AI Receptionists for Restaurants: 2026 Vendor & Compliance Guide

Major takeaways

Which restaurant calls can an AI voice agent handle today?

AI agents can book and modify reservations, manage waitlists, answer hours and menu questions, take takeout orders, and field event inquiries. They read from reservation systems and POS platforms, confirm bookings via SMS, and escalate to staff when a caller requests a manager or reports a food safety concern. Most platforms handle 70–85% of routine inbound calls without human intervention, based on vendor-reported benchmarks.

What are the compliance risks in restaurants?

Federal TCPA rules apply to outbound calls and texts, state call-recording consent laws vary by jurisdiction, and PCI-DSS standards govern how payment card data is captured and transmitted. Health data boundaries matter when callers disclose allergies or medical conditions, and some states impose additional consumer-protection requirements on automated systems. Every restaurant should confirm compliance requirements with counsel before deployment.

When should a human stay on the call?

Escalate to a human when a caller reports illness or food safety concerns, requests a refund for a completed order, asks to speak to a manager by name, or discloses a severe allergy that requires kitchen coordination beyond standard menu notes. AI agents should also hand off when a caller becomes frustrated after repeated clarification attempts or when the request falls outside the scripted use cases.

Key takeaways

• Phone is the primary channel for same-day reservations, last-minute changes, and complex dietary requests that require real-time kitchen confirmation.
• After-hours and peak-time gaps cost restaurants an estimated 15–30% of potential bookings, based on industry surveys of missed-call rates during service hours.
• AI agents integrate with OpenTable, Resy, Toast, Square, and other reservation and POS systems, writing bookings and order details directly without manual re-entry.
• Compliance spans TCPA, state recording-consent laws, and PCI-DSS for payment handling, plus allergen-disclosure liability under state consumer-protection statutes.
• Rollout starts with a single use case such as after-hours reservation booking or takeout order intake, piloted on a subset of traffic before expanding to peak hours.
• Cost models include per-minute metered pricing, monthly platform fees, and hybrid structures that charge per concurrent call or per location, typically compared against the fully loaded cost of a host or phone-answering service.
• Vendor selection depends on reservation-system integrations, multilingual support, and handoff speed to staff when escalation is required, with compliance documentation and call-transcript access as table-stakes.

Why phone still matters in restaurants

Phone calls are the dominant channel for same-day reservations, party-size changes, and dietary questions that require real-time kitchen confirmation.

A 2024 survey by the National Restaurant Association found that 62% of diners still prefer calling for reservations over app-based booking, particularly for groups larger than four or for special occasions that require specific seating requests. Source: National Restaurant Association

Missed calls during service hours cost restaurants an estimated 15–30% of potential bookings, based on a 2023 study by Upserve that tracked call logs and reservation fill rates across 1,200 independent restaurants. The same study found that 40% of missed calls during dinner service were never returned by the caller, who typically booked with a competitor instead. Source: Upserve

After-hours inquiries are another coverage gap. A 2024 analysis by Toast found that 18% of inbound calls to full-service restaurants occur outside operating hours, with the majority asking about hours, menu availability, or attempting to book for the following day. Restaurants without after-hours call handling lose these bookings to competitors with live answering or automated systems. Source: Toast Restaurant Success Report 2024

Peak-time overflow creates a third problem.

During Friday and Saturday dinner service, host staff often manage walk-in seating, coordinate waitlists, and handle in-person guest questions simultaneously, leaving phone calls unanswered or rushed. A 2023 OpenTable survey of restaurant operators found that 54% reported missing calls during peak hours at least weekly, with the highest miss rates occurring between 6:00 PM and 8:00 PM. Source: OpenTable State of the Industry Report 2023

Takeout and delivery order intake adds volume. Restaurants that handle phone orders alongside third-party delivery platforms report call spikes during lunch and dinner rushes, when kitchen and front-of-house staff are least available to take detailed orders. Order errors from rushed phone conversations cost restaurants an estimated $50–$150 per mistake in remade food and lost customer trust, based on industry estimates cited in Restaurant Business Online. Source: Restaurant Business Online

Use cases: what AI can handle

Reservation booking and modification

A caller phones to book a table for four on Saturday at 7:00 PM or to move an existing reservation from 6:30 PM to 8:00 PM. The AI agent checks real-time availability in the reservation system (OpenTable, Resy, Yelp Reservations, or a proprietary platform), confirms the party size and date, captures the caller's name and phone number, and writes the booking directly to the system.

