Software delivery has reached a tipping point. As applications grow more complex and release cycles accelerate, traditional DevOps automation alone is no longer enough to keep pace with business demands. Engineering leaders are under pressure to deliver faster, improve quality, reduce risk, and demonstrate value—all at the same time. This is where an AI software delivery platform changes the game.

By embedding artificial intelligence (AI) directly into the software delivery lifecycle (SDLC), organizations can move beyond reactive DevOps toward a more predictive, automated, and outcome-driven approach. At the center of this shift is the OpenText™ Core Software Delivery Platform, which brings AI, analytics, and automation together across the entire delivery pipeline.

What is an AI software delivery platform?

An AI software delivery platform combines DevOps automation, advanced analytics, and artificial intelligence (AI) to optimize how software is planned, built, tested, secured, and released. Unlike point solutions that address a single phase of delivery, an AI software delivery platform provides end-to-end visibility across the SDLC — enabling teams to orchestrate AI DevOps workflows, reduce manual effort, and align engineering execution with business outcomes.

The role of OpenText Core Software Delivery Platform in AI-driven DevOps

OpenText Core Software Delivery Platform is designed to operationalize AI across the entire SDLC. As a unified, enterprise-grade platform, it connects planning, development, testing, security, and operations into a single system of record.

This platform-based approach enables consistent DevOps automation, shared intelligence across teams, and real-time value stream management—without fragmenting tools or workflows.

And with built-in analytics and delivery insights, the platform supports continuous value stream management, helping leaders understand flow, bottlenecks, and delivery risk across the SDLC.

How AI enhances every stage of the SDLC

AI-driven planning and prioritization

AI analyzes historical delivery data, backlog trends, and performance metrics to help teams:

• Forecast delivery timelines more accurately
• Identify bottlenecks before work begins
• Prioritize features based on risk, effort, and impact

Smarter CI/CD and automation

AI improves CI/CD pipelines by

• Identifying patterns behind failed builds and deployments.
• Predicting pipeline slowdowns or instability.
• Optimizing automation for speed and reliability.

These capabilities enable intelligent AI DevOps workflows that adapt based on delivery signals, which means you can improve speed and reliability without sacrificing governance.

AI-enhanced quality and testing

Quality is one of the most powerful applications of AI in software delivery.

With DevOps Aviator, teams can

• Automatically generate and optimize test cases.
• Accelerate regression testing without sacrificing coverage.
• Identify defects and root causes earlier in the SDLC.

Security and risk management with AI

AI enables proactive DevSecOps by

• Detecting vulnerabilities and anomalies earlier.
• Prioritizing risks based on business impact.
• Reducing false positives that slow development teams.

The business benefits of AI-powered software delivery

Organizations adopting AI-powered platforms consistently achieve

• Faster time to market.
• Higher software quality.
• Reduced delivery risk.
• Improved developer productivity.
• Better alignment between IT and business leaders.

Why platform-based AI matters more than point solutions

A platform-based approach ensures AI insights are shared, contextual, and actionable across teams.

When combined with AI innovations like DevOps Aviator, organizations can scale AI adoption without creating new silos.

The future of software delivery is AI-driven

AI-powered software delivery platforms represent the next evolution of DevOps—where intelligence, automation, and visibility are built in by design.

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