Stamford, Conn., June 18: More than 70% of mainframe exit projects initiated in 2026 will fail to produce the intended benefits due to an overestimation of generative AI (GenAI) tooling capabilities, according to Gartner, Inc., a business and technology insights company.
“There is a widening gap between the marketing promise of GenAI and its real-world ability to transform and migrate complex legacy code,” said Alessandro Galimberti, VP Analyst at Gartner. “At the same time, intense investor pressure is pushing vendors to embed AI into their offerings regardless of whether it meaningfully improves outcomes. When this is combined with the ‘too-big-to-fail’ nature of mission-critical mainframe applications and the accelerating loss of experienced talent, infrastructure and operations leaders face a perfect storm of risk that makes poorly planned exit strategies increasingly untenable.”
Mainframe Exit Risks Demand More Pragmatic Strategies
Poor mainframe migration decisions are not just defined by cost overruns; they can also pose a direct threat to business and operational continuity.
Organizations that pursue “seemingly magical” AI-driven exit strategies, rather than taking a platform-smart approach to align workloads with the right environments, risk introducing significant technical debt and exposing the enterprise to critical failures.
As a result, the mainframe exit market is at a pivotal point. Sustained investments from IBM, along with independent software vendors such as 21CS, BMC, Broadcom, and Rocket Software, and managed service providers like DXC, GTSG, and Kyndryl, further reinforce the mainframe’s position as a modern platform for strategic investment. Gartner predicts that by 2030, 75% of vendors operating in the mainframe exit market will pivot their business models or cease operations, as market expectations reset and demand for one-size-fits-all migration solutions declines.
“The right mainframe strategy depends heavily on the profile and complexity of an organization’s environment,” said Galimberti. “For many mainframe customers, GenAI can be more effectively used to enable modernization in place rather than accelerate migration off the platform.
“For medium environments, which constitute the largest market segment, they face the most complex decisions. Organizations must balance strategies focused on optimizing existing mainframe investments, while limiting full platform exits to select, case-by-case scenarios, as these efforts require high-risk transformation and often result in suboptimal outcomes. Small mainframe environments can instead tackle mainframe-as-a-service (MFaaS) as a cost-effective hosting strategy and focus on replacing legacy third-party software (ISV solutions) and targeted in-platform modernization where a positive ROI is achievable.”
Additional Insights Available
Gartner clients can read more in Too Big to Fail: Why Mainframe Exit Projects Are Likely to Fail in the Age of Generative AI.
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