AI to help mainframes remain business critical in 2026

For years, rip and replace has dominated conversations about the mainframe. A smarter, more pragmatic reality is now taking hold. 

Mainframe systems can process millions of transactions in seconds, making them indispensable for core business functions – from database management to ERP and CRM – that demand absolute consistency and speed. Far from being obsolete, they are the quietly powerful bedrock of modern commerce, handling 90% of all credit card transactions and serving over 70% of global enterprises, according to Gartner.

But as digital demands grow, businesses need their mainframes to keep up. Modernisation helps them move with more agility, support developers better, plug into cloud technologies and manage costs more smartly, which are all essential to stay competitive.

This forces a new, more urgent question for today's IT leaders. As every penny of investment is scrutinised, the focus has shifted from debating the mainframe's future to a more practical challenge. Namely, how do we modernise this critical infrastructure and clearly demonstrate its value in a hybrid world?

Practical modernisation without the Big Bang

In conversations I have with IT leaders it's clear the idea of a risky 'big bang' migration is losing its appeal and for good technical reasons. 

More than 70% of Fortune 500 companies still rely on mainframes – according to Forbes – often built on decades of interwoven COBOL and RPG code and custom business logic. In this environment, where a single change can trigger a domino effect across critical programmes, attempting a wholesale lift-and-shift presents too many risks to be considered a viable strategy.

Instead, a more practical, incremental modernisation is proving effective. The key is to connect mainframes with cloud environments to create a hybrid ecosystem that leverages the best of both worlds. A key technical pattern is to API-enable core mainframe applications, to allow them to participate seamlessly in this broader architecture. This allows teams to build new, cloud-native front ends that leverage the unmatched security and reliability of mainframe transaction processing on the back-end.

There’s no denying this approach demands substantial investment, time and meticulous planning. But this approach to modernising without dismantling allows teams to innovate securely, reduce technical debt and ensure every change is targeted and aligned with clear organisational objectives. It’s an approach that allows teams to innovate without introducing unnecessary risk, systematically reduce technical debt and ensure that every single investment in modernisation is directly aligned with clear, measurable business objectives.

How AI is changing the performance conversation

AI is accelerating this modernisation shift by directly addressing the longstanding challenge of data gravity, and recognises that the smartest approach is to bring analysis to the data instead of forcing the data to move.

Rather than undertaking the costly, complex and high-risk process of moving massive volumes of sensitive information to a separate platform, AI models can now run directly on the mainframe. 

This provides, for the first time, clear business insights from raw performance data, right at the source. A retail bank, for example, can analyse live transaction data to understand why a customer might abandon a purchase, all without that information ever leaving the secure mainframe environment.

Building on this, generative AI is accelerating the modernisation process itself, offering powerful new ways to analyse legacy systems and streamline transformations. 

This technological shift completely reframes the investment conversation. Leaders can now justify mainframe spending not as a defensive capital expenditure to maintain the status quo, but as a growth-focused operational expenditure that directly underpins business success and a better customer experience.

Total cost of ownership as a strategic tool

And this is exactly where Total Cost of Ownership (TCO) becomes key. As AI reshapes how organisations extract value from the mainframe, IT leaders need a way to quantify that value clearly and credibly across the business.  

Modern TCO can’t stop at a basic comparison of hardware costs. In the AI era, the conversation needs to mature from TCO to Total Business Value. This means calculating the ROI of the platform by factoring in the strengths that drive real impact: built-in security that reduces breach risk, resilience that prevents costly outages, and the transactional performance that underpins core business operations.

The 2025 BMC Mainframe Survey confirms the mainframe is here for the long haul, with a 97% long-term commitment rate. This reality brings a new question to the forefront, namely how do you manage it intelligently? The answer lies in a value-based TCO, which provides the framework to make the crucial "modernise vs migrate" decision for every application.

For one financial services giant, this meant standardising how TCO was calculated across more than 4,500 applications. By creating a unified data model that captured this broader view of value, they gained the clarity needed for an honest, apples-to-apples comparison. This is what makes modern TCO a strategic aid in business as it provides one source of truth needed to turn a complex choice into a clear business decision.

Future proofing

By tapping into AI for sharper insights, looking at TCO through a value‑driven lens, and taking a hybrid path to modernisation, leaders can get far more out of their most important systems and stay central to today’s digital business landscape.

But this is just the beginning. The future of the mainframe lies in its ability to evolve, and AI is the key accelerator. As we look ahead to an era defined by AI and even quantum computing, the platform's unique strengths mean more applications, not less, will be best-fit for the mainframe, delivering unmatched value for the years to come.