The Future of Mainframe Excellence

In many ways, the mainframe world is built on speed. The platform’s processing power enables it to process a high volume of transactions quickly and efficiently, making it perfect for today’s 24-hour web- and mobile-driven economy, where consumers expect to do what they need to do in a matter of milliseconds.

In a competitive market that is still adjusting to a post-pandemic world, our customers are looking to speed innovation, releasing new digital services and applications faster than their competition. These applications must, of course, access data and execute transactions as quickly as possible. When something goes wrong, response is measured in mean time to detect (MTTD) and mean time to resolution (MTTR), and a timely response to security threats can be the difference between uninterrupted service and reputational and economic catastrophe.

But as our customers seek to optimize and transform their mainframe environments to respond as quickly as possible to increased transaction volume, market forces, and threats, the integration of automation and the emergence of artificial intelligence (AI) do more than just satisfy the need for speed. They augment the capabilities of the mainframe workforce, enabling all of you, whether you are a developer, database administrator, system programmer, or security professional, to do more of what you do best—develop innovative solutions that meet the needs of your internal and external customers, with confidence.

Infusing AI and expanding automation and efficiency, the October release of enhancements to the BMC AMI portfolio strengthens mainframe professionals’ ability to go beyond what was previously possible and forge new paths of mainframe excellence.

Faster time to innovation on mainframe

October’s release features the first BMC AMI solution to incorporate BMC AMI Assistant, the new GenAI-based solution. Embedded in the in-product experience of BMC AMI DevX Code Insights, it incorporates code explanation in order to mitigate risk and speed time to development. BMC AMI DevX Code Insights is now also available for VS Code.

To learn more about BMC AMI Assistant and our roadmap for the future, read BMC Mainframe Vice President and General Manager John McKenny’s blog post, “You’ve Never Mainframed Like This: Introducing BMC AMI Assistant.”

Optimizing cloud storage management

New functionality within BMC AMI Cloud Data lets storage admins automate the expiration of backups of deleted data sets, helping to reduce overhead and ensure more efficient management of cloud resources. And a new multi-section delete feature streamlines the process of expiring batches of resources and completes the transition to a modernized, user-friendly resources page user interface.

Efficient database performance and security reporting

Database administrators and system programmers can manage complex systems more efficiently with enhancements to BMC AMI Data that simplify IBM^® IMS™ data migrations and streamline resource management across IBM^® Db2^® environments by reducing CPU utilization and improving query performance.

A new feature in BMC AMI Command Center for Security significantly reduces MTTR by automating the generation of detailed forensic reports for specific events within a set time frame. Reports currently compiled manually can now be automatically generated within seconds, improving incident response efficiency.

Harnessing the power of AI and cloud

The features included in our October release leverage the latest technology to empower mainframe users to innovate on, manage, and secure the platform with increased ease and efficiency. As AI and other emerging technologies develop, BMC promises to continue delivering new features and enhancements while we stand as your partner in expanding what is possible on the mainframe.

To learn more about new features included in the October release, including new education courses available for BMC AMI solutions, visit our What’s New in Mainframe Solutions page.

The greatest roadblock to modernizing applications on the mainframe is fear. Fear that making any change, no matter how minor, will break something.

Given that older, monolithic mainframe applications are typically mission-critical – core bank transaction processing, airline reservation systems, insurance ratings, and claims management, to name a few – IT executives are understandably reluctant to touch such apps at all.

It’s no wonder: Many of these applications are extraordinarily complex, consisting of layers of code from decades of development work, in many cases following no consistent coding or documentation practices over the years or decades they have been running the business.

Furthermore, as mainframe professionals retire, their organizations risk the loss of their tribal knowledge – perhaps the only knowledge of how many mainframe applications work. What was once a maintainable application suddenly becomes frighteningly opaque once the experts leave the building.

Despite such challenges, evolving business needs mandate ongoing updates to legacy applications on the mainframe. Regardless of their fear or loss of seasoned personnel, it’s time for today’s mainframe teams to take the plunge and leverage modern tooling to modernize mainframe applications in place.

A New Generation of Mainframe Tooling

The first step in untangling complex, monolithic mainframe code is to gain visibility into its inner workings. Tools like BMC AMI DevX Code Insights, for example, leverage BMC’s expertise with runtime observability to provide visualizations of mainframe code, enabling developers to understand interactions, dependencies, and relationships among programs.

BMC AMI DevX Code Insights gives developers the power to save and replay execution traces, providing insight into program calls, behaviors, and input/output types. The tool also provides data flow analysis, as well as code structure and logic charts, giving developers an understanding of how data flow through an application.

BMC AMI DevX Code Insights breaks down the impenetrability of complex, monolithic mainframe applications – but it doesn’t go far enough. Even with such powerful tooling, developers are left with an essential question.

What does the program actually do?

Tools like BMC AMI DevX Code Insights need additional capabilities to answer this fundamental question.

Tracing data flows is one thing, but connecting the numerous lines of code to the business requirements that originally defined their behavior can be elusive, especially for more complex, layered applications.

The missing piece of the puzzle: generative AI (GenAI). GenAI feeds massive data sets into large language models (LLMs), which, in turn, answer user queries in natural, conversational language.

With GenAI, tools like BMC AMI DevX Code Insights can finally answer this question.

Extending BMC AMI DevX Code Insights with GenAI

BMC has incorporated the power of GenAI into BMC AMI DevX Code Insights via its BMC AMI Assistant capability. The assistant takes as input existing source code, then outputs conversational English that describes what the code actually does – not only to developers, but to business analysts, managers, or anyone else with a vested interest in the behavior of mainframe applications.

BMC AMI Assistant works seamlessly with the rest of BMC AMI DevX Code Insights, augmenting its code structure and data flow analysis capabilities with insight into the behavior of the applications themselves.

The result is quick understanding of even complex, unfamiliar code – with clear explanations of what the code is doing and how it’s doing it.

In fact, the output from BMC AMI Assistant is so clear that developers can use it to add comments to code that may have been lacking adequate documentation – giving future developers a leg up on further modernization work.

Beyond Code Explanations

GenAI can be useful for more than code explanations on the mainframe. Here are some examples.

Code reviews – GenAI can augment human code reviews by providing on-demand, interactive feedback based on corporate rules, policies, and best practices.

Test assistance – GenAI can create test cases with optimal coverage while also creating the minimal quantity of test data necessary to run the tests. The test assistance functionality can analyze the source code itself to determine the best strategy for testing it.

Code assistance – GenAI can provide a “copilot” that can leverage knowledge of best practices, design patterns, and coding standards, both industrywide and specific to the organization.

The Intellyx Take

The two main reasons why people are so afraid of touching monolithic mainframe code are the lack of visibility into what that code is doing and insufficient control over the code’s behavior.

With its new GenAI-powered capabilities, BMC AMI DevX Code Insights addresses both causes. Not only does BMC AMI DevX Code Insights with BMC AMI Assistant help developers understand the structure and behavior of complex mainframe applications, it also provides vital insights into what those applications actually do for the business.

BMC AMI DevX Code Insights has now become an even more vital tool of empowerment for mainframe development teams – not only dispelling the fear of breaking something, but also instilling the confidence that developers can make the updates and changes their organizations require, regardless of the complexity of the code.

Copyright ^© Intellyx BV. BMC is an Intellyx customer. Intellyx retains final editorial control of this article. No AI was used to write this article.

