How to Make AI Voice Agents Think and Act Like Your Best Human Agents

Written by:

November 25, 2025

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5 min read

What Sets Your Best Agents Apart?

Every contact center has a handful of agents who just get it. They deliver higher CSAT scores, resolve issues faster, and convert more leads. They don't just follow scripts—they come prepared, anticipate needs, take ownership, and actually get things done—all while making it feel effortless.

Historically, this level of performance has depended on human intuition and experience, so replicating it at scale has been impossible. Even the most advanced IVRs and rule-based bots could only handle narrow tasks. They couldn’t reason about a customer’s situation, interpret context across systems, or take multi-step actions the way a top human agent can.

Generative Voice AI changes that. Modern LLMs can understand spoken intent with nuance, interpret intent, maintain context, pull information from multiple systems, personalize responses, and take action in real time. With the right tooling, AI agents can understand where a customer is, what’s happened so far, and what needs to happen next.

To truly match elite human performance, AI agents need five core capabilities: spatial awareness, temporal awareness, sensory perception, proactive information retrieval, and real action-taking. With these capabilities, they stop behaving like simple conversational interfaces and start operating like fully empowered operators.

In this article, we’ll break down each capability, and how Regal enables it through technical integrations and deployable Custom Actions.

The Five Pillars of High-Performing Voice AI

1. Spatial Awareness: Knowing Where You Are

How Elite Agents Do It

Top human agents instinctively understand location-based context — whether a customer is in a serviceable area, whether certain products are available in their region, or how local rules and constraints might affect what they can offer. This spatial intuition helps them qualify faster, avoid dead ends, and personalize recommendations.

How Voice AI Does It Better

AI can process spatial data at a depth and scale humans simply can’t. A well-equipped voice agent can:

Validate and normalize addresses in real time
Cross-check serviceability across territories or ZIP codes
Query mapping APIs for distances, routes, and travel times
Pull in regional inventory, pricing, or availability
Factor in local regulations, weather conditions, or event data

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Because these checks happen in milliseconds, the AI enters the call already aware of what’s possible, and what’s not.

What This Looks Like in Practice

Regal makes spatial reasoning plug-and-play by connecting the AI agent to geocoding APIs, territory files, and regional inventory or service systems via Custom Actions. These actions can trigger automatically at call start so the agent enters the conversation already prepared.

For example, an outbound solar sales agent can automatically:

Check the prospect’s address via a geocoding API
Verify sunlight exposure using satellite imagery
Confirm local tax incentives based on ZIP code
Check the regional installation queue across service crews
Calculate ROI using local utility rates and incentive data

All of this happens before the prospect picks up, enabling the AI to open the call with accurate, personalized context from the second it starts talking.

2. Temporal Awareness: Getting Timing Exactly Right

How Elite Agents Do It

The best agents have impeccable timing. They remember time zones, honor promised follow-ups, reference past interactions naturally, and know how to schedule around holidays, downtime, and customer preferences. This temporal intuition helps them reach customers at the right moment and coordinate complex logistics without friction.

How Voice AI Does It Better

AI can track timing with perfect reliability across thousands of customers simultaneously. A well-equipped voice agent can:

Automatically infer or retrieve the customer’s timezone
Understand whether it’s a good time to call based on contact history
Recall past commitments and promised follow-ups
Capture availability in structured formats
Coordinate across multiple calendars, workloads, and blackout periods
Respect holidays, weekends, and regional scheduling constraints

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These temporal checks happen instantly, ensuring the AI always engages at the right moment with the right context.

What This Looks Like in Practice

With Regal, temporal reasoning becomes a built-in capability. The AI automatically detects the customer’s timezone, references past commitments, and uses Regal’s native gather_date action to collect availability in a structured format. From there, it can either create callback tasks directly inside Regal or work with external scheduling platforms—like Cal.com, Google Calendar, Outlook, or internal dispatch tools—through Custom Actions.

For example, when rescheduling a technician appointment, the AI can automatically:

Recognize that it’s Tuesday afternoon and the customer is in Pacific Time
Recall their preference for morning appointments
Avoid an upcoming holiday and internal blackout windows
Check availability across multiple technicians in the region
Offer the earliest compatible time slot
Write the appointment back to the appropriate scheduling system

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All of this happens instantly, enabling the AI to propose accurate options and complete the scheduling workflow without the customer repeating a single detail.

3. Sensory Perception: Seeing and Understanding Context

How Elite Agents Do It

Your best agents never enter a conversation blind. Before they even say hello, they’ve already scanned the customer’s profile, checked recent interactions, reviewed open tickets or orders, and recalled past preferences. That preparation lets them personalize the conversation, anticipate issues, and shortcut decision-making.

How Voice AI Does It Better

AI can absorb and analyze context at a scale no human can. A well-equipped voice agent can:

Interpret what the customer is saying in real time and map spoken intent to the relevant workflow
Pull the full customer profile from the CRM in milliseconds
Combine purchase history, support history, and preferences into a unified view
Identify potential issues or likely intents before the customer mentions them
Retrieve relevant knowledge base entries dynamically
Adjust tone, script path, and decision logic in real time based on context

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Instead of juggling multiple screens, AI processes everything at once, and adapts its next step accordingly.

How This Works in Practice

With Regal, sensory perception becomes a real-time reasoning layer. Through Custom Actions, the AI can fetch CRM data (like customer tier, recent interactions, open issues, product ownership, or lifecycle stage) and immediately use that information to personalize both what it says and how it decides what to do next.

At the same time, Regal’s Knowledge Base gives the agent instant access to domain-specific guidance, FAQs, product rules, troubleshooting flows, compliance language, and more — all retrieved and applied dynamically. The AI uses this information to choose the right answer, follow the correct policy, and navigate complex logic without relying on static scripts.

