Itential highlights orchestration's role in effective AI integration.

Recent insights from Itential highlight that enterprise leaders are increasingly considering Artificial Intelligence (AI) within automation strategies, though many report slower progress than anticipated. This stagnation is linked not to a lack of ambition but to challenges in achieving full orchestration of automation efforts.

Overview of Current Automation Challenges

Many organizations have invested substantially in automation through scripts and bots, but these efforts often lack the necessary integration for broader operational effectiveness. Without a unified orchestration framework, automation remains fragmented, preventing organizations from reaping comprehensive benefits.

Lumen Technologies' Approach

Lumen Technologies faced a similar challenge five years ago, as described by Greg Freeman, Vice President of Network and Customer Transformation at Lumen. The company determined that merely increasing the number of scripts would not suffice and opted instead for a consolidated orchestration layer to integrate automation and AI.

Transitioning to Machine-Automation

Freeman's team restructured their operations to ensure that 80 percent of network interactions were machine-to-machine, allowing for greater scalability without additional human resources. This collective shift in focus sought to enable a streamlined operational model.

Establishing a Solid AI Foundation

Before incorporating AI, Lumen dedicated time to develop a base of 350 deterministic workflows, which now serve as the backbone for their operations. This fundamental preparation is vital, as integrating AI directly without the necessary structures can lead to inefficiencies.

Utilizing a Model Context Protocol

Additionally, Lumen employs Model Context Protocol (MCP) to connect AI and orchestrated operations effectively. This facilitates a modular connection that allows AI to engage with workflows, ensuring that actions are both automated and reliable.

Conclusion and Recommendations

Current findings suggest that orchestration is vital for maximizing AI initiatives. Organizations aiming to incorporate AI should first solidify their orchestration infrastructure, ensuring that operational processes are mapped, automated, and interconnected to optimize outcomes effectively. This foundational approach can transform AI from a concept into a practical asset that enhances business functionality.