In July, I invited you to join us on a journey. Through our statement of direction, BMC outlined a bold vision for the future of mainframe modernization—a vision where artificial intelligence (AI), generative AI (GenAI), and the cloud would become essential tools in simplifying mainframe transformation. Today, I’m excited to share the next major step in that journey: the introduction of BMC AMI Assistant.

Before we delve into the powerful capabilities of BMC AMI Assistant, it’s important to understand the real-world impact this technology can bring to your organization as you strive to simplify and transform the mainframe environment. At this pivotal moment for the mainframe, organizations are not only scaling their workloads, but also looking to modernize the way they work. For example, application development leaders have told us that they are eager to move developers and system programmers (SysProgs) off the green screen and onto modern tools that accelerate innovation, lower operational costs, and address the widening knowledge and skills gap.

BMC AMI Assistant is paving the way for the future of mainframe environments, providing your organization with a roadmap for GenAI-driven solutions that are common in other IT landscapes but now tailored for the mainframe. By simplifying complex tasks, automating routine processes, and enabling teams to innovate faster, BMC AMI Assistant can help your organization fully embrace new ways of working—modernizing mainframe applications and operations to stay competitive while maximizing the value of your existing infrastructure.

Increasing productivity across the talent pool

Mainframe organizations are grappling with a demographic shift: Senior-level mainframe professionals are retiring, taking decades of “tribal knowledge” with them, and leaving a knowledge gap behind. Customers are also needing to grow mid-career professionals and identify the next generation of leaders to hand the reins to. By embracing GenAI enhancements in the daily workflow, mainframe organizations ultimately will have more productive people, more collaborative teams, and a stronger, more resilient organization that can withstand the day-to-day pressures of ransomware attacks, regulator needs, and new initiatives with confidence.

According to the 2024 BMC Mainframe Survey, this shift is stark. Since 2019, there has been a 23 percent drop in respondents with 20+ years of mainframe experience, while the number of respondents with six to 10 years of experience has increased by 14 percent.This demonstrates a clear demographic change that is reshaping how organizations manage and optimize their mainframes.

Simultaneously, mainframe priorities have evolved. AIOps, once ranked ninth as a priority in the 2023 survey, rose to the third-place priority in 2024, and for large organizations, it became the second-highest priority. However, managing AIOps is becoming increasingly complex. In fact, 60 percent of extra-large organizations that prioritize AIOps report that they plan to use GenAI to tackle this complexity. Additionally, a recent study found that one of the top potential GenAI use cases in financial services is code modernization. It is clear there is value to be captured by embracing this new technology.

This is where BMC AMI Assistant steps in. BMC AMI Assistant is not a separate solution—it is BMC’s implementation of GenAI technology, infused directly into existing BMC AMI solutions across the stack of applications, operations, data, and security, transforming everyday activities into more intelligent, responsive, and intuitive experiences for your practitioners. This allows organizations to leverage GenAI without having to leave the products they are already working in. By automating tasks, providing real-time insights, and offering actionable recommendations, BMC AMI Assistant helps bridge the knowledge gaps in mainframe expertise, simplifies the effort of mainframe management, and eases the burden of managing increasingly complex workloads.

A strategic AI partner for mainframe management

The roadmap for BMC AMI Assistant is designed to seamlessly integrate into the BMC AMI solutions your teams already use, enhancing and simplifying your daily management operations with the power of “in-product” GenAI capabilities. Whether you’re a developer navigating complex code, an operator diagnosing performance issues, or an IT manager reviewing metrics and reports, GenAI-driven functionality will enrich the tools you already know, providing advanced capabilities without adding complexity to your environment. Acting as both a copilot, guiding teams with real-time insights, and an autopilot, automating routine tasks, the assistant will help ensure continuity and efficiency.

At a broader level, BMC aims to continue the deep partnerships with our mainframe clients and ensure that the innovations we put into our overall portfolio help you continue to simplify the mainframe platform so it can be treated like any other IT platform, with common approaches to management and tools that excite new practitioners to get involved in this space.

Bridging the knowledge gap with BMC AMI Assistant

BMC AMI Assistant can act as one critical element of your organization’s strategy to address the significant loss of expertise from the loss of retiring mainframe professionals by encoding expert knowledge into the products themselves. This enablement, along with education and recruitment, can be the “third leg in the stool” of an organizational strategy for talent preservation and growth.

One core element of our approach is to enable all team members across a mainframe environment to be more efficient and productive, regardless of their skill level:

• Developers: Real-time code explanations simplify complex legacy code, empowering even those new to mainframes to work efficiently.
• SysProgs: AI-driven root cause analysis allows SysProgs to identify and resolve incidents faster, ensuring operational resilience without relying on expert intervention.
• IT managers: Real-time insights and proactive recommendations generated automatically by GenAI help IT managers optimize performance, reduce inefficiencies, and make faster, smarter decisions.

By infusing GenAI into BMC AMI solutions, BMC AMI Assistant not only bridges the knowledge gap for next-generation mainframers, but also empowers developers, SysProgs, operators, and IT managers at every level. It enhances productivity by automating repetitive tasks and providing real-time insights and recommendations, enabling even seasoned mainframe experts to make faster, more strategic decisions while focusing on initiatives that drive greater efficiency and innovation within their organizations.

BMC AMI Assistant in action: The new capabilities available now

I am delighted to announce today three key areas where BMC AMI Assistant is now available for application development and operations teams, and couldn’t be prouder of our engineering team who have brought these new AI-driven capabilities directly into the BMC AMI solutions you rely on.

• Eliminate the fear of changing complex unfamiliar code: Now supercharged with GenAI-driven BMC AMI Assistant, BMC AMI DevX Code Insights eliminates developer roadblocks by providing rapid understanding of complex code. From within the daily workflow, developers can instantly comprehend unfamiliar code, enabling confident maintenance and extension of mainframe applications. The in-product experience allows code explanations to be inserted as comments, empowering developers to review, extend, and test code with unprecedented efficiency.
• Expand mainframe development to include industry-standard VS Code: BMC AMI DevX Code Insights, with its new GenAI functionality, is now available in BMC AMI DevX Workbench for VS Code, allowing developers to quickly understand complex and unfamiliar code with real-time runtime visualization, structure, and logic charts for guided improvement. From the familiar VS Code environment, developers can track data flows, refactor complex programs, and comment out dead code, simplifying mainframe software development. Now, users of Workbench for VS Code will have access to the GenAI services of BMC AMI Assistant, and, from the editor of BMC AMI Workbench, get the benefit of code explanations.
  • For organizations that leverage BMC AMI DevX Workbench for VS Code and hold a license for BMC AMI DevX Code Insights, BMC AMI Assistant can extend its AI-driven capabilities to BMC AMI DevX Code Debug and BMC AMI DevX Code Coverage. This allows developers to streamline software development processes, enabling teams with limited mainframe expertise to work more effectively and efficiently.

• Resolve issues faster and minimize downtime: BMC AMI Assistant has been infused into BMC AMI Ops Insights (Beta), providing an explanation feature specifically for SysProgs. It delivers root cause analysis and explanations for performance issues and outages in mainframe systems in clear, plain language. SysProgs can gain a clear understanding of the root cause, show how metrics and KPIs are interrelated, and, in upcoming versions, receive actionable recommendations to speed up the resolution process. This infusion of GenAI helps ensure faster recovery and reduced downtime by delivering the insights SysProgs of all experience levels need to resolve issues quickly.

