Itential focuses on building trust in AI operations through orchestration.

The latest insights from Itential emphasize the critical interplay between automation and trust in AI Operations (AIOps). Infrastructure leaders must address how to safely deploy Artificial Intelligence (AI) within their operations while maintaining a foundation of predictable systems.

The New Trust Equation

AI introduces an element of uncertainty not present in traditional automation processes. Unlike deterministic systems that yield consistent outcomes, AI's adaptive nature brings unpredictability, which presents both opportunities and challenges for operational teams.

To navigate this complexity, Itential advocates for a structured approach to AIOps led by orchestration, which enhances context, control, and confidence in AI deployment.

Why Determinism Still Matters

Establishing a reliable AI framework requires a base of deterministic workflows that ensure actions are consistent and traceable. These foundational systems allow AI to operate effectively within defined parameters.

This concept is referred to as operating AI “on rails,” where orchestration guides AI actions to ensure accountability and measurable outcomes, enhancing both innovation and safety.

An example is Lumen Technologies, which has developed over 350 orchestrations that run millions of times annually. These systems uphold a trusted environment that facilitates effective AI integration, demonstrating that AI's advancement relies on strong deterministic systems.

The Role of Orchestration in AI Trust

Orchestration plays a pivotal role in managing the interaction between automation and AI. It dictates crucial elements such as system access for AI, executive actions without human oversight, and triggers for manual intervention.

This framework of governance builds trust by enabling operations teams to maintain control, traceability, and standardization across AI activities, reinforcing orchestration as the foundation for trust in AI applications.

Building the Human Layer

Despite technological progress, human elements remain vital in cultivating trust. Organizations are focusing on training teams in NetDevOps roles that empower engineers to design intelligent orchestrations rather than rely solely on scripted solutions.

This shift toward engineering roles emphasizes ongoing innovation, moving from basic task execution to the creation of systems that incorporate human logic and oversight.

Lessons from the Field

Successful companies deploying AI reveal three patterns: they treat orchestration as an ongoing product, establish AI governance models early, and measure trust through metrics like accuracy and operator confidence rather than solely on performance indicators.

Customer Spotlight: Lumen Technologies

Lumen Technologies exemplifies the evolution towards AI integration. Faced with scaling demands, Lumen focused on building deterministic workflows, reskilling its engineers, and establishing an orchestration model that weaves together automation, data, and AI.

With over 350 orchestrations deployed, Lumen utilizes AI for predictive maintenance and action recommendation, illustrating the necessity of operational maturity to support AI initiatives. As highlighted by Greg Freeman, Vice President of Network & Customer Transformation, the focus shouldn’t be merely on AI but on enhancing the infrastructure that supports it.

This perspective underscores that AI should extend existing systems of trust rather than replace them.

The Responsible Path Forward

As AI shapes future infrastructure capabilities, the focus for organizations should not solely be on the speed of automation but rather on its thoughtful implementation through orchestration. This approach converts AI's potential into real business outcomes while ensuring reliable, intent-driven actions.

For enterprises advancing their automation strategies, developing a trust framework is essential for safe and scalable AIOps. Lumen Technologies’ experience reflects how applying these principles can pave the way for a new Edge Resource Allocator (ERA) of intelligent infrastructure.