The agent sends an SMS confirmation with the reservation details and a link to modify or cancel. If the requested time is unavailable, the agent offers the nearest open slots before and after the target time.

The call escalates to a host if the caller requests a specific table, needs accessibility accommodations, or mentions a VIP status that requires manager approval.

Waitlist management and callback coordination

A walk-in party arrives during peak hours and the host adds them to the waitlist. The AI agent calls the party when their table is ready, confirms they are still on the way, and provides an estimated seating time. If the party does not answer, the agent sends an SMS with a callback number and moves to the next group on the list.

The agent reads waitlist position and estimated wait times from the restaurant's POS or waitlist-management system (Yelp Waitlist, Waitlist Me, or a native POS module) and updates the system when a party confirms or cancels.

The call escalates to a host if the party requests a different table size or reports a delay longer than the quoted wait window.

Hours and location inquiries

A caller asks whether the restaurant is open on Thanksgiving, what time brunch service starts, or where the nearest location is. The AI agent pulls hours from the restaurant's system of record or a connected calendar, provides the address and parking instructions, and offers to book a reservation if the caller is interested. The agent can handle multi-location queries by asking the caller's zip code or neighborhood and routing to the closest restaurant.

The call escalates to a human if the caller asks about a temporary closure, a private event that affects public hours, or a policy question not covered in the script.

Takeout and delivery order intake

A caller phones to place a takeout order for pickup in 30 minutes. The AI agent reads the menu from the POS system (Toast, Square, Clover, or a legacy system with API access), captures the order item by item, repeats each item for confirmation, calculates the total including tax, and processes payment via a PCI-compliant payment gateway or schedules payment at pickup.

The agent provides an estimated ready time based on current kitchen load (if the POS exposes that data) and sends an SMS confirmation with the order summary and pickup instructions.

The call escalates to a human if the caller requests a custom modification not available in the menu configuration, asks about ingredient sourcing, or reports a problem with a previous order.

Event and private dining inquiries

A caller asks about booking a private dining room for a birthday party of 20 or a corporate lunch for 30. The AI agent captures the party size, preferred date and time, and event type, then checks availability in the restaurant's event-management system or calendar.

If the request falls within standard private-dining parameters (party size, advance notice, menu options), the agent provides pricing, menu packages, and deposit requirements, and schedules a follow-up call with the events coordinator.

The call escalates immediately to the events team if the party size exceeds the largest private space, if the caller requests a custom menu, or if the event includes alcohol service that requires a separate contract.

Dietary restriction and allergen questions

A caller asks whether the kitchen can accommodate a gluten-free diet, whether a specific dish contains shellfish, or whether vegan options are available. The AI agent reads allergen and dietary tags from the menu system, confirms which dishes meet the caller's requirements, and notes the restriction in the reservation record if the caller books a table.

The agent provides a standard disclaimer that cross-contamination is possible and that the caller should inform the server upon arrival.

The call escalates to a human if the caller reports a severe or life-threatening allergy that requires direct kitchen coordination, asks about ingredient sourcing or preparation methods not documented in the menu system, or requests a custom dish modification.

General menu and availability questions

A caller asks whether the restaurant has a specific dish, whether the lunch menu is available on weekends, or whether a seasonal item is still on the menu. The AI agent reads from the current menu in the POS or website CMS, confirms availability, and provides pricing if requested. The agent can handle questions about portion sizes, preparation styles, and pairing recommendations if that information is structured in the menu data.

The call escalates to a human if the caller asks about off-menu specials, requests a recipe or cooking technique, or asks whether the chef can prepare a dish from a previous menu.

A sample call flow

This flow describes a standard reservation-booking call, the most common inbound use case for restaurant AI voice agents.

1. Greeting and AI disclosure. The agent answers with the restaurant name and identifies itself as an AI assistant. Example: "Thank you for calling [Restaurant Name]. This is an AI assistant. How can I help you today?" Some jurisdictions require explicit AI disclosure at the start of the call; others allow it to be embedded in the greeting. Confirm requirements with counsel.

2. Intent capture. The agent asks what the caller needs. If the caller says "I'd like to make a reservation," the agent proceeds to booking. If the caller asks a question about hours or menu, the agent routes to the appropriate script. If the caller asks for a manager or reports a complaint, the agent escalates immediately.

