What are virtual agents and how do they improve customer calls?

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For sales and support leaders, the pressure to do more with less isn't new, but the tools available to solve it are changing rapidly. You might be facing high call volumes that leave your team overwhelmed, or perhaps your CRM data is messy because reps simply don't have time for manual entry. This is where the conversations around AI often start.

A virtual agent is an AI-powered system that automates routine voice and text interactions to support human agents. Unlike simple chatbots that only handle text on a website, modern AI virtual agents work within voice workflows to route calls, assist reps in real time, and handle the tedious administrative tasks that follow every conversation. By integrating virtual agent software directly into your tech stack, you can reduce manual effort, improve visibility into team performance, and ensure your human agents are focused on high-value interactions.

Key takeaways

• AI virtual agents handle routine tasks: These systems automate repetitive actions like call routing, data entry, and basic enquiries, freeing up human agents for complex issues.

• Integration is critical for success: Connecting virtual agents to your CRM (like Salesforce or HubSpot) ensures data consistency and provides a unified view of the customer journey.

• Real-time support improves performance: AI agents offer live guidance and coaching during calls, helping reps handle objections and resolve problems faster.

• Cost-effective scaling: Virtual agents allow growing businesses to handle increased call volume 24/7 without proportionally increasing headcount.

• Humans are still essential: Virtual agents support rather than replace human teams, handling the busywork so people can focus on relationship-building.

What is a virtual agent?

A virtual agent is a software application that uses artificial intelligence (AI) and natural language processing (NLP) to interact with customers, automate tasks, and assist human agents. In customer communication, it acts as a first line of defense, capable of understanding caller intent, routing conversations, and even resolving routine queries without human intervention.

Quick facts about virtual agents:

• Primary function: Automates voice and text-based workflows before, during, and after interactions.

• Technology: Uses Natural Language Processing (NLP) and Machine Learning (ML) to understand and act on intent.

• Deployment: Integrates with CCaaS (Contact Centre as a Service) platforms and CRMs.

• Value add: Reduces manual data entry, lowers average handle time (AHT), and provides 24/7 coverage.

How do virtual agents work?

Virtual agents work by processing spoken or written language to determine what a customer wants (intent) and then executing a workflow to fulfill that request.

1. Digitisation: The agent converts voice audio into text using speech-to-text technology.

2. Understanding: It uses NLP to analyse the text and identify the user's intent (e.g., "book a demo" or "technical support").

3. Action: Based on the intent, it triggers a workflow, such as routing the call, retrieving data from a CRM, or providing a spoken answer.

4. Learning: Machine learning algorithms allow the agent to improve accuracy over time based on past interactions.

How does it work in customer communication?

Virtual agent software is a customer communication system using AI to complete call tasks, route conversations, and manage follow-up work across channels. It goes beyond simple automation by understanding context and intent, allowing it to perform work that previously required human intervention.

Quick facts about virtual agents

• Primary function: Automates voice and text-based workflows before, during, and after interactions.

• Technology: Uses Natural Language Processing (NLP) and Machine Learning (ML) to understand and act on intent.

• Deployment: Integrates with CCaaS (Contact Centre as a Service) platforms and CRMs.

• Value add: Reduces manual data entry and lowers average handle time (AHT).

How do virtual agents handle call tasks across the customer journey?

From the moment a customer dials your number, a virtual agent is active. Initially, it acts as a gatekeeper, determining the caller's intent and routing them to the correct department without the clunky experience of a traditional phone tree. During the conversation, it shifts roles to become an AI call assistant, listening in to transcribe the call and surface relevant information to the human agent. Finally, once the call hangs up, the virtual agent automatically logs the call summary and next steps into your CRM, ensuring no detail is lost.

Virtual agents vs. chatbots vs. live agents: What’s the difference?

Many buyers confuse virtual agents with chatbots. While both use AI, virtual agent software platforms are typically more advanced, capable of handling complex voice interactions and integrating deeply with business workflows, whereas chatbots are often limited to text-based FAQs.

How do AI virtual agents support sales and support teams?

The impact of virtual agents is best understood through the specific jobs they do for your teams. They act as force multipliers, handling the necessary but time-consuming tasks that slow down your top performers.

Core use cases for virtual agents

• Inbound call routing: Intelligently directing calls based on caller history and intent.

• Lead qualification: Asking preliminary questions to ensure sales reps talk to qualified prospects.

• FAQ resolution: answering common questions like business hours or order status without human intervention.

• Real-time coaching: Prompting agents with battle cards or answers during a live call.

• Automated admin: Logging notes, summaries, and tags into the CRM.

