Mainframe Trends 2026

In the world of mainframes right now, the conversation has shifted from "How do we get off the mainframe?" to "How do we make the mainframe the heart of our AI and Hybrid Cloud strategy?"

As of early 2026, the hottest mainframe-related trends are focused on some form of AI adoption and integration on Z. Here are the mainframe trends that I see as of early February 2026.

Agentic AI & In-Transaction Inference

Mainframers are no longer just talking about basic machine learning. The focus is now on Agentic AI as organizations look to build autonomous AI agents that live on the mainframe to handle complex tasks like real-time fraud detection and "self-healing" operations.

The goal is to run AI models directly on the processor (IBM Telum-driven systems) so that every single transaction can be screened by AI and processed efficiently (less than 1 millisecond). Doing this can eliminate the "latency tax" of sending data to the cloud for analysis, which is a game-changer for banks and insurance companies.

Mainframe Modernization (The "Hybrid" Shift)

The "Rip and Replace" philosophy is effectively dead. Instead, the industry is obsessed with Hybrid Cloud Integration. DevOps is hot and developers are using tools like VS Code, Git, and Ansible to manage mainframes. Younger developers don't want to see a "green screen"; they want the mainframe to look and feel like any other cloud server.

In some cases, organizations are using AI-assisted refactoring, basically using generative AI to translate COBOL or Assembler programs into Java or Python. If not completely refactoring from one language to another more developers are relying on AI to document spaghetti code that hasn't been touched in 30 years.

Cyber Resilience & Quantum-Safe Security

With the rise of "harvest now, decrypt later" threats, mainframes are being positioned as the ultimate data fortress. Quantum-Safe Cryptography on the mainframe enables organizations to implement algorithms that can't be cracked by future quantum computers.

In Europe (but also impacting global firms), the Digital Operational Resilience Act (DORA) is a massive driver. Companies are using the mainframe’s inherent stability to prove they can withstand and recover from systemic cyberattacks.

The "Silver Tsunami" vs. The New Guard

The skills gap is a perennial topic, but in 2026, the focus has turned to Mainframe-as-a-Service (MFaaS) and automation to reduce the need for deep internals and systems knowledge.

Furthermore, more organizations are embracing automated operations using AI (AIOps) to manage system health. The promise of automation and AI is so that a smaller team can do the work that used to require dozens of senior systems programmers.

Summary

Of course, these are not the only mainframe trends hapening out there today, but they are the ones at the top of the list IMHO. What do you see? Are there any significant trends or issues that you are currently tackling? Share them here in a comment to get the conversation flowing.

5 Big Concerns of Modern IT When Using Db2 for z/OS

Db2 for z/OS is an entrenched solution for managing data at the world's largest organizations. It is a strong, reliable DBMS and I wrote about its strength recently on the blog (here). You really cannot go wrong using Db2 for z/OS for mission-critical workloads.

That said, there are concerns and issues facing organizations using Db2 for z/OS. One of the biggest concerns with Db2 for z/OS today is managing the cost and complexity of maintaining mainframe environments while still delivering high availability and performance. 

As such, here are 5 specific concerns facing large organizations using Db2 for z/OS today:

1. Skill Shortages: Many mainframe experts, especially those with deep Db2 for z/OS knowledge, are approaching retirement, creating a significant skills gap. The lack of trained professionals has made it challenging to manage and maintain Db2 for z/OS systems effectively.

2. Cost of Licensing and Maintenance: Mainframe systems come with substantial licensing costs. Many organizations are looking for ways to optimize usage or even repatriate workloads to more cost-effective platforms, where feasible, to reduce operational expenses. Whether or not such changes result in "actual" cost reductions is unfortunately irrelevant as many executives believe it will regardless of reality and studies to the contrary.

3. Integration with Modern Architectures: As companies adopt cloud, big data, and other modern architectures, integrating Db2 for z/OS with these systems can be complex and costly. Many seek seamless data integration between Db2 on mainframes and newer platforms like data lakehouses, which involves architectural and technological challenges.

4. Automation and DevOps Compatibility: Modern IT environments emphasize agility, continuous integration, and deployment, but the mainframe environment traditionally doesn’t integrate well with DevOps practices. Nevertheless, many companies are pushing for Db2 automation tools and integration with DevOps workflows to streamline operations and reduce manual workloads... and DevOps is being successfully deployed by mainframe organizations today using Zowe and other traditional DevOps tooling.

5. Performance and Availability: High performance and availability are always top concerns, especially as organizations process more data and need to meet stringent SLAs. Handling lock contention, optimizing query performance, and scaling resources efficiently continue to be challenges. But, to be fair, these are challenges with many DBMS implementations, not just Db2 for z/OS.

Organizations are adopting several strategies to address the challenges with Db2 for z/OS and ensure their mainframe environments remain relevant and efficient:

1. Workforce Development and Knowledge Transfer: To counter skill shortages, organizations are investing in training and upskilling initiatives for new IT staff, partnering with universities, or using mentoring programs to transfer knowledge from retiring mainframe experts to newer employees. Additionally, some companies are leveraging consulting firms or managed services providers with mainframe expertise to fill gaps temporarily.

2. Cost Optimization with Usage Analytics: Companies are using detailed workload and resource monitoring tools to optimize Db2 for z/OS usage, identify inefficient processes, and reduce costs. This includes tuning queries, scheduling batch jobs during off-peak hours, and leveraging IBM’s Workload Manager (WLM) to prioritize workloads based on business needs.

3. Hybrid Cloud and Data Lakehouse Integrations: To manage integration with modern architectures, organizations are implementing hybrid cloud strategies and data lakehouses that can interface with Db2 for z/OS. Tools such as IBM Db2 Analytics Accelerator allow data stored on Db2 for z/OS to be offloaded to faster, scalable platforms, enabling integration with big data and analytics environments without entirely migrating off the mainframe.

4. Automation and DevOps Integrations: Organizations are investing in DevOps and automation tools compatible with Db2 for z/OS, such as IBM UrbanCode and mainframe DevOps solutions from other ISVs such as Broadcom and BMC Software. By automating routine tasks like provisioning, patching, and deploying schema changes, organizations can adopt more agile, efficient processes. Integrating Db2 for z/OS with CI/CD pipelines helps streamline development workflows, bridging mainframe operations with modern DevOps practices. For more details on integrating Db2 for z/OS into DevOps, consult this blog post that highlights several posts I wrote on the topic!

5. Mainframe Modernization with AI and Machine Learning: Using AI and machine learning to optimize Db2 for z/OS operations is becoming common. AI-based monitoring tools, such as IBM’s Watson AIOps, can predict system issues and detect anomalies to prevent downtime. Machine learning algorithms can also be used for capacity planning, workload optimization, and tuning Db2 performance parameters, helping reduce manual intervention.

6. Resilience and High Availability Improvements: For performance and availability, companies are implementing high-availability solutions like IBM Geographically Dispersed Parallel Sysplex (GDPS) to ensure continuous uptime. They’re also using backup automation and disaster recovery solutions tailored for Db2 to meet stringent SLAs and minimize downtime in case of failures.

By combining these strategies, organizations are better equipped to manage the costs, complexity, and skills required to maintain and modernize Db2 for z/OS environments in today’s rapidly evolving IT landscape.