads faster but also on modernizing them along the way.

A cloud transformation factory blends automation, AI and deep expertise across every stage to help you decide what to keep, what to upgrade and what to rebuild.

At NTT DATA, we partner with Amazon Web Services (AWS) to use tools such as AWS Application Discovery Service, Amazon Macie and AWS Compute Optimizer to make the process smarter and more efficient.

Our AI-driven mapping and dependency analysis reveal exactly where value lies. FinOps guardrails ensure your CFO has clear visibility of the before-and-after economics, and modernization tools like AWS Transform refactor your legacy code for the cloud era.

This helps you avoid pitfalls like cost overruns, a lack of skills, misconfigured cloud services, poor tracking and usage monitoring, and inadequate optimization or “right-sizing” of workloads.

Why this matters now

Cloud transformation is a business strategy. If you stop at migration, you risk paying more for systems that deliver less. But if you modernize, you gain speed, scalability and a foundation for innovation.

Don’t get left behind — the future belongs to those who transform smartly.

• ALSO READ → Rearchitecting for the future: Why private and sovereign clouds lead in the AI era