Reducing toil while continuously improving mainframe development

Development and IT managers often struggle with the manual effort of gathering, analyzing, and interpreting the multitude of metrics necessary to make informed decisions and continuously improve the mainframe application development process. Reducing this toil while still obtaining actionable insights is crucial for optimizing performance.

Earlier this year, BMC introduced a cutting-edge feature within BMC AMI zAdviser Enterprise (available as a SaaS solution, but currently in Beta for on-premises deployment), an early example of how we’re leading the way in mainframe transformation. Powered by GenAI, BMC AMI zAdviser Enterprise automates repetitive and redundant tasks, allowing users to focus on more strategic initiatives. This is a prime example of how BMC continues delivering innovative technologies that empower organizations to modernize their mainframes efficiently.

BMC AMI zAdviser Enterprise’s autopilot capabilities allow users to automatically generate detailed reports on key DevOps metrics (including summary, analysis, and recommendations for improvement), enabling IT managers to monitor and optimize performance continuously. This example highlights our ongoing commitment to driving mainframe modernization through the power of AI.

Conclusion: You’ve never mainframed like this

BMC AMI Assistant is just the beginning of a broader effort to make mainframe environments simpler and more efficient through the power of AI. As the assistant’s capabilities expand, it will continue to reduce complexity and enhance efficiency across mainframe operations, all within the BMC AMI solutions you already rely on.

With BMC AMI Assistant, we are fulfilling our promise to simplify mainframe management and address the knowledge gap left by retiring experts. By automating tasks and providing real-time insights, this GenAI-powered assistant transforms how you manage teams and optimize mainframe environments.

As we continue to enhance its capabilities, BMC AMI Assistant will help your teams simplify mainframe management with confidence and ease. The future of mainframe transformation is here, and you’ve never mainframed like this.

Meet Divya, an IT manager at a large financial services company. Every day, Divya faces the challenge of maintaining the company’s critical mainframe systems while navigating the rapid pace of technological advancements. Recently, Divya’s organization has been contemplating how to address its aging mainframe workforce while also maintaining the expected levels of service. It has three choices: 1) Get off the mainframe, 2) Become caretakers of the mainframe, or 3) Modernize the mainframe in place.

The dilemma

The first option, getting off the mainframe, is quite a project. As we have seen in the industry, many have tried and failed. One needs to ask, “Why replicate a system that is providing core business value? What is the true benefit?” In doing this, companies introduce cost and a lot of risk and disruptions to operations, and stifle business innovation. In this technology swap, organizations retiring their mainframes must model effort, cost, and risks that they have never considered before as they replatform, refactor, and replace critical applications, systems, and infrastructure. Let’s not forget that the effort of moving off the mainframe is consuming person hours that would have been spent delivering more business innovations. So, again, why would this be a preferred option?

The second option, being mere caretakers of the mainframe, means maintaining the status quo without modernizing—keeping the lights on, in other words. As caretakers, the team is no longer using the mainframe strategically, and nothing is being done to retire it. This risks stagnation and obsolescence in a rapidly evolving technological landscape. Essentially, the decision here is to just “let it die.” As many core systems are on mainframes, this is simply not an option, especially in the financial sector, where risk and continuity of service is regulated.

If no innovation is delivered, business is lost and customers move on since their expectations are continuously evolving. As customers, we are always “wonderfully dissatisfied” with functionality and demand more not less, and businesses need to keep up. The only strategic and advantageous choice, Divya realizes, is to modernize the mainframe in place, which avoids a world of upheaval and the expense of a full system replication.

What does “modernize the mainframe in place” mean?

“Modernizing the mainframe in place” refers to the process of:

• Updating and enhancing the existing mainframe ecosystem, without or migrate it to entirely new platforms
• Leveraging intuitive and automated technologies and practices to meet contemporary business needs and make the platform more accessible

This approach leverages the mainframe’s steadfast reliability, scalability, and security while layering in a completely modern, intuitive experience from generative artificial intelligence (GenAI) and addressing system custodianship and application production to keep pace with business demands. In fact, our customers have done it, and can attest that having a good transformation partner with the right experience and shared best practices can make the process significantly easier.

Why now?

The urgency to modernize the mainframe is here now, and it cannot be ignored. As technology rapidly advances, organizations that fail to update their legacy systems lose their competitive edge amid the consumer appetite for increasingly digital, real-time access to financial institutions, utility providers, or marketplaces, and more.

Delaying modernization can lead to increased vulnerabilities, higher maintenance costs, and difficulty attracting top talent. By starting now, organizations ensure their mainframes remain core to their digital transformation strategies, as well as the business as usual (BAU) in an ever-evolving market. Another reason for Divya to modernize the mainframe in place is to maintain the organizational intellectual property (IP) that has been refined over decades and is the foundation of why customers selected the company in the first place.

Operational impacts

For Divya, moving off the mainframe is similar to clearing a 40-year-old garden that has overgrown with layers of interwoven plants, each representing decades of intricate, mission-critical code. The IP embedded in this code is complex and vital, requiring a deep understanding before any transformation can occur. Just as every plant in the garden has its place and purpose, so does each line of code. Modernizing in place allows Divya to trim, nurture, and optimize this “garden,” ensuring business continuity and leveraging existing strengths without uprooting the entire ecosystem or losing critical functionality. That, combined with the significant costs of a replication off platform, make modernizing in place a far more viable and strategic choice.

“Modernizing the mainframe in place revolutionizes your legacy systems with cutting-edge technology. It unleashes unprecedented innovation, efficiency, and security, while preserving valuable organizational IP. This transforms your mainframe into a powerhouse of modern computing—eliminating the need for a business disruptive replication.”

Key elements

To embark on this journey of modernizing the mainframe in place, Divya focuses on integrating several key elements that align with her organization’s goals and needs:

• Leveraging modern tools: To empower next-generation developers, operators, and system programmers, Divya integrates the mainframe platform with a modern user interface (UI) and an automated, intuitive application production line that provides automatic insights on velocity and quality of delivery. On the systems side, action-oriented insights help remove human decision within the complex environment, ensuring operational efficiency and keeping pace with digital business demands. Divya also finds that the new tools attract and retain top talent, further strengthening the team.
• Implementing AI and GenAI: By leveraging AI and GenAI, Divya automates routine tasks and enhances decision-making processes. This improves efficiency, reduces human error, and fosters innovation by providing new insights and capabilities. Divya is excited to see how AI can transform her mainframe operations. AI is also used to navigate application knowledge so that new generations can innovate faster by understanding the dependencies between applications to bridge tribal knowledge needs.
• Enhancing DevOps practices: Incorporating DevOps methodologies from x86 systems to mainframe streamlines the development and deployment processes of mainframe applications. Divya sees faster development, as well as more reliable software delivery, improved collaboration between development and operations teams, and a seamless workflow. Also, measurement is now possible so that problems can be discovered and remedied. The morale among Divya’s team improves as they experience fewer bottlenecks and delays.
• Improving UIs: Updating UIs to be more intuitive and user-friendly makes it easier for Divya to find and onboard a new generation of developers and operators to work with the mainframe platform, while reducing training time and enhancing productivity. Even the more experienced developers like that the new tooling has multiple perspectives and is easy to navigate.
• Enhancing security and compliance: Implementing advanced security measures and compliance protocols helps Divya protect sensitive data, meet regulatory requirements, and ensure operational resilience, so she is confident in the organization’s ability to withstand the constantly evolving threat landscape.
• Optimizing performance and efficiency: Utilizing modern tools and techniques, Divya improves the performance and efficiency of mainframe operations. This reduces costs and enhances overall productivity, boosting the effectiveness—and morale—of both development and operations teams.
• Connecting the mainframe to the wider enterprise and cloud: The mainframe must not be an isolated island, but instead a fully integrated component of the enterprise IT landscape in terms of data, events, metrics, and methodologies of application production across the wider enterprise. Divya works to align mainframe data management with hybrid cloud strategies, ensuring seamless connectivity and unified management.

