Analysis
IBM lowered its full-year earnings forecast following a disappointing Q2 2026 report on July 22, and management used the earnings call to directly push back on a narrative that's been building across enterprise software all year: that generative AI is actively killing demand for traditional enterprise software deals. IBM's framing instead is that AI is lengthening sales cycles -- as enterprise buyers pause to evaluate AI-native alternatives before committing -- rather than eliminating the underlying demand.
The company made a parallel, more specific defense of its mainframe business, insisting that even as enterprises spend time evaluating AI-native tooling, legacy infrastructure commitments remain sticky because migrating off a mainframe carries real operational risk that AI hype alone doesn't erase. That argument is self-serving given IBM's mainframe revenue dependency, but it's also a genuinely testable claim: if true, delayed deals should show up as a bookings recovery in coming quarters rather than permanently lost revenue.
The defensive framing isn't unique to IBM this week -- ServiceNow's CEO Bill McDermott made a similar case for his own company's continued relevance, touting a 'kill switch' feature for rogue AI agents as evidence ServiceNow remains essential infrastructure even as AI-native competitors emerge. Two major enterprise incumbents making structurally similar 'we're still necessary, just misunderstood' arguments in the same earnings week suggests genuine, shared anxiety across legacy enterprise software about AI-native disruption, not just one company's isolated messaging challenge.
The stakes of IBM's argument being right or wrong are significant for the sector: if 'delayed, not lost' is accurate, enterprise software should see a bookings recovery once AI-tooling evaluation cycles complete, and current weak results are a temporary air pocket rather than a structural decline. If IBM is wrong, and some meaningful share of those delayed deals are being displaced by AI-native alternatives rather than merely paused, it's an early warning sign for legacy enterprise software's multi-year growth assumptions across the sector, not just IBM specifically.
For enterprise software investors and founders, IBM's own admission that AI evaluation cycles are measurably lengthening enterprise sales -- regardless of whether deals are ultimately lost or merely delayed -- is itself useful data: it confirms that AI-native competitive pressure is now a real, quantifiable factor in enterprise buying behavior industry-wide, not just a talking point. Founders selling AI-native alternatives to legacy enterprise software should expect longer, more contested sales cycles as a result, even against incumbents whose products haven't fundamentally changed.
