Cloud Giants Hit Slow Lane as Legacy Systems Stall Upgrades – Crypto News

For years, digital transformation took the lion’s share of investment, as companies wanted to move fast and capture new efficiencies to compete with even faster-moving, more operationally streamlined firms.

Today, however, enterprise digital transformation at the highest level is no longer just about buying modern tools and leaning into cloud migrations. For some of the world’s biggest and most sprawling businesses, it can be about timing, culture and a hands-on approach to unraveling the complexities of long-standing legacy back offices.

When cloud-native companies like Snowflake and Databricks first rocketed to prominence, their success was buoyed by the growth of digital-first businesses. These organizations, often startups or cloud-native unicorns, needed scalable, agile infrastructure to fuel growth. Cloud data warehouses and platforms were the answer, offering a way to store, manage and analyze data without the burdens of traditional IT infrastructure.

However, as these cloud providers set their sights on the next phase of growth by targeting large, multinational enterprises with legacy systems, a different picture is emerging, one centered around capital budgets for mainframe modernization, enterprise resource planning (ERP) upgrade timelines and multiyear IT strategic plans.

Financial filings and statements from leading cloud providers about their deal pipelines show that digital transformation in the enterprise space is not a sprint. It’s a marathon, often run on a track laid decades ago.

See also: From PDFs to APIs: Enterprise Modernization Ditches Clunky Human Hand-Offs

The Slow-Motion Stampede of Enterprise Upgrade Cycles

At a May conference, Snowflake Vice President of Finance Jimmy Sexton said when it comes to the type of major transformation deals that Snowflake made its business on, the cloud provider is now at the mercy of corporate renewal cycles and legacy infrastructure, The Register reported June 2. That means slow, deliberate progress.

Today’s biggest firms don’t rip and replace their back-office architecture on a whim. They wait for on-premises environments and data ecosystems to hit end-of-life or contract renewal. Only then do they consider initiating a phased cloud shift.

The challenge for cloud platforms is less about convincing chief information officers and chief financial officers of the value proposition and more about syncing with an existing cadence that moves in triennial, not quarterly, rhythms.

At the heart of this dynamic is the enterprise upgrade cycle. These cycles, such as planned migrations of ERP systems, data warehouses and core business applications, are the gatekeepers to large-scale cloud adoption.

For example, SAP customers on older versions of ERP Central Component (ECC) are only now beginning to move to S/4HANA, a transformation often tied to broader infrastructure changes. SAP’s financials showed steady S/4HANA growth, but Chief Financial Officer Dominik Asam said in the company’s April earnings report that many customers are still in the planning or piloting phase.

The challenging macro environment may have firms waiting even longer to consider any shift at all. The PYMNTS Intelligence report “What Uncertainty Means: US Goods Firms Retool Product Plans Amid Tariffs” found that 8 in 10 product leaders said tariffs have forced them to redirect their focus to short-term fixes over long-term strategies.

Read also: Real-Time Data, Real-Time Decisions: The CFO’s New Reality

Digital Transformation Is a Tale of Two Speeds

The state of enterprise digital transformation is best described as a tale of two speeds. On one hand, there is the relentless velocity of innovation from cloud providers that push quarterly product updates, beta releases and new service announcements at a dizzying pace. On the other hand, enterprise buyers operate at the speed of committee approvals, security audits, procurement reviews and multiyear budgeting cycles.

“This is an unprecedented time in history,” WEX Chief Digital Officer Karen Stroup told PYMNTS in April. “[AI] technology is evolving every six months. In general, organizations change on five- or six-year cycles. And so, the technology is outpacing us.”

As it relates to AI systems like agentic AI, the PYMNTS Intelligence report “AI at the Crossroads: Agentic Ambitions Meet Operational Realities” revealed the opportunities and challenges that large companies face when using AI to support and optimize their business operations.

Meanwhile, payments advances, such as real-time payments systems, could require cloud-based infrastructure adoption by banks.

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