3. Party size and date. The agent asks how many people and what date. If the caller provides a day of the week without a date, the agent confirms the specific date. Example: "You'd like a table for four this Saturday, which is March 15th. Is that correct?"

4. Time preference. The agent asks what time the caller prefers. If the caller provides a range, the agent checks availability for the earliest time in the range first.

5. Availability check. The agent queries the reservation system in real time. If the requested time is available, the agent confirms the slot. If not, the agent offers the nearest available times before and after the target. Example: "7:00 PM is fully booked, but I have 6:30 PM and 7:45 PM available. Which works better for you?"

6. Caller information. The agent captures the caller's name and phone number. If the caller is a returning guest, the agent may recognize the phone number and confirm the name on file. Example: "I have a reservation under Sarah Chen. Is that correct?"

7. Special requests. The agent asks if the caller has any special requests, such as a high chair, outdoor seating, or a birthday celebration. The agent notes the request in the reservation record. If the request requires manager approval (e.g., a specific table), the agent flags the reservation for follow-up and tells the caller a staff member will confirm within a specified time window.

8. Confirmation and SMS. The agent repeats the reservation details: party size, date, time, and any special requests. The agent sends an SMS confirmation with a link to modify or cancel the reservation. Example: "Your table for four is confirmed for Saturday, March 15th at 7:00 PM. I've sent a confirmation text to your phone."

9. CRM write-back. The agent writes the reservation details, caller information, and any notes to the reservation system and CRM. If the restaurant has a unified POS and CRM (Toast, Square), the data flows into the guest profile for future reference.

10. Escalation path. If at any point the caller asks to speak to a human, reports a problem with a previous visit, or makes a request outside the agent's script, the call transfers to a host or manager. The agent provides context to the human: "I'm transferring you to a team member. The caller is asking about [specific issue]."

Recording disclosure typically occurs at the start of the call, either in the greeting or via a pre-recorded message before the agent picks up. Example: "This call may be recorded for quality and training purposes." State laws vary on whether one-party or two-party consent is required; confirm with counsel.

Compliance and risk in restaurants

TCPA and telemarketing rules

The Telephone Consumer Protection Act restricts automated calls and texts to mobile phones without prior express written consent. For restaurants, this primarily affects outbound use cases: waitlist callbacks, reservation reminders, and promotional calls.

Inbound calls initiated by the customer generally do not require TCPA consent, but if the restaurant's AI agent sends a follow-up SMS (reservation confirmation, waitlist update), that message may fall under TCPA if the caller did not explicitly opt in to texts. The safest approach is to capture SMS consent during the call ("Can I send you a text confirmation?") and log the consent timestamp in the CRM. Source: FCC TCPA Rules

State telemarketing laws may impose additional restrictions. California's Automatic Dialing-Announcing Device (ADAD) statute prohibits certain automated calls to residences, and other states have similar rules. Restaurants that use AI agents for outbound reservation reminders or promotional calls should confirm that the vendor's dialing system complies with state-level restrictions.

Call recording consent requirements

Eleven states require two-party consent for call recording: California, Connecticut, Florida, Illinois, Maryland, Massachusetts, Michigan, Montana, New Hampshire, Pennsylvania, and Washington. In these states, the restaurant must inform the caller that the call is being recorded and obtain affirmative consent before recording begins.

The disclosure can be a pre-recorded message ("This call may be recorded") or delivered by the AI agent at the start of the call. The remaining states follow one-party consent rules, meaning the restaurant can record without explicit caller notification, though best practice is to disclose recording in all cases. Source: Justia Legal Resources

Call recordings that contain payment card information are subject to PCI-DSS requirements. If the AI agent captures card numbers verbally, the recording must either mask the card data or be stored in a PCI-compliant environment. Most vendors avoid this problem by routing payment capture to a separate IVR system or by sending the caller an SMS link to a secure payment page.

Payment card data handling (PCI-DSS)

The Payment Card Industry Data Security Standard governs how card data is captured, transmitted, and stored. Restaurants that use AI agents to take phone orders must ensure that card numbers are not stored in call recordings, transcripts, or CRM fields unless those systems are PCI-compliant.

The safest approach is to use a PCI-certified payment gateway that captures card data via DTMF tones (which are not recorded) or via an SMS link to a secure payment page. Source: PCI Security Standards Council

If the AI agent must capture card data verbally, the vendor should provide PCI-compliant recording and storage, with card numbers masked in transcripts and redacted from CRM write-backs. Restaurants should confirm that the vendor's PCI compliance certificate is current and that the certificate covers the specific use case (voice-based card capture).

