Machine Learning

How would you best describe your organization's current software delivery environment(s) on mainframe computers? (Select all that apply)(Required)

Primarily manual or legacy delivery processes

Automated CI/CD in limited areas

Hybrid environment with multiple delivery platforms and toolchains

Mostly standardized CI/CD platform

Intelligent, governed software delivery platform

My organization does not utilize mainframes

Not sure / don't know

In which areas of your mainframe software delivery environment are you currently using AI? (Select all that apply)(Required)

Code generation / developer assistance

Automated testing / test generation

Build and pipeline optimization

Deployment automation

Monitoring and incident response

Security / compliance automation

Other

We are not currently using AI in our environment today

As software delivery responsibilities expand beyond traditional build, test, and deploy, which of the following areas is the most challenging for your organization today with respect to mainframe software delivery? (Select one)(Required)

Integrating security throughout the software delivery lifecycle

Meeting governance, audit, or compliance requirements

Managing software supply chain integrity and visibility

Operationalizing AI across software delivery workflows

Coordinating software delivery across diverse tools, teams, and environments

Other

None of these are significant challenges

Not sure / don't know

Which of the following do you expect is most likely to accelerate your organization's mainframe software delivery progress over the next 12-18 months? (Select one)(Required)

Greater automation across the software delivery lifecycle

Broader use of AI-assisted software delivery workflows

Stronger governance, policy, and compliance automation

Improved software supply chain visibility

Better integration across software delivery tools and platforms

Greater standardization across development teams

Other

No significant changes are planned

Not sure / don't know

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