Transformative value

The impact of these collective efforts is substantial, providing a comprehensive array of benefits that enhance organizational efficiency, drive innovation, and secure a competitive edge in the rapidly evolving technology landscape.

• Unleashing innovation: By using integrated development environments (IDEs) and integrating AI and GenAI, Divya drives unprecedented levels of innovation. These technologies provide new capabilities, automate repetitive tasks, and offer deep insights that were previously unattainable, thus increasing the person hours focused on pure innovation.
• Enhancing efficiency: Streamlining DevOps practices and leveraging modern tools significantly enhances the efficiency of both developers and operators. This leads to faster development cycles, reduced downtime, and more reliable operations.
• Improving security and compliance: Advanced security measures and compliance protocols ensure that mainframe systems remain secure and adhere to regulatory standards. This is essential for protecting sensitive data and maintaining trust with customers and stakeholders.
• Boosting productivity: Modern UIs and optimized performance make it easier for teams to work with mainframes. This reduces training time, minimizes errors, and allows teams to focus on more strategic initiatives.
• Reducing costs: By improving operational efficiency and reducing the need for costly migrations, modernizing in place offers significant cost savings, allowing Divya to leverage existing investments while reaping the benefits of modern mainframe technologies.
• Empowering teams: Next-generation developers and operators are empowered with advanced tools and intuitive interfaces, making it easier for them to innovate and excel in their roles. This attracts and retains top talent, ensuring a strong workforce for the future.

A vision for the future: BMC AMI

With BMC AMI, our vision is to revolutionize mainframe systems with cutting-edge technology, unleashing unprecedented innovation, efficiency, and security. We aim to transform mainframes into powerhouses of modern computing without the upheaval of a full-system, off-platform replication. Our approach to modernizing the mainframe in place empowers organizations like Divya’s to harness the unmatched reliability of their existing systems while integrating modern technologies and practices.

Conclusion

Modernizing the mainframe in place is not just a strategic initiative for Divya; it is a transformative journey that enables her organization to stay competitive, innovative, and resilient in the digital age. By adopting cloud-native technologies, implementing AI and GenAI, enhancing DevOps practices, improving user interfaces, leveraging modern tools, enhancing security and compliance, and optimizing performance and efficiency, Divya can unlock the full potential of her mainframe systems.

Embracing this approach ensures that mainframes continue to play a vital role in the modern IT landscape, driving innovation and supporting critical business operations. At BMC, we are committed to helping organizations like Divya’s achieve this vision, providing the tools, technologies, and expertise needed to transform mainframe systems into future-ready powerhouses.

This year marks my tenth year at BMC, and for almost all of that time, I have been associated with conducting the BMC Mainframe Survey. In the analysis phase we have just completed, one thing from the survey results stood out this year ahead of all others. Throughout the data, we observed a new priority and focus on the use or potential use of artificial intelligence (AI) to manage mainframe complexity and the knowledge gap created by the changing mainframe workforce. Leveraging AI, including machine learning (ML) and generative AI (GenAI), has become crucial for enhancing operational efficiency and meeting modern IT demands. This blog post explores the role of AI in mainframe transformation based on insights from BMC’s 2024 Mainframe Survey, highlights key trends and challenges in this evolving landscape, and provides strategic recommendations for how organizations can effectively leverage AI in their mainframe environments.

Understanding AI: ML versus GenAI

AI encompasses a range of technologies that enable machines to mimic human intelligence, including problem-solving and decision-making. Within this broad field, AI/ML involves the use of algorithms to analyze data, learn from it, and make predictions. GenAI, a subset of AI, goes a step further by creating new content or solutions based on learned patterns. Each of these technologies offers unique capabilities and applications in mainframe environments:

• ML: Advanced data analysis and anomaly detection enable proactive issue identification and resolution, ensuring smoother system performance.
• GenAI: By automating code generation and addressing complex problems, GenAI drives innovation and transformation in mainframe operations.

Survey insights on AIOps

Results of the 2024 BMC Mainframe Survey show that AIOps, the application of AI to IT operations, has seen a significant rise in prioritization among mainframe organizations, increasing from 34 percent in 2023 to 45 percent in 2024. Notably, AIOps, which ranked ninth in mainframe priorities in 2023, has moved into the top three in this year’s survey, indicating a strategic shift towards AI-driven operations. Extra-large shops (greater than 50K MIPS), with a higher AIOps prioritization of 54 percent, demonstrate the critical role of advanced AI technologies in large-scale environments. GenAI, in particular, is highlighted as the most important capability, with 45 percent of organizations emphasizing its significance.

Leveraging GenAI and ML to address AIOps complexity

Despite its benefits, AIOps for the mainframe is particularly complex due to the intricate and highly integrated nature of mainframe systems, which have been developed and expanded over decades. These systems often run a vast array of critical applications, each with unique dependencies and configurations, creating a challenging environment for traditional IT operations.

The survey reveals that 31 percent of mainframe organizations that have implemented AIOps perceive complexity as a major issue, up from 24 percent in 2023. This growing concern underscores the need for effective solutions to manage and mitigate these challenges. The impact of AIOps complexity on mainframe operations requires strategic approaches, such as leveraging GenAI and ML technologies to streamline and optimize processes. Sixty percent of extra-large mainframe organizations that are prioritizing AIOps are looking to solve this AIOps complexity issue using GenAI solutions, while 57 percent are using ML-based automation.

GenAI adoption in mainframe organizations

The mainframe survey shows that 76 percent of organizations are using GenAI, reflecting its widespread acceptance and implementation. In terms of mainframe adoption, 86 percent of respondents who are increasing their mainframe investment are using GenAI. These organizations are significantly more likely to use the technology than those who have a flat or decreasing investment in their mainframe systems, and 82 percent have a GenAI policy in place.

Benefits observed by organizations using GenAI include significant improvements in efficiency and operational performance, with 40 percent reporting notable advancements. Of organizations prioritizing AIOps, 45 percent say that GenAI is the most important capability to help them achieve their objectives. The high adoption rate of GenAI and recognition of its benefits underscore the technology’s potential to transform mainframe operations and drive innovation.

Current GenAI use cases in mainframe transformation

Based upon the survey results, respondents report that GenAI shows great promise in various ways to enhance mainframe operations:

• Automation: Thirty-seven percent of organizations want to use GenAI to eliminate repetitive tasks, improving efficiency and freeing up resources for strategic activities.
• Identifying issues and risks: Thirty-six percent of organizations seek to analyze code and configuration files to identify problems and vulnerabilities, enhancing security.
• Gaining insights: Thirty-four percent of organizations want to augment existing expertise with critical business insights, supporting decision-making processes.
• Training: Thirty-three percent of organizations plan to use GenAI for onboarding and training new personnel, effectively bridging the knowledge gap.

