Breaking 20:29 Trump claims senior Iranian leaders killed as tensions over Strait of Hormuz intensify 19:15 Trump announces renewed maritime blockade against Iran amid Strait of Hormuz tensions 19:00 NASA seeks four volunteers for year-long Mars mission simulation 17:30 States challenge Paramount’s $110 billion Warner Bros. Discovery takeover in major antitrust lawsuit 17:15 Bosch launches sample production at first U.S. semiconductor plant to strengthen domestic chip supply 14:30 Williams secures $5.3 billion investment from Blackstone-led consortium for power projects 13:45 Iraqi Prime Minister Ali al-Zaidi seeks major US energy investment during Washington visit 12:31 Jay-Z concert delayed in New York after ticketless fans disrupt Yankee Stadium event 12:00 Wall Street banks accelerate AI assistant adoption in race for productivity gains 11:47 US Military Reveals First Combat Use of New Unmanned Weapons in Strikes on Iran 11:30 US Ebola patient infected in Congo transferred to specialized hospital in Germany 10:56 Morrisons explores £600 million property deal with US investor Realty Income, Sky News reports 10:41 US dollar gains as Middle East tensions fuel inflation concerns 09:00 UN chief urges US and Iran to end renewed hostilities and resume diplomacy 08:35 U.S. military says Strait of Hormuz remains open despite rising tensions with Iran 08:30 France’s World Cup journey links Boston and Dallas, two cities tied to John F. Kennedy’s legacy 08:18 Support grows in U.S. Congress for bill seeking terrorist designation of Polisario Front 07:31 Stellantis reports 10% rise in second-quarter vehicle shipments driven by North American demand

Gartner warns most ai driven mainframe migrations will fail

Thursday 16 April 2026 - 10:20
By: Dakir Madiha
Gartner warns most ai driven mainframe migrations will fail

Gartner has warned that a large majority of enterprises relying on generative AI to migrate away from mainframe systems are likely to fail. In a recent report, the firm estimates that more than 70 percent of such projects launched in 2026 will not meet their objectives, citing an overestimation of what AI tools can deliver in complex legacy environments.

The report argues that generative AI can help identify and document technical debt within mainframe systems, but falls short when it comes to fully automating code conversion and migration. These systems often support critical workloads with high performance and throughput requirements that are difficult to replicate outside mainframe environments. As a result, organizations risk losing key capabilities during poorly executed transitions.

Analysts highlight the scale and interconnected nature of enterprise data as a core barrier. Many large organizations operate systems built over decades, with tightly coupled processes and dependencies. According to the report, this level of complexity makes full scale migration both technically challenging and financially prohibitive in most cases.

The study also points to market dynamics driving unrealistic expectations. Investor pressure has pushed software vendors to position AI as a universal solution, encouraging the development of migration tools that may not be suited to real world enterprise needs. At the same time, companies face genuine concerns about aging mainframe expertise and growing technical debt, which increases the appeal of AI driven solutions.

The warning follows earlier developments involving Anthropic, which promoted its Claude Code tool as a way to modernize COBOL systems. That announcement triggered a sharp market reaction, including a significant drop in the stock of IBM, a long time leader in mainframe infrastructure. Gartner’s analysis challenges this narrative, emphasizing that mainframes remain essential for certain mission critical applications.

Instead of pursuing full migration, the firm advises organizations to modernize existing mainframe systems incrementally. The report stresses that failed migration efforts can have severe consequences, including operational disruption and business continuity risks. For many enterprises, maintaining and evolving current systems may offer a more reliable path than attempting a complete transition driven by immature AI capabilities.


  • Fajr
  • Sunrise
  • Dhuhr
  • Asr
  • Maghrib
  • Isha

This website, walaw.press, uses cookies to provide you with a good browsing experience and to continuously improve our services. By continuing to browse this site, you agree to the use of these cookies.