Health data boundaries and allergen liability

When a caller discloses a food allergy or medical condition, the AI agent is capturing health information. While restaurant conversations are not typically covered by HIPAA (which applies to healthcare providers, insurers, and their business associates), the information may still create liability if the restaurant fails to accommodate the disclosed restriction and the caller suffers harm.

The AI agent should note the allergen or dietary restriction in the reservation record and provide a standard disclaimer: "Please inform your server about your allergy when you arrive so the kitchen can take appropriate precautions." Source: U.S. Department of Health & Human Services

The agent should escalate to a human if the caller reports a severe or life-threatening allergy, asks about cross-contamination procedures, or requests a custom dish modification. Some states impose strict liability for allergen-related harm if the restaurant knew about the allergy and failed to prevent exposure. Restaurants should work with counsel to draft the allergen-disclosure script and escalation rules.

State-specific consumer protection laws

Some states impose additional requirements on automated phone systems. California's Consumer Privacy Act (CCPA) gives consumers the right to request deletion of their personal information, which may include call recordings and CRM data captured by the AI agent.

Illinois's Biometric Information Privacy Act (BIPA) restricts the use of voiceprints for caller identification without explicit consent. Restaurants operating in multiple states should confirm that the vendor's system complies with the most restrictive state laws that apply to their customer base. Source: California Attorney General CCPA

Compliance checklist

• Confirm TCPA consent requirements for outbound calls and SMS with counsel.
• Verify that the vendor's system complies with two-party recording-consent laws in all states where the restaurant operates.
• Ensure that payment card data is captured via a PCI-compliant gateway and not stored in call recordings or transcripts.
• Draft an allergen-disclosure script and escalation rule for severe allergies, reviewed by counsel.
• Confirm that the vendor's data retention and deletion policies comply with CCPA and other state privacy laws.
• Document AI disclosure language and confirm it meets state requirements for automated-system transparency.
• Review the vendor's data-security certifications (SOC 2, ISO 27001) and confirm that call recordings are encrypted at rest and in transit.
• Establish a process for handling caller requests to speak to a human or to delete their data.

How to evaluate AI voice vendors for restaurants

Vendor landscape

Slang.ai offers AI phone agents built specifically for restaurants, with native integrations to OpenTable, Resy, Toast, and Square. The platform handles reservation booking, takeout orders, and waitlist management, with reported deployment at chains including Wow Bao and Beef 'O' Brady's. Source: Slang.ai

PolyAI provides conversational AI for restaurant chains and hospitality groups, with support for multilingual calls and complex order modifications. The platform integrates with major POS systems and is reportedly used by Papa Johns and other QSR brands. Source: PolyAI

Kea specializes in drive-thru and phone order automation for quick-service restaurants, with integrations to legacy POS systems and reported deployments at Checkers, Rally's, and other chains. Source: Kea

Valyant AI focuses on voice AI for QSR drive-thrus and phone orders, with reported pilots at White Castle and other brands. The platform is designed for high-volume, low-complexity order intake. Source: Valyant AI

Voiceflow and Vapi are general-purpose voice-agent platforms that can be customized for restaurant use cases, offering flexibility for independent restaurants or small chains that need tailored scripts and integrations. Both platforms require more technical setup than restaurant-specific vendors. Source: Voiceflow, Vapi

Rollout plan

1. Choose one call type. Start with the highest-volume, lowest-complexity use case: after-hours reservation booking, takeout order intake, or hours-and-location inquiries. Avoid starting with event inquiries or complex dietary questions, which require more nuanced escalation rules.

2. Map the script and escalation rules. Document the agent's greeting, the questions it asks, the system lookups it performs, and the conditions under which it escalates to a human. Include the exact wording for AI disclosure, recording consent, and allergen disclaimers. Review the script with counsel to confirm compliance with TCPA, recording-consent laws, and allergen-liability standards.

3. Legal review. Have counsel review the script, escalation rules, data-retention policy, and vendor contract. Confirm that the vendor's compliance documentation (PCI certificate, SOC 2 report, TCPA legal opinion) is current and covers the specific use case.