These use cases demonstrate the versatility and impact of GenAI in driving mainframe transformation.

Recommendations: Future opportunities for AI in mainframe transformation

The future of AI in mainframe transformation looks promising, with emerging trends indicating the continued evolution of AI technologies. With nearly half of organizations seeing GenAI as the most important capability to help them achieve their objectives, you should focus on getting AI right with use cases that benefit your business. These advancements offer new opportunities for enhanced automation, predictive analytics, and real-time problem-solving capabilities. To capitalize on these opportunities, organizations can invest in:

• Strategic planning: Develop a strategic roadmap with policies for integrating AI into mainframe operations, aligning with business objectives.
• Education: Equip employees with the knowledge and skills needed to leverage AI technologies effectively.
• Infrastructure upgrades: Ensure that the necessary infrastructure is in place to support AI implementations.

Conclusion: Strategic recommendations for AI in mainframe transformation

AI presents many opportunities for transforming mainframe environments, particularly in application development and operations. Based on the insights from the BMC Mainframe Survey, here are some strategic recommendations:

• For application development:
  • Use AI to assist in routine coding tasks and enhance code maintenance.
  • Detect code anomalies early, reducing the likelihood of errors.
  • Leverage code explanation for better understanding of unfamiliar code and applications.
• For operations:
  • Use ML for advanced data analysis and anomaly detection, enabling proactive issue detection.
  • Implement AI rules to perform problem diagnosis and identification.
  • Apply GenAI to automate problem resolution and optimize system performance, enhancing overall operational efficiency.

By embracing these AI technologies, organizations can drive innovation, improve efficiency, and maintain a competitive edge in the rapidly evolving IT landscape. The strategic adoption of AI will be pivotal in realizing the full potential of mainframe transformation.

For more insight into the trends affecting the mainframe, visit the 2024 BMC Mainframe Survey page.

Results of the 2024 BMC Mainframe Survey have been released, and they reveal that the state of the mainframe is strong, with a bright outlook, thanks to emerging technologies and continued digital transformation. The mainframe’s speed, processing capacity, and security continue to make the platform a key component of the ever-changing IT landscape. Enhancements to the platform’s hardware, like the IBM^® z16’s Telum^® processor, development of adoption of modern, intuitive tooling, and incorporation of artificial intelligence (AI) and machine learning (ML) have increased the mainframe’s capabilities while also making it more accessible to IT professionals. The result is that mainframes are still in high demand as a reliable platform for new innovation.

Positive perception

This year’s edition of the BMC Mainframe Survey, now in its 19^th year, shows that positive perception of the mainframe remains high, with 94 percent of respondents seeing it as a long-term platform or a platform for new workloads. Not surprisingly, survey results also show that investment in the mainframe remains high, with 90 percent of respondents reporting that their organizations are continuing to invest in the platform. While large (10,001–50k MIPS) and extra-large (greater than 50k MIPS) shops show increased investment, smaller shops (under 10k MIPS) are seeking to maintain current investment levels while leveraging new technologies to optimize within their current footprint.

Top priorities: Compliance and security

Named by 64 percent of 2024 BMC Mainframe Survey respondents, compliance and security top the list of mainframe priorities for the fifth consecutive year. While the threat of ransomware remains a top concern, survey respondents report decreased confidence in the effectiveness of their ransomware controls, with an eight percent drop in those that find their controls to be extremely effective. This drop in confidence is even more pronounced in European respondents, with a 10 percent decrease.

With official application of the European Union’s Digital Operational Resilience Act (DORA) coming in January 2025, and ransomware attacks continuing to make headlines, it is clear that ransomware controls, hardened security, and recovery capabilities are facing increased scrutiny.

New technologies are getting attention

Cost optimization took the second spot on the list of priorities, while the number of respondents listing artificial intelligence for IT operations (AIOps) and operational analytics as a top priority jumped to 45 percent (an 11 percent increase from 2023), moving it into the top three.

The increased prioritization of AIOps reflects surging interest in the implementation of emerging technologies on the mainframe. Those reporting the adoption of AIOps on the mainframe increased nine percent from the 2023 BMC Mainframe Survey, while 76 percent of respondents reported the use of generative AI (Gen AI) in their organizations.

The power of AI/ML and Gen AI open a new world of possibility in IT management. Organizations are leveraging these technologies throughout their IT ecosystems to gain real-time insight into security postures, automate issue resolution, gain critical business insight, and onboard and train new personnel.

Respondents are also considering the use of cloud technologies, with storage backup, connecting the mainframe to cloud-based workloads, and utilizing a cloud-based mainframe as leading considerations.

While not technically a new technology, the use of Java for mainframe code is increasing, as well. As organizations feel the need for code that is accessible across platforms, and for developers who can write mainframe code without additional training, Java has emerged as an attractive option. Survey results show an increase in new applications being written, and in the rewriting of existing applications, in the language.

Overall, the use of these technologies promises to improve performance and provide new insights into mainframe data while also making the mainframe more secure, cost-effective, and accessible to IT professionals.

Mainframe transformation continues

Results of the 2024 BMC Mainframe Survey show a strong positive perception of the platform as one of growth. While compliance and security are top priorities, respondents indicate that there is work to be done to further protect the platform from threats like ransomware. The survey also shows that new technologies play a pivotal role in mainframe transformation, with organizations considering how best to utilize these technologies to drive the platform into the future while optimizing costs.

In short, the mainframe remains strong, poised to embrace new workloads while also optimizing infrastructure, tools, and processes. The BMC AMI suite covers the breadth of the mainframe software stack, and we are committed to helping organizations simplify their mainframe environments and create new levels of flexibility for the future using cloud, AI, and Gen AI technologies. To learn more about the direction of BMC AMI innovation, read the BMC AMI Platform Statement of Direction.

Download the 2024 BMC Mainframe Survey report for more detail about the current state of the mainframe and its future, including insights into the use of DevOps, AIOps, and Gen AI on the platform.

As digital transformation reshapes IT landscapes, mainframe operations must evolve to keep pace. Today’s mainframe operations teams require predictive insights to identify and resolve performance issues before they impact service delivery. With this in mind, artificial intelligence for IT operations (AIOps) can provide comprehensive visibility, helping operations ensure consistent service level agreement (SLA) compliance and cost-effective resource management. This approach drives operational efficiency, reduces costs, and maintains uptime, ensuring business continuity. By leveraging AI and automation for real-time anomaly detection, teams can proactively identify and address potential challenges in increasingly complex environments.

Next-Generation SysProgs: The backbone of modern mainframe operations

In the face of digital disruption, the next generation of systems programmers (SysProgs) must navigate complicated and complex infrastructures that demand agility and real-time response. To stay ahead, SysProgs need AIOps solutions that simplify workflows and empower them with AI-driven tools to detect anomalies and maintain resilience. This shift emphasizes intelligent automation and user-centric designs, enabling SysProgs to confidently, proactively manage mainframe operations, regardless of their experience and agility, and keep pace with the evolving demands of the digital enterprise.

