Many companies are starting to use AI to improve their old mainframe computer systems, and even more are planning to do so. Mainframes have been around for 60 years. They weren’t originally made for AI, but businesses see their value. A study by Kyndryl found that 86% of business and IT leaders are already using AI on their mainframes or planning to. Also, 71% are using AI to help update and modernize these systems.
This is a new trend, but companies are realizing they don’t need to replace their mainframes just because AI is changing how computing works. Petra Goude from Kyndryl says many businesses want to connect their important data stored on mainframes with AI tools. Some companies even want to use AI to get useful insights from this data.
There are two ways to do this. One way is to move the data to AI systems, which usually run in the cloud. The other way is to bring AI systems to the mainframe, where the data is already stored. Goude believes companies will use both methods.
AI is also helping businesses modernize their mainframes in other ways. It can make it easier to move some tasks to the cloud, update old programming code, and train employees to work with modern technology. Many companies are choosing a mix—keeping some important tasks on the mainframe while moving others to the cloud.
Goude says more business leaders now understand the benefit of using both cloud and mainframe systems together instead of picking only one. The goal is to put the right tasks on the right system.
Lisa Dyer from Ensono, a company that helps businesses manage their mainframes, says AI is playing a big role in modernization. Many companies want to use AI to improve or update their mainframe code. AI can write small pieces of new code, translate old programming languages like COBOL into modern ones like Java, and help developers maintain systems.
Chris Dukich, CEO of Display Now, has also seen companies use AI to make mainframe upgrades easier. AI can handle complex tasks like rewriting code or replacing databases. This makes the entire process faster and simpler.
Some companies are even running AI directly on their mainframes instead of moving data to another system. Many businesses store their most important data on mainframes, so it makes sense to run AI there instead of transferring data to less secure or less reliable systems. Keeping AI close to the data improves speed and efficiency.
Dukich says mainframes remain valuable because they are reliable, secure, and scalable. AI is helping businesses make better use of them, especially when handling large amounts of data for decision-making and analytics. Many organizations see AI as the key to unlocking even more potential from their existing mainframes.
AI is making things easier for companies by handling tasks that were once complicated and time-consuming. Businesses no longer have to manually rewrite old code or spend months upgrading their mainframe systems. AI can analyze data, suggest improvements, and even perform some updates automatically. This helps companies save time and money.
Another big advantage of AI is that it can help businesses understand their data better. Mainframes store huge amounts of important data, but it’s often difficult to access or analyze. AI can quickly process this data and find patterns that humans might miss. This can help businesses make better decisions, improve customer service, and find new opportunities for growth.
Some companies are using AI to improve security on their mainframes. AI can detect unusual activity, prevent cyberattacks, and protect sensitive information. Since mainframes store critical data, keeping them secure is a top priority. AI can analyze security threats in real time and respond faster than human teams.
Training employees to work with mainframes has also become easier with AI. Many IT workers today are more familiar with cloud computing and modern programming languages. AI can help bridge this gap by assisting with training, translating old code, and making mainframe systems easier to work with. This is important because many businesses still rely on mainframes for their core operations.
Even though AI is making modernization easier, companies still face challenges. One challenge is deciding which workloads should stay on the mainframe and which should move to the cloud. Some tasks require the security and reliability of a mainframe, while others work better in a flexible cloud environment. AI can help analyze these needs and recommend the best approach.
Another challenge is ensuring that AI models work well with mainframe data. Some businesses may need to upgrade their hardware or software to support AI applications. Others may need to train their teams to work with AI-powered tools. However, these challenges are not stopping companies from moving forward with AI adoption.
In the future, we may see even more businesses using AI on their mainframes. As technology improves, AI will become even better at handling complex tasks, analyzing data, and helping businesses operate more efficiently. Companies that invest in AI now may gain a competitive edge in their industries.
Mainframes have been around for a long time, and they are not going away anytime soon. Instead of replacing them, companies are finding new ways to improve them with AI. By combining the power of AI with the reliability of mainframes, businesses can modernize their systems while keeping their critical data secure and accessible.
As AI continues to evolve, we can expect even more innovative solutions for mainframe modernization. Whether it’s helping businesses move to the cloud, updating old code, or improving security, AI is changing the way companies use mainframes. The future of mainframes and AI looks bright, with many exciting possibilities ahead.