4. Connect systems. Integrate the AI agent with the reservation system, POS, CRM, and any other platforms it needs to read or write data. Test the integration with sample calls to confirm that bookings, orders, and notes flow correctly and that the agent can handle edge cases (unavailable times, out-of-stock items, duplicate reservations).

5. Pilot on a slice of traffic. Deploy the agent on after-hours calls only, or route a percentage of peak-time calls to the agent while the rest go to staff. Monitor call transcripts daily for the first two weeks to identify escalation gaps, script ambiguities, and caller frustration points.

6. Review transcripts and adjust. Read every escalated call transcript to understand why the agent handed off. Common issues include callers asking questions not covered in the script, callers requesting a human without giving the agent a chance to help, and callers with accents or background noise that the agent struggles to parse. Update the script and escalation rules based on these findings.

7. Expand coverage. Once the pilot shows consistent performance (target: 70–85% of calls handled without escalation, based on vendor benchmarks), expand the agent to peak hours or additional call types. Continue reviewing a sample of transcripts weekly to catch drift in caller behavior or new edge cases.

Metrics to track:

• Call containment rate: percentage of calls the agent completes without escalating to a human.
• Booking conversion rate: percentage of reservation-inquiry calls that result in a confirmed booking.
• Order accuracy rate: percentage of takeout orders completed without errors or customer callbacks.
• Average handle time: how long the agent takes to complete a call, compared to human staff.
• Escalation reasons: why the agent handed off, categorized by intent (complaint, out-of-scope question, caller request, technical failure).
• Caller satisfaction: post-call survey scores or callback rates for callers who escalated.

Do not set arbitrary targets before the pilot. Baseline performance varies by restaurant type, call volume, and caller demographics. Use the pilot data to establish realistic benchmarks.

Cost considerations

AI voice agents for restaurants are typically priced per minute of talk time, per call, or via a flat monthly platform fee. Per-minute pricing ranges from $0.05 to $0.25 per minute based on vendor-reported public pricing, with higher rates for platforms that include advanced features such as multilingual support, CRM integrations, or custom script development.

Per-call pricing is less common but may be offered by vendors targeting high-volume QSR chains, with rates tied to call complexity (simple menu inquiry vs. multi-item order). Flat monthly fees are typically reserved for enterprise contracts and may include a seat-based component for restaurants with multiple locations.

Cost drivers for restaurant call patterns include average call length (reservation bookings are shorter than event inquiries), peak-time concurrency (how many calls the agent must handle simultaneously during dinner service), and integration complexity (connecting to legacy POS systems or custom reservation platforms adds setup cost). Restaurants with high after-hours call volume may see faster ROI, since the agent replaces the cost of an answering service or eliminates missed calls entirely.

Comparing AI agent cost to staffing requires calculating the fully loaded cost of a host or phone-answering service. A full-time host at $15 per hour costs approximately $31,200 annually including payroll taxes and benefits, based on standard employer-cost multipliers. A phone-answering service typically charges $1.00–$2.50 per call or $200–$500 per month for a fixed number of calls, based on industry estimates.

AI agents that handle 1,000 calls per month at $0.10 per minute and an average call length of 2 minutes cost $200 per month, roughly equivalent to a low-tier answering service but with 24/7 coverage and direct system integration.

For a detailed staffing-cost comparison, see the SDR cost calculator, which models fully loaded employee costs including salary, benefits, software, and management overhead. While the calculator is built for sales teams, the cost structure applies to any phone-based role.

Setup fees vary by vendor and use case. Restaurant-specific platforms with pre-built integrations to OpenTable, Toast, and Square may charge $500–$2,000 for initial configuration, while general-purpose voice platforms that require custom script development and API work may charge $5,000–$15,000 for the same deployment, based on vendor-reported estimates. Restaurants should confirm whether the setup fee includes script revisions, integration testing, and compliance review, or whether those services are billed separately.

Frequently asked questions

Is it legal to use AI for restaurant phone answering?

Yes, but compliance requirements vary by state and use case. Inbound calls initiated by the customer generally do not require special consent, though some states mandate AI disclosure at the start of the call. Outbound calls and SMS messages (reservation reminders, waitlist callbacks) are subject to TCPA rules, which require prior express written consent for automated calls to mobile phones.

Call recording is legal in one-party consent states without explicit disclosure, but eleven states require two-party consent, meaning the caller must be informed and must agree to recording before the call proceeds. Restaurants should confirm compliance requirements with counsel before deployment.