What are some pre-call tasks AI agents automate for support and sales calls?

Before a human ever says "hello," the AI is at work. For support teams, this means identifying the customer and pulling up their recent ticket history so the agent is prepared. For sales, an AI call assistant can screen inbound leads, checking them against your ideal customer profile (ICP) and routing high-value prospects to your best closers immediately.

In-call assistance through coaching and real-time context

During the conversation, the virtual agent acts as a whisper in the rep's ear. If a customer mentions a competitor, the AI can instantly surface a battle card with talking points. If a support agent is struggling to resolve a technical issue, the AI can suggest relevant knowledge base articles based on the conversation's context. This live guidance helps standardise performance across the team, ensuring every rep performs like a top performer.

Post-call follow-up and CRM updates completed automatically

The most repetitive part of any sales or support role is the "after-call work" (ACW). Virtual agents can eliminate this by automatically generating accurate call summaries, identifying action items, and syncing this data directly to your CRM. This call summarisation intelligence ensures that your data is clean and consistent without your team having to type a single word.

Benefits of using virtual agents for business

Why are businesses investing in virtual agents? The ROI comes from three main areas: efficiency, data accuracy, and customer experience.

• Reduced manual data entry: By automating call summaries and CRM logging, virtual agents save reps 30-60 minutes per day, allowing them to focus on selling and support.

• Faster response times: AI agents answer immediately, 24/7, eliminating wait times for routine enquiries and ensuring no call goes unanswered.

• Cost-effective scalability: Virtual agent platforms allow you to scale support capacity during peak times without the cost of hiring and training temporary staff.

• Better visibility for managers: With every call transcribed and categorised by AI, managers gain structured insights into customer sentiment and agent performance without listening to hours of recordings.

Reduced manual data entry and better CRM hygiene

When humans log calls, variance is inevitable. Some take detailed notes; others write nothing. Virtual agents standardise this process. And by integrating with your CRM, every interaction is logged with the same level of detail and structure. This data hygiene is critical for leadership to make informed decisions based on accurate information.

Faster response times and fewer missed calls

Customers expect immediate answers. A virtual agent ensures that even when your team is busy or offline, the customer is acknowledged, and their basic needs are addressed. This reduction in missed calls translates directly to revenue retention and customer loyalty.

Better visibility for managers through structured insights

With AI capturing and categorising every call, managers gain unprecedented visibility. You can see exactly why customers are calling, which objections are stalling deals, and which technical issues are causing the most friction. These structured insights allow you to coach proactively rather than reacting to fires.

How virtual call agents differ from typical call automation

It is easy to confuse AI agents with older forms of automation. Here is how to tell them apart:

• Rule-based automation: Simple "if this, then that" logic. It cannot handle deviations from the script.

• IVR (Interactive Voice Response): The traditional "press 1 for sales" menu. It is rigid and often frustrating for callers.

• AI agents: Systems that use NLP to understand spoken language and intent, allowing for fluid conversation and complex task execution.

• Multi-agent AI workforces: A coordinated ecosystem of specialised AI agents (e.g., one for routing, one for coaching, one for data entry) working in harmony.

What virtual agent software includes and how to evaluate it

Not all AI is created equal. When evaluating a solution for your business, look beyond the marketing hype and focus on operational capabilities.

Essential capabilities to look for in AI call assistants

Use this checklist when demoing potential software:

• Real-time transcription: Can it transcribe accurately as the person speaks?

• Intent detection: Can it understand why someone is calling, not just what they said?

• Context awareness: Does it remember previous interactions?

• Seamless handoff: Can it transfer to a human with full context attached?

• Customisable workflows: Can you build specific flows for your unique business needs?

• Post-call automation: Does it summarise and log calls automatically?

Integration requirements for Salesforce, HubSpot, and help desks

Your phone system cannot live in a silo. A robust Salesforce phone integration or HubSpot calling integration is non-negotiable. The virtual agent must be able to read data from these systems (to route calls) and write data back to them (to log activities). This bi-directional sync is what allows for true workflow automation.

Security and compliance questions IT leaders will ask

AI involves processing voice data, which raises valid security concerns. Ensure your vendor can answer:

• Is data encrypted in transit and at rest?

• Do they comply with SOC 2, GDPR, and HIPAA (if applicable)?

• How is voice data used? (Ensure your proprietary calls aren't training public models).

How virtual agent automation improves the work before, during, and after calls

To maximise the value of a business phone system for SMB, you need to think of the call as a three-stage process.

