Why Preserving Operational Intelligence Matters More Than Ever
The future of IBM Z increasingly depends on the success of the people who are new to the platform.
The IBM Z community has done an extraordinary job creating pathways for the next generation of professionals through university programs, apprenticeships, New to Z initiatives, and community-driven education. New professionals are bringing fresh perspectives, modern development skills, AI expertise, and new ways of thinking to one of the world’s most important enterprise computing platforms.
This investment could not come at a better time.
IBM’s Institute for Business Value reports that the mainframe continues to process approximately 70 percent of the world’s transactions by value, while organizations increasingly look to IBM Z as a platform for AI, digital transformation, and hybrid cloud initiatives. The platform remains one of the most important engines of business processing in the world, and its continued success depends upon developing and empowering the next generation of talent.
The industry has rightly focused on building new skills. However, another challenge deserves equal attention. Organizations must ensure that decades of operational knowledge, business context, and practical experience are preserved and made available to the professionals who will lead the platform into the future.
Organizations are not simply transitioning people. They are transitioning knowledge.
A Generational Opportunity and a Generational Transition
The influx of new professionals into the IBM Z ecosystem represents one of the greatest opportunities for the future of the platform. New professionals bring curiosity, new experiences, and a willingness to challenge assumptions and embrace emerging technologies. They also bring experience with automation, AI, APIs, and modern development practices that can help shape the next era of IBM Z.
At the same time, organizations are experiencing a generational transition that extends far beyond staffing.
Experienced IBM Z practitioners often carry decades of operational knowledge that is difficult to document and even harder to replace. They understand which business processes are critical, which procedures have been tested, which dependencies matter, and which recovery steps have proven effective during real-world events. They understand the history of the environment and the reasons why systems, applications, and operational procedures evolved the way they did.
KPMG has identified the shrinking pool of professionals skilled in legacy technologies as a significant challenge, noting that mainframe environments often serve as central hubs for highly interdependent systems and applications. Deloitte has similarly observed that organizations continue to face growing operational complexity and the need to balance modernization with risk reduction.
The good news is that this challenge is manageable.
Organizations are not starting from scratch. Modern software, operational intelligence, automation, and AI-assisted capabilities provide opportunities to capture, preserve, and make institutional knowledge more accessible than ever before.
The challenge is therefore not whether this transition can be managed. The challenge is whether organizations are willing to invest in the people, tools, and capabilities that enable the next generation to succeed.
The challenge is not simply learning IBM Z. The challenge is understanding how the business operates on IBM Z.
The Knowledge That Rarely Gets Documented
Most organizations have documentation. Some of it is excellent. Some of it is current. Some of it is useful during planning exercises. However, the most valuable operational knowledge is often much harder to capture.
It exists in application dependencies, business processes, recovery procedures, operational practices, historical decisions, and the experience of people who have seen the environment fail and recover. The people who have supported these environments for decades often know why a process exists, why an exception was created, which procedures can be safely modified, which business services are most critical, how applications depend on one another, and what must happen first when change or recovery becomes necessary.
This knowledge is rarely documented in a way that can be easily consumed by new teams. During an operational event, these individuals often become the most valuable people in the room because they understand not only the technology, but also the business context surrounding it.
The challenge for organizations is therefore much larger than a traditional skills gap. It is an opportunity to preserve and operationalize institutional knowledge before it disappears.
Why AI Makes This More Important, Not Less
Artificial intelligence is rapidly becoming part of the IBM Z conversation.
IBM’s Institute for Business Value found that 78 percent of surveyed IT executives are piloting or operationalizing AI capabilities in mainframe applications and transactions, while 74 percent are integrating AI into mainframe operations to enhance system management and maintenance. Additionally, 61 percent believe generative AI is important to their application modernization strategies.
These findings demonstrate that the platform continues to evolve and remains central to many organizations’ future strategies.
However, AI does not eliminate the need for operational knowledge. It amplifies its importance.
AI can accelerate learning, summarize information, identify patterns, and improve productivity. However, AI still depends upon trusted data, accurate context, and operational understanding. KPMG notes that generative AI can accelerate activities such as code discovery, dependency analysis, documentation, and modernization, while also cautioning that AI-generated information still requires validation, governance, and human oversight.
In many ways, AI is only as effective as the operational intelligence that supports it. If knowledge remains trapped in documents, spreadsheets, or the minds of a few experienced practitioners, AI has little foundation from which to reason effectively.
Modern software and operational intelligence capabilities can help address this challenge by making relationships, dependencies, historical knowledge, and operational context visible and consumable. They provide the trusted information that both people and AI require to make better decisions.