Understanding “normal” and proactively detecting anomalies

Real-time anomaly detection is a key strategy for maintaining high availability and operational resilience. AIOps solutions like BMC AMI Ops Insight use AI and machine learning (ML) algorithms to establish a baseline of normal system behavior and continuously monitor for deviations. This proactive approach helps teams identify potential issues early, before they can impact mainframe performance and business operations.

The ability to detect anomalies in real time through multiple metrics allows mainframe operational teams to identify issues across various domains and ensure that nothing is missed. Unlike traditional tools that rely on predefined thresholds, the most powerful AIOps solutions use multivariate analysis, enabling more comprehensive monitoring across systems and reducing false positives.

A proactive approach to anomaly detection is essential for teams determined to stay ahead of disruptions. By identifying anomalies early, SysProgs can avoid reactive firefighting and mitigate issues before they escalate. This reduces the frequency of crisis management sessions—known as “war rooms”—and ensures that teams can focus on delivering consistent service.

Intelligent automation to simplify incident response

Automation has become a critical component of mainframe management, but today’s best practices go beyond basic task automation. High-performing teams can leverage intelligent automation driven by AIOps to resolve incidents in real time. Tools like BMC AMI Ops Monitoring and BMC AMI Ops Automation offer data centers seamless, automated remediation, enabling proactive monitoring solutions to trigger automatic responses based on defined rules. This addresses issues without manual intervention, reduces downtime, and allows SysProgs to focus on higher-value tasks.

When automation is tightly integrated with monitoring and alerting systems, the entire incident management process becomes more cohesive—teams implementing intelligent automation benefit from streamlined workflows, faster resolution times, and reduced operational overhead.

Actionable insights for faster problem resolution

In addition to early detection, teams must ensure that their AIOps monitoring tools provide actionable insights. Knowing that a problem exists is not enough—understanding its probable cause and the scope of its impact is also critical for fast and efficient resolution. Monitoring solutions that provide detailed information on severity, trends, and affected categories (such as CPU, storage, or workload) allow SysProgs to confidently address issues.

Moreover, insights should also include the current state of the system, along with projections on the critical nature of the issue. For example, by providing data on trends (such as whether the issue is improving or worsening), SysProgs can effectively prioritize responses and allocate resources where they are most needed.

Future-Proofing with AIOps and the benefits of a modern unified interface

As mainframe environments grow more complex, the ability to manage systems from a unified interface is becoming even more important. Whereas a seasoned SysProg may be able to navigate multiple legacy tools with ease, a new or less-experienced SysProg does not necessarily have the historical background, context, ability—or desire—to navigate multiple tools and possibly antiquated user interfaces. Instead, a modern, user-friendly user experience (UX) allows SysProgs, especially those less experienced, to quickly and easily access relevant data without navigating multiple tools or sign-ons. By streamlining access to AIOps-centric monitoring, automation, and insights, teams can increase productivity and reduce the likelihood of human error.

A modern, unified interface can also support collaboration across teams and departments, enabling faster decision-making. This is crucial as many organizations operate with remote and hybrid work environments. New hires, in particular, benefit from the simplified navigation and intuitive design, which helps them become productive more quickly and reduces the learning curve associated with traditional tools.

One step ahead of disruptions

Teams must also stay ahead of system disruptions to future-proof operations. Waiting for a phone call or a traditional alarm may mean it’s already too late, leading, at best, to firefighting mode, and at worst, to SLA non-compliance. Today’s rapidly evolving environments require solutions that enable teams to start at an advantage, proactively detecting problems and meeting changing business requirements.

Additionally, as experienced SysProgs retire, organizations face the loss of valuable expertise. Ensuring that new SysProgs are equipped with user-friendly, AIOps-based tools and built-in industry expertise becomes the key to minimizing the impact of these workforce changes. Modern tools can shorten the steep learning curve associated with traditional mainframe operational tools by providing solutions with built-in intelligence that are easy to use and navigate out of the box.

Explaining how proactive AIOps-centric monitoring improved their operations, a Vice President of Systems Platform Engineering at a global financial services company said, “We had a real-world issue with one of our applications where we were dropping transactions. The monitoring solution helped us drill into the handoff between IBM^® MQ and IBM^® CICS^®, allowing us to understand what was going on and fix the issue. As a result, we drove greater customer satisfaction and processed more transactions.”

Best practices for teams: Reducing cost, risk, and complexity

To maximize efficiency and reduce operational risks, organizations can follow these best practices:

1. Proactive alerts: Ensure that the monitoring solution provides proactive notifications when potential problems are identified, allowing SysProgs to act before issues escalate.
2. Multivariate analysis: Choose tools that monitor cross-domain metrics simultaneously, reducing the risk of missing critical anomalies and providing a more comprehensive view of system health.
3. Industry expertise: Look for monitoring solutions that incorporate built-in domain expertise, reduce guesswork, ensure that only relevant metrics are evaluated, and minimize MIPS consumption.
4. Ease of use: Invest in solutions that require minimal configuration and provide immediate value, allowing teams to gain insights as soon as the tool is installed.
5. Continuous learning: Choose solutions that continuously learn from data, becoming more intelligent and effective at detecting and diagnosing issues over time.

Multivariate and probable cause analysis: Finding correlations and patterns for a more comprehensive understanding

One of the most powerful solutions for staying ahead of system disruptions is BMC AMI Ops Insight, which leverages ML to continuously learn what “normal” performance looks like and detect anomalies in real time. With multivariate analysis—as opposed to traditional single-metric monitoring—the system ensures that nothing is missed by evaluating multiple key metrics simultaneously to reduce false positives.

Built-in domain expertise eliminates the need for time-consuming configuration and guesswork, making it easier for newer SysProgs to start delivering value immediately. BMC AMI Ops Insight also provides probable cause analysis, allowing teams to quickly diagnose issues and act before they escalate, ensuring higher availability and minimizing costly downtimes.

The continuous learning capability of this solution allows it to get smarter over time, adjusting to new patterns and performance profiles to offer increasingly precise monitoring and diagnostics. Connecting the dots between key metrics and alerting teams early helps avoid costly slowdowns and unplanned outages.

Conclusion: Empowering mainframe teams for the future

As mainframe environments grow more complex, detecting and resolving performance issues before they affect service is critical. By ensuring comprehensive visibility through AIOps, operations teams can maintain consistent SLA compliance, optimize resource management, and drive efficiency while reducing costs. These capabilities help safeguard uptime and ensure business continuity. Leveraging AI, automation, and real-time anomaly detection allows teams to proactively address challenges, equipping them with confidence and resilience for the future of mainframe operations.https://soundcloud.com/modernmainfra

To learn more about how organizations can take advantage of AI/ML and intelligent automation to maximize mainframe operations, listen to the podcast, “AI, Intelligent Automation, and a Future-Proof Interface for Mainframe Ops.”

The goal of BMC AMI Data for Db2^® is to provide our customers with cutting-edge innovation in data management processing to help drive their business and meet their customer demands. With the prevalence of social media use, advancements such as internet of things (IoT) and especially current artificial intelligence (AI) initiatives, unstructured data (videos, PDFs, emails, images, etc.) is forecasted to make up 80 percent of data volumes by 2025.

IBM^® Db2^® for IBM^® z/OS^® has been prepared for this explosion in unstructured data with its commitment to Db2 large objects (LOBs), a data type specifically designed to bring unstructured data into the structured relational database world.