Before the call: Qualification, routing, and intent detection

The work starts before the phone rings. An AI agent can screen inbound numbers against your CRM to identify VIPs or open support tickets. It can ask qualifying questions to ensure that your sales team is only spending time on leads that meet specific criteria, routing the rest to self-service or junior reps.

During the call: Guidance, summarisation, and support

While the rep is speaking, the AI is listening. It provides a safety net, offering answers to tough questions and ensuring compliance with scripts. It also tags key moments in the conversation - like a pricing objection or a feature request - making it easy to review later.

After the call: Data entry, ticket updates, and follow-up tasks

Once the call ends, the AI finishes the job. It drafts a follow-up email for the rep to review, updates the deal stage in the CRM, and logs the call outcome. This customer support software that integrates with your tools ensures that the administrative burden is lifted from the human agent.

How Aircall’s AI Agent Workforce enhances virtual agent value

Aircall moves beyond the concept of a single "bot" to a model of specialised agents, each designed for a specific function within your team. This AI Agent Workforce mimics the structure of a high-performing human team.

AI support agent for resolving issues faster

This agent sits on your front line, resolving Tier 1 issues without human involvement. It frees up your call centre software for support team to focus on complex, high-empathy cases.

AI receptionist for routing calls intelligently

Forget "Press 1 for Sales." The AI Receptionist asks, "How can I help you?" and routes the caller based on their spoken answer, creating a smoother, faster experience.

AI SDR for qualification and outbound readiness

By handling the initial qualification, the AI SDR ensures that your human account executives are fed a steady diet of sales-ready leads, maximising the efficiency of your sales dialer for outbound team.

AI sales coach for improving rep performance in real time

Instead of waiting for a weekly 1:1, reps get feedback in the moment. The AI Sales Coach helps new hires ramp faster and ensures tenured reps stay sharp.

AI analyst for summaries, insights, and system updates

The AI Analyst works in the background, turning unstructured voice data into structured reporting. It gives you the "why" behind your metrics.

How to implement virtual agents effectively, generally

Implementing a virtual agent doesn't have to be a massive overhaul. Follow this step-by-step plan to ensure a successful deployment:

1. Define your use cases: Identify high-volume, low-complexity tasks (like password resets or scheduling) that AI can handle.

2. Map your call flows: Visualise the customer journey. Where should the AI intervene? Where should it hand off to a human?

3. Clean your data: Ensure your CRM and knowledge base are up-to-date so the AI has accurate information to work with.

4. Test with real conversations: Don't launch to 100% of your traffic on day one. Route a small percentage of calls to the virtual agent and review transcripts for accuracy.

5. Monitor and refine: Use analytics to track success rates. If the AI misinterprets a specific phrase, update its training data.

Here is how to implement virtual agents in an existing phone system or CCaaS stack

1. Preparing data, call flows, and CRM/Help desk mappings

2. Testing AI agent performance with real conversations

3. Tracking performance with analytics and coaching feedback loops

4. Tracking performance with analytics and coaching feedback loops

Preparing data, call flows, and CRM/Help desk mappings

Start by mapping out your ideal customer journey. 

• Where is the friction? 

• What data do you need to capture? 

• Ensure your CRM fields are clean and ready to receive data from the AI.

Testing AI agent performance with real conversations

Don't launch 100% of your traffic on day one. Route a small percentage of calls to the virtual agent and review the transcripts. 

• Is it understanding intent? 

• Is the tone right?

• Iterate based on real interactions.

Tracking performance with analytics and coaching feedback loops

Use the data generated by the AI to refine its performance. If the AI is misclassifying a certain type of call, adjust the parameters. Treat your virtual agent like a new employee that needs coaching and feedback to improve.

Best practices for virtual agent deployment

• Always offer a human off-ramp: Never trap a customer in an AI loop. Always provide an option to speak to a live agent if the issue becomes complex or the customer becomes frustrated.

• Be transparent: Let customers know they are speaking with an AI agent. Trust is built on transparency.

• Focus on "After-Call Work" (ACW): One of the highest-value deployments is using virtual agents to automate the note-taking and tagging that happens after a call, as this requires zero change to the customer experience but saves massive amounts of rep time.

Top virtual agent software providers: What to look for

When comparing virtual agent solutions available in the market, look for platforms that offer more than just a "bot." The best solutions provide a comprehensive workforce of specialised AI agents.

Key capabilities to evaluate:

• Real-time transcription: Can it transcribe accurately as the person speaks?

• Intent detection: Can it understand why someone is calling, not just what they said?

• Seamless handoff: Can it transfer to a human with full context (summary + sentiment) attached?