As IBM Senior Vice President and Chief Commercial Officer Rob Thomas has emphasized, organizations should assume disruption will occur and focus on resilience, trusted recovery capabilities, and business continuity. In an AI-driven world, the question becomes even more important:
Can we trust the data and operational intelligence on which our business and AI systems depend?
Strong operational resilience and operational intelligence are becoming prerequisites for successful AI adoption.
Operational Knowledge Is a Strategic Asset
When experienced professionals retire, organizations do not simply lose technical expertise. They often lose the knowledge that explains how applications, business processes, and operational procedures work together.
That knowledge becomes critically important during periods of change.
Organizations need it to:
· accelerate onboarding of new professionals;
· reduce operational risk;
· recover critical business services;
· modernize applications;
· integrate AI capabilities;
· improve confidence in decision-making.
The same questions repeatedly emerge during resiliency initiatives and modernization efforts:
· How are applications connected?
· Which business processes depend on one another?
· What is the impact of change?
· What operational procedures are critical?
· Which services are most important to the business?
These are not simply technology questions.
They are questions about institutional knowledge and operational understanding.
The challenge is not simply learning IBM Z. The challenge is understanding how the business operates on IBM Z.
Why Operational Intelligence Matters
Operational intelligence helps organizations preserve and expose the knowledge that allows critical business services to operate, recover, and evolve. It provides context around how applications, processes, and information are related and makes years of operational experience available to new teams. This is particularly important for organizations investing in New to Z initiatives because new professionals need more than technical skills. They need context and a deeper understanding of how the business operates and how critical services depend on one another.
Operational intelligence does not replace experienced professionals. It amplifies them by helping capture what they know, validate how the environment operates, and make that knowledge available to the next generation. The value of this knowledge extends far beyond resiliency. The same information that helps organizations recover critical business services is often the information required to modernize them successfully.
Effective modernization initiatives require organizations to understand how applications, processes, and data are connected. They require an understanding of dependencies, business context, operational workflows, and the potential impact of change. Without this knowledge, modernization initiatives carry significantly greater risk. This is one of the reasons that operational intelligence is becoming increasingly strategic. The information that improves resiliency also creates the foundation for modernization, AI adoption, skills transfer, and the continued strength and growth of the platform.
As organizations invest in the next generation of IBM Z professionals, preserving operational knowledge becomes an opportunity rather than simply a risk mitigation exercise. Organizations now have access to capabilities that can help make operational knowledge more visible, easier to understand, and more accessible to new teams. These investments can reduce onboarding challenges, accelerate modernization initiatives, strengthen resiliency, and improve confidence during operational events.
Investing in the next generation therefore means more than hiring and training. It also means equipping those professionals with the tools and capabilities they need to succeed.
The Question That Matters
For years, the New to Z conversation has focused on an important question:
How do we bring new talent to IBM Z?
That question remains essential. However, another question may become equally important:
How do we preserve the knowledge required to operate, recover, and evolve the business?
The answer cannot depend solely on documentation, training, or the availability of a few experienced individuals during a crisis. Organizations need ways to make operational knowledge visible, repeatable, validated, and usable by new teams. The future of IBM Z depends not only on attracting and developing new talent, but also on preserving the knowledge that allows critical business services to continue operating, recover, and evolve.
New professionals will bring new skills, new ideas, and new approaches to the platform. Their success, however, will increasingly depend on their ability to access and understand decades of operational experience that might otherwise disappear as experienced practitioners retire. The challenge facing organizations is therefore much larger than a skills transition. It is a knowledge transition that will significantly influence resiliency, modernization, and the future growth of the platform.
Fortunately, organizations have more opportunities than ever to address this challenge. Modern software, operational intelligence, and AI-assisted capabilities can help capture knowledge, improve visibility, accelerate learning, and make decades of institutional experience available to the next generation. The organizations that thrive in the coming decade will not necessarily be those with the largest teams or the deepest institutional memory. They will be the organizations willing to invest in the people, tools, and capabilities that enable new professionals to succeed.
Technology alone will not solve the knowledge challenge. However, when combined with experienced professionals and intentional knowledge preservation, modern tooling can help transform institutional knowledge from something that is fragile and difficult to transfer into something that is visible, accessible, and actionable.
Organizations are not simply losing people. They are being given an opportunity to preserve knowledge, operationalize experience, and better prepare the next generation for the future of IBM Z.
References
IBM Institute for Business Value. AI Drives Mainframe Innovation.
IBM Newsroom. New IBM Institute for Business Value Study Shows AI Driving Mainframe Innovation.
KPMG. From Legacy to Leading: Revolutionizing the Mainframe for the Digital Age.
Deloitte. Mainframe Modernization: The AI-Human Synergy.
IBM. Rob Thomas thought leadership on resilience, trusted AI, and business continuity.
Research on workforce transition, institutional knowledge preservation, and operational resilience.