WIRE: Transforming Work Instruction Quality Through AI

The Work Instruction Review Engine (WIRE) was created as part of a broader AI initiative focused on improving operational effectiveness and compliance across TRIGO . During the Operation AutonomIQ initiative WIRE was introduced as an example of how AI-powered tools can be used to improve the robustness and compliance of work instructions while saving valuable time for operational teams.

Before WIRE, the quality of work instructions often depended on the experience and perspective of the individual reviewing them. WIRE was designed to provide a structured and repeatable review process that evaluates work instructions against established best practices and identifies gaps that could impact quality performance. Evidence from WIRE reviews shows a strong focus on improving acceptance criteria, inspection sequencing, visual standards, reaction plans, traceability, and defect containment processes.

A common challenge in the field is ensuring that work instructions are clear, complete, and capable of producing consistent inspection results regardless of who performs the work. WIRE addresses this challenge by systematically identifying weaknesses such as:

• Missing acceptance criteria.
• Lack of good-versus-bad visual examples.
• Undefined inspection sequences.
• Weak reaction plans for non-conforming material.
• Incomplete traceability requirements.
• Ambiguous wording that can lead to inconsistent interpretation.

By highlighting these issues automatically, WIRE helps sites strengthen their work instructions before those weaknesses result in defects, escapes, or audit findings.

WIRE is used by uploading a work instruction for review, after which the engine assesses the document and provides detailed improvement recommendations. A user demonstration showed the tool reviewing and scoring a work instruction while generating recommendations for improvement. Feedback from field users focused on refining scoring logic, recommendation accuracy, and alignment with standard work instruction formats, demonstrating active use and continuous improvement of the tool.

The reviews generated by WIRE are highly detailed and provide practical guidance that can be immediately applied by operational teams. Examples include recommending measurable acceptance criteria, improved visual standards, defined inspection flows, enhanced containment requirements, and stronger documentation controls.

Impact on the Organization

WIRE has become more than a simple review tool; it has served as a proof point for the organization’s AI strategy. During the Operation AutonomIQ meeting, Charles Atkins, TRIGO Canada Country Manager, described WIRE as “a tool that increases compliance and improves the robustness of work instructions while making operations more effective and efficient”. The success of WIRE helped demonstrate the potential value of AI agents and contributed to broader plans for additional specialized operational tools.

The tool has also fostered a culture of continuous improvement. Feedback channels were established specifically to gather all type of feedback from users, allowing recommendations and scoring models to be refined over time. Charles Atkins emphasized that WIRE would evolve continuously as teams learned from real-world usage and incorporated user feedback.

WIRE was created to solve a fundamental operational challenge: ensuring work instructions are clear, complete, and consistently effective. By automating expert-level reviews and providing actionable recommendations, WIRE helps strengthen compliance, improve inspection consistency, reduce risk, and support continuous improvement across the organization. Its success has demonstrated how practical AI solutions can deliver measurable value while helping teams work smarter, faster, and with greater confidence.