• CRM Integration: Does it natively sync with Salesforce, HubSpot, and help desks?

• Security: Is the platform SOC 2 and GDPR compliant?

What industries benefit from virtual agents?

While any business with high call volumes can benefit, specific industries see faster ROI from virtual agent deployment:

• SaaS & Technology: For automating technical support triage and qualifying inbound sales leads.

• E-commerce & Retail: For handling order status enquiries, returns, and FAQs during peak seasons.

• Financial Services: For secure identity verification, balance checks, and appointment scheduling.

• Healthcare: For patient appointment reminders and intake form automation.

• Real Estate: For instantly qualifying inbound leads and scheduling viewings 24/7.

Examples of virtual agent impact on sales and support teams

Seeing is believing. Here is how a typical mid-market team transforms after implementing an AI Agent Workforce.

Case Study: TechFlow Solutions (Mid-Market SaaS)

• Challenge: High missed call rate (20%) and poor CRM data quality due to rapid growth.

• Solution: Implemented Aircall AI Receptionist and AI Analyst.

• Outcome:

  • Missed calls reduced to <2% by utilising AI for overflow and after-hours routing.

  • Manual data entry reduced by 90% thanks to automated summarisation and tagging.

  • Proprietary Insight: The team recovered 15 hours per week per manager previously spent on listening to call recordings, shifting that time to active coaching.

When virtual agents aren’t enough and where humans remain essential

AI is powerful, but it is not a replacement for human connection. The goal is a human-in-the-loop framework.

• Empathy and emotion: When a customer is angry or distressed, a human is needed to de-escalate and build rapport.

• Complex problem solving: For unique, multi-layered issues that fall outside the training data, human judgment is essential.

• Strategic negotiation: Closing large deals or navigating complex partnerships requires human intuition and relationship skills.

Virtual agents handle the routine so humans can handle the exceptional.

How the future of virtual agents is shifting toward coordinated AI workforces

We are moving away from isolated tools toward integrated ecosystems. The future lies in the multi-agent model, where different AI agents collaborate. Your AI Receptionist will talk to your AI Analyst, which will inform your AI Sales Coach. This coordinated effort, central to Aircall’s AI strategy, creates a seamless layer of intelligence that permeates every aspect of your customer communication.

How Aircall’s AI Agent Workforce enhances virtual agent value

Aircall moves beyond the concept of a single "bot" to a model of specialised agents, each designed for a specific function within your team.

Frequently asked questions

How do virtual agents improve customer service? 

Virtual agents improve service by answering calls instantly, 24/7, and removing the need for customers to wait on hold for simple queries. They also ensure human agents are less stressed and better prepared for complex calls.

Are virtual agent platforms cost-effective? 

Yes. By automating routine tasks, businesses can reduce their cost-per-contact significantly. A virtual agent can handle infinite concurrent calls for a flat software fee, whereas scaling human teams requires linear cost increases in salaries and overhead.

What is a virtual agent in customer communication?

A virtual agent is AI software that handles routine call tasks, routes conversations, supports reps in real time, and completes post-call actions like summaries and CRM updates.

How does an AI virtual agent differ from a chatbot?

Chatbots handle text interactions. AI virtual agents work in voice workflows, assisting during calls, routing enquiries, and updating systems automatically.

What are the main benefits of virtual agents?

They reduce manual entry, shorten handle times, prevent missed calls, and give managers clearer insights for coaching.

Do virtual agents replace human agents?

No. They automate repetitive work so humans focus on complex conversations, relationship-building, and judgment-based tasks.

How do AI call assistants integrate with CRMs?

They sync call data, summaries, and action items into systems like Salesforce or HubSpot without manual entry.

Is virtual agent software secure?

Yes. Leading platforms follow encryption, access controls, and data storage standards to meet IT and compliance requirements.

What teams benefit most from virtual agents?

Sales and support teams that manage high call volumes, rely on CRM data accuracy, and need faster coaching cycles.

How do I implement a virtual agent in my existing call system?

Leading virtual agent software like Aircall offers native "one-click" integrations with major CRMs like Salesforce and HubSpot. This allows the virtual agent to read and write data to your system of record without complex coding.

Try AI Voice Agent today

The era of manual call logging and rigid phone trees is over. By adopting a virtual agent strategy, you aren't just buying software; you are hiring a digital workforce that works 24/7 to support your human team. Whether it's eliminating admin work, catching every inbound lead, or providing the insights you need to grow, the value is clear. The next step is to evaluate your current stack and identify where AI can start doing the work for you now.

Published on December 31, 2025.