Every era of software delivery has been defined by its people. Now, it is defined by its teams: human and digital. OpenText DevOps Cloud is leading a shift from fragmented toolchains to coordinated execution by autonomous agents. These are not copilots or chat overlays. They are digital workers: policy-aware, outcome-driven AI agents embedded directly into the delivery lifecycle. They do not wait for instructions, and they act with purpose.

Digital workers represent a new operational reality. They execute work across testing, planning, compliance, and performance engineering without relying on human prompts. This is agentic AI by design: autonomous, policy-driven agents that pursue delivery goals within enterprise constraints. This approach moves us beyond the outdated model of DevOps with AI bolted on and into a fundamentally new delivery system where AI becomes a true contributor on the team.

Beyond assistance: Autonomous execution

The first generation of enterprise AI focused on lightweight assistance—code suggestions, summarization, knowledge retrieval. Helpful, but limited. Digital workers go much further. They are proactive and deeply embedded in delivery operations, governed by enterprise policies, activated by real-time telemetry, and integrated with systems of record. At OpenText, we moved deliberately past the copilot metaphor because we believe the moment demands more rigor, more responsibility, and more autonomy.

For the first time, AI is not just helping someone write code. It is generating the tests, validating the policies, and determining when to ship.

The Knowledge Expert System: AI that operates, not just suggests

This shift is powered by a purpose-built architecture called the Knowledge Expert System. In this architecture, when something changes, whether it is a code commit, a new ticket, or a policy update, the system triggers a response. It activates the appropriate agent, pulls context from across the SDLC, evaluates permissions based on identity and policy, and then executes. This orchestration layer blends generative reasoning with deterministic control, enabling digital workers to act safely and effectively at enterprise scale.

Digital workers are grounded in a multi-context protocol that combines real-time telemetry, delivery metadata, policy rules, and user activity. This allows them to make decisions in motion and adjust based on what is happening in the broader delivery environment. They do not require repetitive input' they do not lose context; and they learn continuously and act intentionally.

Enterprise proven and field-tested digital workers

This is not theoretical. We have deployed it at scale, and we run our business on it. In fact, more than 7,000 engineers use DevOps Cloud every day at OpenText. We replaced Jira, unified our planning, testing, and release workflows, and embedded digital workers across teams to manage quality, enforce compliance, and drive continuous improvement. Every product shipped on schedule with no trade-off in quality.

What our customers are doing with it

We are not alone in this. Our customers are already seeing results. For example, at Kellanova, digital workers helped manage testing and governance across 700 applications during a major global spin-off. At DATEV, performance testing coverage increased by a factor of 17, transforming what was once a bottleneck into a fully self-service capability. Financial institutions are using digital workers to adapt to shifting policies and automate compliance verification across pipelines in real time.

Digital workers empower developers, not replace them

This is not about replacing developers. It is about removing the friction that slows them down.

Digital workers handle the repetitive, the traceable, and the governable. They generate test coverage as features are built, align release gates to enterprise risk posture, and automate audit readiness. In this way, digital workers close the gap between what was built and what was intended to ensure confidence at every stage of delivery.

With that burden lifted, developers stay focused on architecture, business logic, and user impact.

Defining a new category: The digital worker platform

This shift is significant enough to warrant a new category: the Digital Worker Platform. These new platforms are not overlays, and they don't just augment a single team or sit idle until prompted. They are embedded into the workflow, drawing from telemetry and multiple context sources to continuously act on behalf of delivery goals.

OpenText DevOps Cloud is the first of its kind: it's a platform where digital workers actively contribute across planning, testing, release, and compliance, not beside the work but inside it.

What comes next

And this is just the beginning. In the next 12 to 18 months, we expect to see

• Fully autonomous pipelines with minimal human handoffs.
• Risk-aware orchestration that continuously adapts.
• Domain-specific agents trained on enterprise delivery patterns.
• Intelligent feedback loops that drive optimization in real time.

This is not just the next chapter. It is a new model, one that moves the industry forward.

Others will try to bolt AI onto outdated architectures. We have built something different: an operational foundation where digital workers are governed, secure, trusted, and continuously evolving.

The age of intelligent execution has arrived. Your next teammate is not a person. It is a digital worker. AI should not just assist—it should deliver.

This is the future we are already living. See what it looks like with OpenText DevOps Aviator.

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