Shifting Perspectives: AI on the Mainframe Moves Towards Trusted Operations

Trust in AI on the Mainframe: A New Era of Operational Confidence

In a recent survey conducted by BMC, a leading automation company for the AI era, it has been revealed that the landscape of artificial intelligence (AI) on mainframes is evolving. No longer limited to experimentation, organizations are now focusing on operationalizing AI while emphasizing trust, governance, and tangible business results. This marks a significant transition in how enterprises perceive and utilize AI technologies on their mainframe systems.

Key Survey Findings

The 2026 BMC Mainframe Survey, which surveyed over 1,300 mainframe practitioners and decision-makers worldwide, uncovered some fascinating insights. One notable highlight from the survey is the overwhelming confidence in the mainframe system itself. A staggering 94% of respondents expressed continued faith in the mainframe as they scale AI implementations, showcasing a long-term commitment to investing in these robust systems.

Furthermore, it appears that mainframe professionals are increasingly embracing generative AI tools. These tools are being used primarily to recommend actions rather than execute them autonomously, showcasing a careful and measured approach to AI adoption. In fact, 45% of survey respondents identified the implementation of AI technologies as a top priority within their organizations.

AI as a Trusted Advisor

A notable trend emerging from the survey is the shift towards viewing AI as an advisor rather than an executor. While 40% of respondents were comfortable allowing AI to suggest code-management actions, only 23% felt secure enough to let AI complete those actions independently. This cautious realism reflects a growing desire among mainframe practitioners to retain human oversight to ensure reliability and accuracy in critical business processes.

Additionally, interest in having AI recommend actions for database reorganizations has increased, with 43% of respondents expressing a willingness for AI to provide suggestions, compared to 37% in the previous year. However, only 21% were comfortable with AI fully executing those recommendations.

Growth in AI Use Cases

The survey also highlighted that enterprises are exploring various use cases for AI on mainframes, focusing on areas that enhance productivity and optimize operations. Key initiatives prioritized by organizations include performance tuning, problem detection, database reorganizations, Integrated Management Systems (IMS) queue management, and documentation generation. This diverse range of applications indicates that businesses are serious about leveraging AI to modernize and streamline their operations.

Implementation Challenges

Despite the optimism surrounding AI's role in mainframe operations, several implementation challenges remain. Respondents cited considerable concerns, including 41% highlighting high implementation costs, 39% pointing to security and privacy issues, and 37% addressing difficulties with data integration. Regulatory and compliance challenges also loom large, affecting 22% of respondents. Such hurdles must be navigated carefully to ensure successful AI integration.

Future of Mainframe Management

BMC's survey indicated that a significant investment strategy emerging within the field is the development of agentic mainframe management. About 36% of respondents are planning to invest in creating agents specifically designed to manage mainframe operations, while 32% intend to invest in third-party agents that can assist in this process.

In addition, the survey brings attention to evolving requirements around digital certificates. With a mandate to reduce the standard digital TLS certificate lifecycle by 88% by 2029, organizations may face potential disruptions if proper management strategies are not established. Currently, 43% of respondents utilize in-house automated solutions for certificate management, while 31% utilize product-based solutions, and 25% still rely on manual processes.

Conclusion

John McKenny, Senior Vice President at BMC, stated, “Our latest mainframe survey shows an industry moving beyond AI experimentation toward trusted, operational adoption.” It's increasingly clear that organizations are evolving, prioritizing trust and governance in AI implementation while allowing humans to remain actively involved in overseeing AI recommendations. This careful approach underlines the path toward greater AI autonomy on the mainframe and signifies an exciting era for enterprises in embracing AI.

To read more about the findings from the 2026 BMC Mainframe Survey, view the full report here and join the upcoming webinar on September 23, 2026, for deeper insights into these imperative trends.