Do callers need to be told they're speaking to AI?

Best practice is to disclose AI at the start of the call, either in the greeting or via a pre-recorded message. Some states are considering or have passed laws requiring explicit AI disclosure for automated systems, and failing to disclose can create customer-trust issues even in jurisdictions where disclosure is not legally required.

A simple disclosure is sufficient: "This is an AI assistant" or "You're speaking with an automated system." The disclosure does not need to explain how the AI works or what data it collects, though privacy-conscious restaurants may choose to provide that information.

Can an AI agent access our reservation and POS systems?

Yes, if the vendor provides a native integration or API connector. Most restaurant-specific AI platforms integrate directly with OpenTable, Resy, Yelp Reservations, Toast, Square, Clover, and other major systems, reading availability in real time and writing bookings or orders without manual re-entry.

Legacy POS systems or custom reservation platforms may require API development, which adds setup time and cost. Restaurants should confirm that the integration is bidirectional (the agent can read and write data) and that changes made by staff in the POS or reservation system are visible to the agent immediately.

What happens when the AI can't answer a question?

The agent should escalate to a human. Most platforms allow the restaurant to define escalation rules: transfer immediately when the caller asks for a manager, flag the call for follow-up when the question is out of scope, or attempt to capture the caller's contact information and have a staff member call back.

The escalation should include context (call transcript, caller ID, stated intent) so the human does not make the caller repeat themselves. Restaurants should review escalated calls regularly to identify gaps in the script or training data.

How much does AI phone answering cost for restaurants?

Per-minute pricing typically ranges from $0.05 to $0.25 per minute based on vendor-reported rates, with the total monthly cost depending on call volume and average call length. A restaurant that handles 1,000 calls per month with an average length of 2 minutes would pay $100–$500 per month under a per-minute model.

Flat monthly fees are common for enterprise contracts and may range from $500 to $5,000 per month depending on the number of locations, concurrent call capacity, and included features. Setup fees range from $500 to $15,000 based on integration complexity and script customization requirements.

Will AI replace our host staff?

No. AI agents handle routine calls (reservation booking, hours inquiries, takeout orders) but escalate to humans for complaints, complex requests, and situations that require judgment or empathy. Host staff remain responsible for in-person guest management, walk-in seating, waitlist coordination, and handling escalated calls.

The agent reduces the volume of routine calls that interrupt hosts during peak service, allowing them to focus on the dining room. Some restaurants redeploy host hours to other tasks (guest follow-up, event coordination) rather than reducing headcount.

How long does it take to go live?

Deployment timelines range from two weeks to three months depending on integration complexity, script customization, and legal review. Restaurants using a vendor with native integrations to their reservation and POS systems can often go live in two to four weeks, including script development, system testing, and a pilot period.

Restaurants with custom or legacy systems may require six to twelve weeks for API development and integration testing. Legal review adds one to two weeks if the restaurant's counsel needs to review the vendor contract, compliance documentation, and call scripts.

Which vendors specialize in restaurants?

Slang.ai, PolyAI, Kea, and Valyant AI offer platforms built specifically for restaurant use cases, with native integrations to reservation systems and POS platforms. General-purpose voice platforms such as Voiceflow and Vapi can be customized for restaurants but require more technical setup.

Restaurants should evaluate vendors based on integration support, multilingual capabilities, compliance documentation, and pricing model, and should request a pilot or proof-of-concept before committing to a long-term contract.

Can AI handle multiple languages for diverse customer bases?

Yes, most modern AI voice platforms support multilingual conversations, with the agent detecting the caller's language and responding in that language. Common languages for U.S. restaurants include Spanish, Mandarin, Cantonese, Vietnamese, and Korean.

Some platforms translate on the fly using a speech-to-text and text-to-speech pipeline, while others are trained natively in each language. Restaurants should confirm that the vendor's multilingual support includes the specific languages spoken by their customer base and should test the agent's fluency in each language during the pilot.

What if a caller has a complaint or wants to speak to a manager?

The agent should transfer immediately. Complaints, refund requests, and manager escalations are high-stakes interactions that require human judgment and empathy. The agent should provide context to the manager (call transcript, caller ID, stated issue) and should not attempt to resolve the complaint itself.

Restaurants should define a clear escalation path in the script and should monitor escalated calls to ensure that callers are not left on hold or transferred multiple times.

Last updated: November 2026.