Voice AI

What is Voice AI?

Voice AI refers to artificial intelligence systems that can understand and respond to spoken language, enabling natural voice conversations between humans and computers. In drive-thru applications, Voice AI combines automatic speech recognition (ASR) to convert speech to text, natural language processing (NLP) to understand meaning, and speech synthesis to generate spoken responses. Hi Auto’s Voice AI processes 100M+ drive-thru orders annually at 93%+ completion rates, demonstrating that the technology has matured beyond pilots to enterprise-scale deployment.

Voice AI represents the convergence of multiple AI technologies into a single conversational experience.

Why Voice AI Matters for QSRs

The Labor Challenge

Drive-thru faces persistent staffing issues:

100-150% annual turnover
Recruitment difficulty
Training costs
Peak hour staffing gaps

Voice AI addresses these by automating order-taking.

The Efficiency Opportunity

Voice AI delivers operational benefits:

Consistent execution
100% upsell offer rate
No fatigue or distraction
24/7 availability

The Technology Moment

Voice AI has reached maturity:

Purpose-built solutions proven
93%+ completion rates achieved
100M+ orders processed annually
Enterprise scale demonstrated

How Voice AI Works

Core Components

Automatic Speech Recognition (ASR):

Converts spoken words to text
Handles noise and accents
Real-time processing
Drive-thru optimized

Natural Language Processing (NLP):

Understands meaning from text
Identifies items, modifications
Handles variations in phrasing
Context awareness

Dialog Management:

Maintains conversation flow
Tracks order state
Handles clarifications
Manages turn-taking

Speech Synthesis (TTS):

Generates spoken responses
Natural-sounding voice
Consistent tone and delivery
Brand-appropriate personality

The Processing Pipeline

Guest speaks
    ↓
[ASR] Speech → Text
    ↓
[NLP] Text → Intent + Entities
    ↓
[Dialog] Update order state
    ↓
[Response Gen] Determine what to say
    ↓
[TTS] Text → Speech
    ↓
System speaks

This happens in under 1 second for natural conversation.

Voice AI in Drive-Thru

The Application

Drive-thru Voice AI handles:

Greeting customers
Taking orders
Processing modifications
Confirming orders
Offering upsells
Completing transactions

Why Drive-Thru is Challenging

Environmental factors:

Outdoor noise (traffic, wind, weather)
Variable audio quality
Distance from microphone
Multiple speakers

Conversational factors:

Complex menus
Heavy customization
Informal speech patterns
Time pressure

Operational factors:

High volume
Peak hour intensity
Integration requirements
Reliability demands

Purpose-Built Requirements

General voice assistants fail in drive-thru because:

Not trained on drive-thru audio
Not designed for outdoor noise
Not optimized for ordering
No fallback for edge cases

Purpose-built Voice AI addresses all of these.

Voice AI Capabilities

What Voice AI Does Well

Consistent execution:

Same performance every time
No fatigue or mood variation
Reliable upselling
Predictable timing

Pattern handling:

Common orders processed smoothly
Standard modifications understood
Typical conversations managed
Routine requests handled

Data capture:

Every conversation recorded
Performance metrics tracked
Patterns identified
Continuous improvement enabled

Current Limitations

Edge cases:

Unusual requests
Complex situations
Angry customers
Unexpected scenarios

Human judgment:

Conflict resolution
Unusual accommodations
Empathetic response
Creative problem-solving

This is why hybrid architecture with human backup is essential.

Voice AI Performance

Key Metrics

Metric	Enterprise Target	Hi Auto Performance
Completion rate	90%+	93%+
Accuracy	95%+	96%
Uptime	99.9%+	99.9%+
Response time	<1 sec	<1 sec

Performance Evidence

Proven at scale:

~1,000 live stores
100M+ orders per year
Multiple major brands
Diverse environments

Voice AI Architecture Options

Fully Automated

How it works:

AI handles 100% of interactions
No human backup
Customer escalates if frustrated

Performance:

60-70% completion typical
Many failed interactions
High guest frustration
Operational challenges

Hybrid (HITL)

How it works:

AI handles most interactions
Humans cover edge cases
Seamless transition
Quality guaranteed

Performance:

93%+ completion
Rare failures
Good guest experience
Operationally viable

Hi Auto uses hybrid architecture for enterprise-grade reliability.

Evaluating Voice AI

Key Questions

Performance proof:

Completion rate at scale?
Accuracy metrics?
How many live stores?
Verifiable references?

Architecture:

What happens when AI fails?
Human backup available?
How seamless is handoff?
Uptime guarantees?

Integration:

POS connectivity?
Menu synchronization?
Order submission?
Data exchange?

Red Flags

Only pilot deployments
Vague performance claims
No hybrid architecture
No verifiable references

Green Flags

Hundreds/thousands of live stores
Specific, verified metrics
HITL backup
Referenceable customers at scale

Voice AI Benefits

Labor Impact

3-8 hours saved per store per day
Staff reallocated to higher-value tasks
Reduced hiring pressure
Better employee experience

Revenue Impact

100% upsell offer rate
25-40% conversion vs. 5-20% human
1.5%+ average ticket increase
Consistent execution

Operational Impact

Consistent performance
Peak hour reliability
Reduced error rates
Better guest experience

Data and Insights

Every conversation captured
Performance metrics available
Optimization opportunities identified
Continuous improvement enabled

The Future of Voice AI

Near-Term Evolution

Broader adoption
Improved accuracy
Better edge case handling
Enhanced personalization

Longer-Term Potential

Full conversation capability
Multi-language support
Integrated loyalty/personalization
Predictive capabilities

Common Misconceptions About Voice AI

Misconception: “Voice AI will replace drive-thru workers.”

Reality: Voice AI augments workers rather than replacing them. Staff are reallocated to food preparation, quality control, and guest service. The technology addresses staffing shortages, not eliminating jobs. Most operators use Voice AI to better utilize existing staff.

Misconception: “Voice AI is just IVR with better marketing.”

Reality: Modern Voice AI uses deep learning, neural networks, and advanced language models that far exceed IVR capabilities. The difference is like comparing GPS navigation to a paper map. Voice AI understands natural language and maintains conversation context.

Misconception: “If AI fails, customers just wait for help.”

Reality: Enterprise Voice AI includes human backup that activates within seconds when needed. Customers rarely notice the transition. The hybrid architecture ensures 93%+ of interactions complete successfully with seamless coverage for the rest.