For example, when a customer says, “I have a question about my order,” the AI can automatically:

Pull their CRM profile and identify two active orders
Detect that one shipment is running a day late
Identify that the customer is VIP tier, which allows for free upgrade options
Check if they’ve contacted support about this issue before
Retrieve the relevant Knowledge Base entry for this product’s shipping policies
Adapt its tone and message to acknowledge the delay and offer the appropriate solution

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The agent can then respond conversationally with something like:

“Hi Jennifer, I see you’re asking about your laptop order. It’s running a day behind due to weather, but since you’re a VIP customer, I’ve upgraded it to overnight shipping at no cost. It will still arrive tomorrow.”

This all happens in real time — not through scripting, but through dynamic reasoning powered by CRM data, knowledge base context, and on-the-fly logic adaptation.

4. Information Retrieval: Looking Things Up Proactively

How Elite Agents Do It

Great agents don’t just rely on what’s already in front of them—they go find what’s missing. They search product catalogs, check stock levels, review policy documents, and dig through internal tools so they have answers ready the moment the customer asks. This proactive lookup is what lets them solve problems quickly and confidently.

How Voice AI Does It Better

AI can retrieve information across your systems faster and more comprehensively than any human. A well-equipped voice agent can:

Query product catalogs or inventory systems in real time
Search documentation, policy pages, or knowledge repositories
Look up pricing, promotions, and eligibility rules
Validate specifications or compatibility details
Scan multiple systems in parallel to eliminate wait time

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And it can do all of this the moment the customer asks a question—or even before.

How This Works in Practice

Through Custom Actions, the AI can tap into product databases, warehouse systems, pricing engines, and policy APIs to answer questions with perfect clarity and accuracy. Unlike sensory perception (#3), which focuses on interpreting the customer’s context, information retrieval focuses on gathering the external information required to answer operational questions.

For example, when a customer says, “Do you have this appliance in blue?” the AI can instantly:

Query all warehouses or stores for the relevant SKU
Check if the blue variant is in stock
Verify price and promotion eligibility
Calculate shipping timelines based on location
Pull any relevant product specs or compatibility rules
Surface any upsell or cross-sell opportunities

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Then respond naturally and precisely:

“Yes — the blue model is in stock and qualifies for free expedited shipping. I can get it to you by Friday. Would you like me to place the order?”

This isn’t memorized scripting; it’s real-time data retrieval across your operational systems.

5. Taking Action: Getting Things Done

How Elite Agents Do It

Elite agents don’t stop at understanding the issue or finding the right information—they take ownership. They schedule the appointment, process the refund, send the confirmation, and update the account during the call. When the customer hangs up, everything is already handled. Their value isn’t just knowledge; it’s execution.

How Voice AI Does It Better

AI excels at fast, precise, multi-step execution. A well-equipped voice agent can:

Update records across multiple systems simultaneously
Trigger workflows, automations, or downstream processes
Apply credits, refunds, or adjustments with perfect accuracy
Send emails, texts, or notifications instantly
Create tasks, tickets, or follow-up reminders
Complete complex multi-step actions without losing context

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And because AI doesn’t fatigue or multitask poorly, it can execute flawlessly every single time.

How This Works in Practice

Through Custom Actions, the AI can write back to your operational systems—CRMs, billing platforms, order management tools, workforce systems, marketing automation platforms, and more. Rather than handing tasks off, the AI completes the work end-to-end, turning conversations into finished actions.

For example, during a billing inquiry, the AI could:

Apply a $25 account credit via your billing API
Update billing preferences (e.g., paperless, payment method)
Send a confirmation email or SMS summarizing the change
Create a follow-up task or callback if needed
Tag the account as VIP for the next 90 days

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All in real time, while still carrying on a natural, human-like voice conversation.

The result: customers hang up with everything already resolved—and your team never touches the case.

Bring Elite Performance to Every Call

The capabilities that once distinguished your top agents—understanding where a customer is, what’s happening right now, what information matters, and what action to take—can now be delivered consistently on every interaction. With generative Voice AI, it’s finally possible to combine human-level intuition with machine-level speed, reliability, and scale. The result is a voice agent that doesn’t just respond, but prepares, reasons, and executes from the moment the call begins.

Regal’s Custom Actions give AI voice agents direct access to your systems, data, and workflows so they can personalize conversations, retrieve accurate information, and complete tasks end-to-end without human handoffs.

Ready to make your Voice AI agent a top performer? Schedule a demo with our team.

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8 Ways AI Sales Tools Assist in the Success of Call Centers

Discover how AI sales tools enhance call center performance, improve efficiency, and increase customer satisfaction with these 10 powerful strategies.

What Is Conversation Intelligence? Improve CX & Sales Insights

Learn how conversation intelligence can enhance customer experience and provide valuable sales and support insights. Discover key technologies, implementation strategies, and best practices.

6 Ways Agent Insights Into the Buyer’s Journey Improve CX

Discover 6 real-world examples for how high-consideration B2C companies are arming their agents with real-time customer data to drive more effective sales, support and retention interactions across industries.

October 2024 Releases

10 Proactive Outreach Strategies to Build Loyalty with Personalization

In order to build loyalty, it’s essential to create proactive outreach strategies that demonstrate your awareness of your customers' challenges and show that you’re taking action before they even need to ask for help.

5 Ways to Improve Agent Productivity & 5X Outbound Performance

In this blog, we share tips to improve agent productivity for handling high volumes of calls, whether it's inbound support teams or outbound sales teams. The guiding principle is simple — focus your agents on tasks that absolutely requires their attention, and automate everything else.

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