Voice AI Implementation: Technical Requirements and Common Concerns

Why Voice AI Raises Immediate Skepticism 

Voice AI triggers stronger reactions than other forms of automation. Email automation feels familiar. Workflow automation feels invisible. Voice feels personal. 

Executives worry about customer perception, call quality, accuracy, and loss of control. These concerns are valid. They are also often based on outdated assumptions. 

The Actual Technical Requirements 

Voice AI does not require advanced infrastructure. 

Core requirements include: 

• ERP API access for reading and updating records 

• Accurate contact data for customers or vendors 

• Defined rules for when calls are initiated 

• Escalation paths to humans 

No custom telephony infrastructure is required. Modern platforms handle call routing, transcription, and logging. 

Data Quality Reality 

Perfect data is not required. Adequate data is. 

Phone numbers must be current for a majority of accounts. Call success rates above 60 percent are sufficient for ROI. Missed or invalid contacts are logged and escalated. 

Voice AI does not replace data hygiene efforts. It exposes gaps faster. 

Accuracy and Control 

Voice AI does not improvise business decisions. 

It follows predefined scripts and rules. It escalates when conditions fall outside defined parameters. It does not negotiate pricing or make discretionary commitments. 

Control is higher than manual processes, not lower. 

Customer Acceptance Concerns 

Customer acceptance is contextual. 

Acceptance is high when: 

• Calls are informational 

• Tone is professional 

• Escalation to humans is available 

Acceptance is lower when: 

• Conversations are emotionally sensitive 

• Negotiation is required 

• Relationship nuance dominates 

Implementation success depends on selecting appropriate use cases. 

Monitoring and Oversight 

Voice AI requires oversight, not micromanagement. 

Calls are logged. Transcripts are available. Outcomes are measurable. Adjustments are iterative. 

The system improves through refinement, not retraining. 

The Reality 

Voice AI is not experimental. It is operational technology when applied to the right processes. 

The primary risk is not technology failure. It is poor use case selection. 

About the Author 

This content is published by ERP AI Agent, a consulting practice specializing in AI agents for mid-market ERP exception processes. 

Published: January 2025 

Last Updated: January 2025 

Reading Time: 6 minutes