The True Cost of Hiring Staff to Answer Phones (vs Maple AI

May 16, 2025

Purple Flower

For restaurant owners, staffing is always a balancing act—especially when it comes to managing the phone. Every call could be a new order, a large catering inquiry, or a loyal customer checking hours. But hiring someone just to answer the phone? It’s expensive, inconsistent, and often inefficient.

In 2025, restaurants have a better option: AI voice assistants like Maple that answer every call instantly, accurately, and affordably.

Let’s break down the true cost of hiring a person to answer your restaurant’s phone—and how it compares to Maple AI.

Part 1: What It Really Costs to Hire Staff for Phone Duty

Hiring someone just to answer the phone seems simple, but the real costs go far beyond hourly wages.

💵 Base Wages Add Up Quickly

Let’s assume you pay $17/hour, and the staff member answers phones for 6 hours a day, 6 days a week:


That’s nearly $30,000 per year—and that’s before taxes, benefits, or training costs.

📉 You're Paying for Downtime

The phone doesn’t ring non-stop. Most restaurants see calls spike during certain hours, leaving the phone staff idle during slow periods. This means you’re paying for non-revenue generating time.

😫 Burnout & Human Error Are Inevitable

  • Staff may miss calls during rush.

  • They can’t answer after hours or on holidays.

  • They might forget menu details or mishear orders.

  • They occasionally sound impatient or rushed, especially when multitasking.

In short: your guest experience and revenue are at the mercy of how someone’s shift is going.

Part 2: What Maple AI Costs (and Delivers)

Maple is a 24/7 AI phone assistant designed specifically for restaurants. It answers every call, handles orders and reservations, and never gets tired.

Flat Monthly Fee

Most restaurants using Maple pay between $199–$299/month/location.

Even at the high end, that’s 88% cheaper than a full-time human hire.

Always Available

Maple never misses a call—not during the lunch rush, not after hours, not on New Year’s Eve. It:

  • Answers in under 2 seconds

  • Takes detailed pickup or delivery orders

  • Books reservations or waitlists

  • Handles FAQs (hours, address, specials)

📊 Built-In Call Analytics

Maple provides transcripts, call logs, order conversion data, and keyword insights—something human staff can’t offer. You get visibility into what customers ask most, when calls spike, and what’s being missed.

Side-by-Side Cost Comparison

Feature

Human Staff

Maple AI

Monthly Cost

~$2,448

~$199–$299

Availability

Limited to shift hours

24/7, 365 days

Response Time

Varies; often delayed

<2 seconds

Order Accuracy

Inconsistent under pressure

Consistent and error-free

After-Hours Coverage

Call Analytics

Scalability

Requires more hires

Instantly scales across stores

Customer Experience

Varies by mood/stress

Polite, consistent, reliable

What About Partial Coverage?

Some restaurants use existing staff to handle phones “when they can.” But that creates its own issues:

  • Calls are missed during rush

  • Orders get taken wrong due to distractions

  • Staff split attention between guests and the phone

  • No accountability for dropped calls

This “no-plan plan” still leads to revenue loss and bad customer experiences.

Final Thoughts: Hire for Hospitality, Automate the Phones

Your best staff should be focusing on guests—not juggling phone calls. In a tight labor market, it makes more sense to put people where human touch matters most: service, food quality, and in-person hospitality.

For everything else? AI can handle it—better, faster, and cheaper.

Hiring a person to answer your phones costs you $30,000 a year. Maple costs less than $3,000—and never drops a call.

Want to See the ROI for Yourself?

Maple is helping restaurants recover thousands in lost orders, reduce labor costs, and turn the phone into a 24/7 sales channel.

Book a free demo to see how much you could save.

Join the hundreds of restaurants already streamlining their operations with Maple's Voice AI solution.

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