IBM reported a surprising software shortfall in its fiscal 2026 second quarter, with CEO Arvind Krishna attributing the miss to a sudden shift in customer spending toward AI hardware and cybersecurity software. During the earnings call, Krishna acknowledged that “execution” was the core problem: “With the portfolio we have and the opportunities ahead, it comes down to execution. That is where we fell short in the second quarter.” CFO James Kavanaugh explained that clients pivoted to servers, storage, and memory purchases in late June to secure supply-constrained infrastructure ahead of expected price increases, causing a double-digit number of large deals to slip past their expected close dates.
Why It Matters: AI Spending Is Disrupting Traditional IT Budgets
IBM’s miss is not just a one-quarter hiccup—it signals that AI infrastructure is becoming a “black hole” for enterprise IT budgets. Clients are delaying traditional software license agreements to prioritize capex on AI-related hardware. Kavanaugh noted that many clients purchase mainframes and associated software through enterprise license agreements, which are treated as capital investments. As those clients shifted capex toward AI hardware, deal timing moved. This structural shift threatens legacy enterprise software vendors like IBM, Oracle, and SAP. However, Krishna offered a hopeful sign: about one-third of the delayed deals have already closed within three weeks, suggesting the shortfall was a deferral, not permanent demand destruction.
XPLAIN AI’s Analysis: Execution Gap and Rebound Potential
We interpret IBM’s struggle as a failure of sales execution rather than product weakness. Krishna himself admitted the issue was execution, not portfolio quality. IBM has invested heavily in AI-ready software through acquisitions like Red Hat, HashiCorp, and Confluent, but its sales organization failed to adapt quickly enough to shifting client priorities. Positively, IBM plans to use AI internally to scale software development, optimize supply chains, and boost sales and marketing. The goal to expand coverage to thousands of additional clients beyond the Fortune 1000 shows IBM is trying to turn AI demand into growth. Still, the near-term risk is that if AI hardware investment persists, IBM’s traditional software revenue could face prolonged pressure.
- AI Infrastructure Suppliers (Beneficiaries): Companies providing servers, storage, and memory for AI data centers stand to gain as enterprises redirect capex toward hardware. Memory and high-performance storage vendors are likely short-term winners.
- Legacy Enterprise Software Vendors (Risk): IBM’s experience suggests Oracle, SAP, and similar firms may face similar spending shifts. Clients prioritizing AI infrastructure could delay or reduce license-based software contracts.
- IBM (Mixed): Near-term earnings pressure is a headwind, but if delayed deals close and AI investments pay off, a medium-term rebound is possible. However, IBM’s weak position in AI hardware limits upside.
Counter Scenario and Uncertainties
Krishna’s expectation that two-thirds to three-fourths of delayed deals will close within six months is optimistic. If AI investment proves longer-lasting or if IBM’s software portfolio is perceived as less relevant for AI workloads, deferrals could become permanent losses. Additionally, IBM’s internal AI innovation pace may lag behind competitors like Amazon Web Services and Microsoft, raising long-term competitive concerns. The fact that only one-third of deals closed in three weeks, while encouraging, is not yet full evidence of a rebound.
Key Metrics to Watch Next Quarter
Investors should monitor two things in IBM’s next earnings: first, whether the closure rate of delayed large deals exceeds 50%; second, whether AI-related software and services revenue becomes a visible growth driver. IBM’s strategy to offer “cost-effective and scalable” AI solutions must translate into concrete contracts to validate the turnaround narrative.
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Sources
- IBM CEO admits to ‘execution’ short fall, but touts some rebound — SDxCentral · News coverage · Thu, 23 Jul 2026 19:02:22 +0000
Written by: XPLAIN AI Editorial Team · Reviewed by: XPLAIN AI Editorial Desk
This content was drafted with AI assistance based on publicly available sources and reviewed under XPLAIN AI's editorial standards.