LOBs present unique challenges to Db2 users by introducing new indexes, table types, and especially pointers into Db2. Any experienced data management professional will tell you, when you have pointers, you have problems. These problems usually present in data integrity issues, where broken pointers mean data is effectively lost!

BMC AMI LOBMaster integration

Because managing these growing LOBs has been so difficult for Db2 users, BMC AMI Data introduced BMC AMI LOBMaster for Db2^®. BMC AMI LOBMaster for Db2^® customers have seen huge reductions in the CPU usage and time required to manage growing LOB data, and enjoy the fact that during the reorg process, the integrity of unstructured data is automatically checked, ensuring regulatory and legal compliance.

Given our commitment to helping our customers’ data-driven businesses and the challenges they are facing with the explosion of unstructured data, we are happy to announce that in our recent quarterly release for July 2024, we have integrated BMC AMI LOBMaster for Db2^® into BMC AMI Reorg for Db2^®. As of this release, every customer that licenses BMC AMI Reorg for Db2^® as a standalone product or as part of a solution such as BMC AMI Utilities for Db2^® or BMC AMI Database Performance for Db2^®, will be able to manage and ensure data integrity of their Db2 LOBs automatically and efficiently with BMC AMI LOBMaster for Db2^® built in!

Proper LOB maintenance requires the database administrator (DBA) to consistently run CHECK LOB, CHECK IX, and CHECK DATA, and then run a REORG. Most DBAs find this approach impractical and simply ignore all integrity checking, putting the business in jeopardy of regulatory and legal fines. Because unstructured data is often regulatory, compliance, or legal information (contracts, support phone call recordings, emails, etc.) that is written once and typically not accessed unless a lawsuit or complaint is filed years later, companies may not discover data corruption until it is critical and too late. Now, BMC AMI Reorg with Db2^® with integrated BMC AMI LOBMaster for Db2^® consolidates all the required processing into a single, efficient, high-speed solution, leaving the data online for application processing throughout the process.

Benefits of AMI LOBMaster integration

• Replace a four-step, manually intensive process with single, automated step guaranteeing data integrity and compliance.
• Reduce write time by up to 80 percent on a 200-GB LOB through parallel technology to manage growing data volumes.
• Simplify the rollout and maintenance of new LOB applications to expand and exploit the benefits of unstructured data.
• Understand your unstructured data, including inlining information with extensive LOB reporting.

To take advantage of the newly integrated BMC AMI LOBMaster for Db2^® into your existing AMI Reorg processing, please contact your BMC account team or technical specialist.

Mainframe professionals live in exciting times. While the platform has adapted and modernized over its six decades of existence, today’s marriage of the mainframe’s power, security, and resilience with cutting edge technology is unprecedented. As organizations continue to transform their approaches to mainframe management with DevOps, AIOps, DataOps, and SecOps, integration with the cloud and the possibilities offered by artificial intelligence (AI) offer a new world of potential for the platform.

Our July release of enhancements to the BMC AMI portfolio not only includes features that will advance mainframe transformation today, but also looks toward a future of unlimited possibility.

Leveraging AI and cloud in mainframe transformation

In May 2024, we announced the public beta of Code Explain, a feature of BMC AMI DevX Code Insights that revolutionizes code explanation and documentation by providing developers with a summary of a piece of code’s function as well as business context. BMC also continues to enhance the BMC AMI portfolio with AI. BMC AMI zAdviser Enterprise includes AI-based developer productivity metrics and abend, regression, and fallback anomaly detection, as well as a monthly report of AI-generated insights based on BMC AMI DevX Code Pipeline usage data.

With a look to the future, BMC has outlined a mainframe strategy that builds upon AI-based tooling and leverages cloud technology to create a seamless, unified experience for the BMC AMI suite of solutions and AI capabilities. Combining cloud flexibility with mainframe simplicity, our new platform will offer a single access point for all BMC AMI solutions while infusing generative AI (GenAI) directly into those solutions. To learn more about this vision for the future, read John McKenny’s blog post, “BMC AMI Platform Statement of Direction: Simplify Mainframe Management with AI and Cloud.”

Regulatory compliance and digital resilience

As organizations around the world look to safeguard their data from cyberthreats and comply with regulatory standards like the European Union’s Digital Operational Resilience Act (DORA), air-gapped storage of immutable data copies has emerged as an excellent way to strengthen data security and digital resilience.

With BMC AMI Cloud Vault, users can create immutable copies of mainframe data for storage on-premises or in the cloud, send backups to air-gapped object storage, and perform standalone recovery of their data. These features not only enhance data protection, they help bring financial institutions in the E.U., and those that do business with them, into DORA compliance.

Mainframe application transformation

Enhancements to the BMC AMI DevX suite of solutions empower developers to learn from production abends and help optimize continuous integration and continuous deployment (CI/CD) pipelines.

A new report section in during testing that were present at the time the error occurred. This ability to recreate abend scenarios while testing shortens mean time to resolution (MTTR) by delivering insight into the nature of errors and enabling developers to ensure that production errors are fixed before deployment.

Developers can also retrace the steps that led to an abend while debugging in BMC AMI DevX Workbench for VS Code. This new feature gives developers a full view of a program’s execution and abend by allowing them to see each step and data input from the beginning.

Users are now able to view component versions and transfer tasks to new releases in BMC AMI DevX Code Pipeline, enabling easy organization of scopes of work by project and requirement.

Efficient mainframe data management

New capabilities help BMC AMI Data users reduce costs while increasing efficiency and database performance. New enhancements to BMC AMI Copy for Db2^® make it easy to convert from alternative solutions, and reduce CPU usage by up to 94 percent, helping customers improve recovery times with up to 16x more copies than before—at no additional cost.

The new Online Defrag Wizard in BMC AMI Data for IMS^™ provides advanced online defragmentation that is managed in a central location while allowing easy access to historical defrag activity data.

Enhanced operational resilience

With a more efficient probable cause engine and enhanced root cause analysis, BMC AMI Ops Insight enables faster diagnosis of issues and reduced mean time to repair (MTTR), leading to greater availability and uptime. These upgraded AI-based problem detection and diagnosis capabilities reduce the number of false positives, improve accuracy, and automate the processing of all detection events.

Cybersecurity risk mitigation

Increase the speed with which ransomware attacks can be detected by BMC AMI Command Center for Security with two new features in BMC AMI Datastream for IBM^® z/OS^®. New out-of-the-box settings enable security teams to flag binary values outside a normal range, alerting them to file encryptions that could indicate a ransomware attack or system compromise. A second feature brings in out-of-the-box user behavior associations, identifying and alerting about non-standard user behavior that could indicate an intentional or unintentional insider threat.

You’ve never mainframed like this before

These enhancements, part of both the BMC AMI July release and our strategic view of the future, give organizations cutting-edge tools to augment the transformation, management, and security of their mainframe systems while opening the door to new, AI-infused features that make the platform more flexible and easier to use than ever. As we move together into the future, BMC remains committed to taking your mainframe experience to new heights.

Learn about all of the features included in the July release of BMC AMI enhancements on the What’s New in Mainframe Solutions page.

In an era where digital transformation is no longer an option but a necessity, the ability to innovate and adapt rapidly while mitigating risk is a must-have for enterprises. That is why I am thrilled to share our statement of direction for the BMC AMI Platform, an industry-first cloud-native solution with generative artificial intelligence (Gen AI) currently under development. This article delves into the strategic direction and vision behind this groundbreaking platform, which aims to integrate all BMC AMI products while leveraging Gen AI capabilities to simplify mainframe transformation, enhance productivity, and accelerate innovation.

