Using AI to Identify Communication Failures That Led to Near-Miss Incidents

Overview

In high-stakes environments such as rail, aviation, and healthcare, effective communication is critical to safety and operational efficiency. However, communication failures can lead to near-miss incidents, posing significant risks to personnel and operations. Traditional methods of monitoring and evaluating safety-critical communications often fall short, leaving organizations vulnerable to compliance issues and safety breaches. This is where artificial intelligence (AI) can play a transformative role. By leveraging AI, organizations can identify communication failures in real-time, ensuring adherence to protocols and enhancing safety measures. In this post, we will explore how AI can be utilized to detect communication failures that contribute to near-miss incidents, the implementation process, and the practical value it provides.

The Safety Critical Communications Challenge

Communication failures in safety-critical environments can stem from various factors, including protocol non-adherence, ambiguous language, and delayed feedback. The stakes are high: regulatory compliance, safety incident prevention, and audit readiness are all at risk when communication is not effectively monitored.

The Manual Review Problem:

• Traditional SCC Monitoring: Supervisors typically rely on manual reviews of a small sample of calls, often leading to retrospective checks that uncover issues weeks or months later. This approach lacks visibility into contractor and subcontractor communications, resulting in overwhelming compliance documentation.

• Scalability Crisis: Consider a scenario with 500 workers making 50 calls each day, resulting in 25,000 calls daily. A manual review might cover only 1-2% of these calls, leaving over 98% of communications unmonitored and invisible, especially in distributed contractor settings.

• Regulatory Pressure: With the introduction of standards like Network Rail's NR/L3/OPS/301, organizations face strict compliance requirements, including mandatory call recordings and documentation of protocol adherence. The deadline for compliance is March 2026, emphasizing the urgency for organizations to adopt more effective monitoring solutions.

How AI Call Recording Analysis Works

AI offers a systematic approach to analyzing safety-critical communications, addressing the shortcomings of traditional monitoring methods. The AI pipeline consists of several key steps:

Step 1: Call Recording Capture
Voice recordings from various sources, including mobile, VoIP, and control room communications, are stored in a retrievable format. This ensures comprehensive coverage of all safety-critical communications.

Step 2: Speech-to-Text Transcription
AI converts audio recordings into text with over 95% accuracy, recognizing industry-specific terminology and ensuring that multi-speaker interactions are accurately captured.

Step 3: Protocol Analysis
The AI analyzes transcripts against established safety-critical communication protocols, detecting issues such as:

• Errors in phonetic alphabet usage
• Non-compliance with repeat-back requirements
• Ambiguous language or unclear confirmations

Step 4: Scoring & Flagging
The system generates an overall compliance score and flags specific protocol violations. This scoring system allows organizations to classify risks and identify training needs.

Step 5: Insights & Reporting
AI provides actionable insights through dashboards that visualize worker performance, compliance trends, and training recommendations. This data-driven approach enables organizations to proactively address communication gaps.

Implementation & Integration

To effectively implement AI for identifying communication failures, organizations must follow a structured process:

Preparation:

• Define the scope of communications to be recorded, including internal staff and contractors.
• Assess current communication systems and identify gaps in compliance.

Execution:

• Integrate AI-powered call recording solutions that are compatible with various devices, including BYOD setups.
• Configure the AI system to analyze communications based on established protocols.

Evaluation:

• Monitor the effectiveness of the AI system in identifying communication failures.
• Collect feedback from users and stakeholders to assess the impact on safety and compliance.

Iteration & Improvement:

• Continuously refine the AI algorithms based on new data and insights.
• Regularly update training programs to address identified gaps in communication skills.

By following this structured approach, organizations can successfully leverage AI to enhance communication monitoring, ensuring compliance and improving safety outcomes.

Practical Value & Use Cases

The implementation of AI in monitoring safety-critical communications offers numerous practical benefits:

• Protocol Failure Detection: AI can swiftly identify critical failures, such as missing phonetic alphabet usage or lack of repeat-backs on safety instructions. Traditional methods may take weeks to uncover these issues, while AI provides insights within hours.

• Workforce Monitoring at Scale: With AI, organizations can monitor 100% of recorded calls, providing continuous oversight of every worker’s communication. This visibility allows for targeted training interventions based on specific performance metrics.

• Incident Investigation: In the event of a near-miss incident, AI enables rapid retrieval of relevant call recordings, allowing for immediate analysis and documentation. This capability significantly reduces the time required for investigations and enhances compliance readiness.

• Training & Coaching: AI-driven insights facilitate targeted coaching for individuals and teams, moving from reactive training to proactive skill development. Organizations can implement tailored training programs based on identified gaps, ensuring that workers are equipped with the necessary communication skills.

By adopting AI for communication monitoring, organizations not only enhance safety and compliance but also foster a culture of continuous improvement in communication practices. This strategic approach ultimately leads to better operational outcomes and a safer working environment.