Addressing the complexity of mainframe transformation

Mainframe environments have often felt different from other platforms, creating unique challenges for innovation and skills retention. Due to their critical role in handling large-scale, mission-critical applications, innovating and transforming mainframe systems can be highly complex. These systems are often deeply integrated into an organization’s infrastructure, making changes risky and demanding. The legacy nature of many mainframe applications further complicates transformation efforts, requiring specialized skills that are becoming increasingly scarce as a significant portion of the mainframe workforce approaches retirement. According to recent statistics and client data, one-third of the mainframe workforce is set to retire in the next five years, creating an urgent need for solutions that address both innovation and skills gaps.

Transforming the mainframe for the next generation

As your organization seeks to modernize its mainframe environment, our goal is to help you preserve your existing investments and institutional knowledge while transforming the mainframe with the power of cloud and AI. This transformation aims to make mainframes as intuitive as possible for the next generation of talent. The “new mainframer” increasingly will work in a more integrated and fluid manner across the enterprise, with mainframe-specific systems programmers, as well as colleagues in other disciplines such as cloud architects, prompt engineers, operations incident managers, and machine learning (ML) operations specialists.

Cloud flexibility meets mainframe simplicity

We are committed to bringing the flexibility of cloud-native infrastructure and tooling, along with the simplicity that AI and Gen AI offer, to the mainframe platform. With this combination, you can expect to:

• Accelerate time to value and productivity: By leveraging AI to automate mainframe intelligence, new hires and consultants can quickly become productive, significantly reducing time to value and boosting overall efficiency from day one.
• Speed the development cycle with deep code understanding: Integrated Gen AI capabilities empower developers to understand, auto-generate, and test code, accelerating the development cycle and enabling faster innovation.
• Make agile business decisions with real-time insights: With real-time and actionable insights with root-cause analysis at their fingertips, IT professionals can make agile business decisions swiftly, driving innovation and maintaining a competitive advantage.
• Speed innovation with expert knowledge at the point of interaction: By providing expert knowledge precisely when and where it is needed, our platform speeds up the innovation process, allowing teams to resolve issues quickly and efficiently while fostering continuous improvement.

According to Steven Dickens, Vice President and Practice Leader at The Futurum Group, “The primary challenge with mainframe transformation lies in overcoming the evolving workforce demographics and the outdated practices that hinder this effort. Organizations that can successfully integrate AI and cloud-native capabilities into their mainframe environments will lead the next wave of digital transformation, driving unparalleled efficiency and innovation.”

Simply put, we believe that mainframe services should be utilized as simply and easily as the best cloud experiences, using commonly available skills and tools. Additionally, we believe in supercharging the productivity of developers, administrators, and infrastructure managers with integrated Gen AI services and capabilities, leveraging the vast knowledge of the mainframe community to accelerate their learning curve and guide their daily decision-making.

Simplifying mainframe management: Our vision for the industry’s first copilot for mainframe

Today, BMC AMI stands for “automated mainframe intelligence,” a suite of software solutions designed to support the vast majority of your mainframe management and help you make smarter, faster, and more confident business decisions. We are excited to introduce our statement of direction for the BMC AMI Platform, envisioned as the industry’s first mainframe copilot. This platform is designed to be the first stop for the next generation of mainframe talent to onboard, modernize, and operate using a cloud-native service catalog and AI-infused experiences with the new BMC AMI Assistant. Today, we are also announcing our managed beta program for code explain functionality in BMC AMI DevX Code Insights, which is the first example of the BMC AMI Assistant in action.

What will it look like? BMC’s approach to the future of mainframe management

Unified access to solutions

The platform will include a unified access point for all BMC AMI solutions you have licensed. A single, persona-aware management console will display the capabilities relevant to each user. Whether you prefer the robustness and privacy of an on-premise setup or the flexibility of a private cloud deployment, you will be able to use a common tool set between environments without losing functionality or context. This integration epitomizes our commitment to deliver BMC AMI services on a cloud-native platform that scales securely and deploys quickly.

Subject matter expert in a box

The BMC AMI Platform will feature the BMC AMI Assistant, a chat-based, AI-powered assistant available for developers, operators, system programmers, and IT managers to use for real-time explanations, support, and automation. Whether help is needed to debug code, understand system processes, or make informed decisions and take actions, the BMC AMI Assistant will provide expert guidance instantly, enhancing productivity and reducing downtime. Users will leverage BMC AMI Assistant Tools to capture their rich local knowledge and integrate it seamlessly into the BMC AMI Assistant.

Generative AI services infused into BMC AMI solutions

One of the standout features of our platform will be the infusion of the BMC AMI Assistant directly into our solutions, starting with the BMC AMI DevX Code Insights feature, Code Explain (currently in beta testing). This integration means no more context switching—customers can leverage powerful AI capabilities right within the products they use every day. By embedding AI services into our solutions, we ensure a smoother, more efficient user experience, enabling businesses to derive more value and insights effortlessly.

Flexible AI model integration

To accommodate the flexibility needed to support AI policies and data privacy requirements, users will be able to use BMC large language models (LLMs), integrate their own LLM, or continue using a familiar one. This means users can enhance our solution with their own organizational knowledge, ensuring that their unique business insights are effectively utilized. This feature empowers businesses to customize AI capabilities to best fit their specific needs and preferences, further exemplifying the theme of cloud flexibility meeting mainframe simplicity. Additional flexibility will be provided to allow users to host LLMs wherever needed—in the cloud or on-premise—enabling them to comply with company AI policies and keep data private.

Innovative solutions for the future

BMC’s comprehensive suite of solutions will include AI services, data services, RESTful APIs, CLIs, and SDKs. These tools are intended to empower organizations seeking mainframe transformation to access BMC AMI solutions for DevOps, operations, hybrid cloud data management, data, security, and storage management.

Our approach is designed to ensure that organizations can seamlessly integrate these solutions into their existing infrastructure, providing a consistent and unified experience across all platforms. This not only aims to simplify mainframe management, but also enables organizations to innovate and adapt rapidly to changing business needs.

Empowering the next generation of mainframe professionals

As we look to the future, our focus is on empowering the next generation of mainframe professionals. The BMC AMI Platform is being developed to enhance their mainframe experience with AI-powered guidance to ensure their impact in a rapidly evolving digital landscape.

Call to action: Embrace innovation and simplicity in your environment

The BMC AMI Platform represents a new era in mainframe management, but like any journey it cannot be taken alone. That’s why we are introducing our new Design Program, with the ability to participate in the public beta for new Gen AI features, with more features to come. Several customers have already signed up to participate, and I hope you will also consider it. To learn more, feel free to reach out to me or my team

You’ve never mainframed like this before

As we embark on this journey, we are reimagining what mainframe management can be with the industry’s first copilot for the mainframe. This will be the first stop for the next generation of mainframe talent to onboard, modernize, and operate. By blending the unparalleled reliability and performance of mainframes with the agility and innovation of cloud-native and AI technologies, we are poised to revolutionize the mainframe landscape. This is not just an evolution; it’s a bold step into a future where mainframe professionals can operate with unprecedented ease, efficiency, and effectiveness. Welcome to a new era of mainframe excellence—you’ve never mainframed like this before.