AI for Call Centers: Features, Use Cases & the Best Solutions

While it may feel as if you’re not yet using artificial intelligence (AI) in your call center, you’re somewhat lagging. The reality is that behind all the marketing hype is a much smaller number of early adopters than you think.

The use cases and benefits are starting to become clear, and organizations that always embrace new technology are implementing and realizing the productivity and customer satisfaction gains.

In some cases, however, you may be using AI without knowing what’s powering it. If the future of customer service lies in AI call centers, it’s vital that we know exactly what’s possible and when to use it.

What Is AI in a Call Center Context?

AI isn’t something to fear in call centers. In fact, it’s something we should embrace and welcome with open arms when implemented and adopted correctly.

AI solutions introduce automation, intelligence, and real-time insights to the voice channel. This means there’s less reliance on time-consuming, repetitive tasks and more chances to delight customers with smooth, efficient interactions.

When it comes to using AI for customer service, sales, or support, there are a plethora of tools and functions at your disposal.

Core AI technologies include the following.

Speech recognition

During the customer journey, you may have opportunities to speed up the routing process. Instead of asking customers to press 1 for sales or 2 for support, only to then ask them further queries to route them to different departments, choose to shortcut the key presses and reading of menus by asking them one simple question: “What’s your reason for calling today?”

From here, your customer says they have a problem with their broadband router, and you can:

• Transfer them to a broadband specialist
• Program automatic troubleshooting questions
• Read regular resolutions for them to try while they hold for an advisor

This simple component, using AI behind the scenes, means there’s no need for customers to wait in a queue or get transferred to incorrect agents. The removal of multiple transfers means there’s less time spent repeating themselves and a lower chance of customer frustration.

During the call, this same speech recognition technology converts live audio to text for transcriptions and customer sentiment detection. Mid-call, if negative sentiment is detected, supervisors get real-time notifications that they may need to review and intervene.

At the end, calls get flagged for quality assurance with obvious issues highlighted in the transcription. There’s no need for call center managers to listen to the entire 10-minute call. Instead, they can search for the negative word detected (thanks to transcription) and review what went wrong.

Real-time Agent Assist

This same speech recognition is constantly processing call data to surface contextual information to agents during live customer calls. As well as flagging when conversations are going south, one specific feature allows agents to get real-time notifications on-screen to coach them through live scenarios.

Agents benefit from AI Agent Assist most in sales or support environments:

• Sales: When a customer mentions their contract is near the end, Agent Assist can provide all the renewal details in the blink of an eye. Suggested next steps and even customer service scripts can appear on-screen to coach agents to an optimized conversation.
• Support: When an agent is struggling to resolve an issue, Agent Assist steps in with frequent resolutions or suggested escalation paths. During these interactions, when conversations get heated, Agent Assist suggests empathetic phrases to regain control of the situation.

Natural language processing (NLP)

Behind the scenes, features like AI Agent Assist and speech recognition are using an NLP engine to understand the intent behind spoken phrases for smarter interactive voice response (IVR) and bot responses.

NLP is a branch of AI that enables computers to understand, interpret, and respond to human language in a way that feels natural, not robotic. If you’re using any form of smart IVR system or anything that asks for a customer’s voice input, an NLP system is processing it to gauge the best output. This might be transferring a call, providing self-service options, redirecting to an online knowledge base, or loading a payment processing interaction.

Predictive analytics

In the past, call center analytics reported on basic volume-based metrics like the number of missed calls and time spent on the phone.

Today, with AI using historical data to forecast call volumes and agent needs, you can use what’s happened in the past to inform the future.

With predictive analytics, you can best ensure:

• Agent availability: Ensuring you have the right number of agents scheduled at peak times to meet customer expectations without overstaffing or underutilizing resources
• Forecast contact volume: Analyzing historical data and trends to predict customer interactions, allowing for proactive staffing adjustments to improve response times and reduce unnecessary operational costs
• Optimized revenue targets: Scheduling top-performing agents during peak hours or for high-value interactions to enhance customer experience and maximize revenue opportunities

AI-powered call scoring

By analyzing customer input, agent responses, and the tone of the conversation, AI-powered call center solutions can evaluate every call using preset criteria, giving managers actionable insights.

By ranking the words with negative sentiment versus positive and neutral, as well as things like call flow and raised voices, you get a score for each call. Using this information, you can prioritize proactive outreach to impacted customers and plan nuanced training for agents who become repeat low scorers.

Conversational AI

If you can identify early on that a human agent doesn’t need to be involved with a call, you should use that to alleviate the pressure on call queues and agent performance.

Conversational AI is literally enabling your customers to have a conversation with AI. This technology powers virtual agents that answer FAQs or collect precall data. So for customer inquiries like paying a bill, checking opening times, or anything else that doesn’t need human intervention, preprogram and enable machine learning algorithms to introduce self-service for basic queries.

You may have used conversational AI when you last called your bank. Instead of asking you to hold for ages, the system asks for your reason for calling. If you said, “Pay a bill”, it completes the identity and verification workflow using your account number and security questions. It then looks up any outstanding amounts and asks you if you want to pay the full balance. The transaction completes without the need for a human.

The Top 5 Use Cases for Call Center AI

Below are the key uses of call center AI:

1. AI call summaries & auto-transcription

NLP and automatic speech recognition work together to transcribe voice calls in real time. Generative AI is the term used for the type of AI that creates an output and then condenses those transcripts into structured call summaries, highlighting key action items, sentiment, and intent.

Where it helps:

• Reduces post-call wrap-up time
• Ensures every conversation is documented consistently
• Improves manager visibility without listening to every call

2. Smarter call routing with AI-enhanced IVR

AI-powered IVR systems can understand natural language input (via NLP), letting callers say things like, “I want to update my billing address” and be routed appropriately.

When integrated with CRM or website behavior (e.g., the last page visited), AI can use this data to guide routing logic in real time.

Where it helps:

• Increases first-call resolution
• Shortens average handle time by getting customers to the right agent faster
• Reduces call transfers and repeat calls

3. Real-time agent coaching

Real-time speech analytics tools can detect when agents speak too fast, use filler words, or miss compliance statements. These systems surface nonintrusive on-screen prompts to guide agents during live customer calls. Some even alert supervisors in real time when a call is going off track.

Where it helps:

• Speeds up ramp time for new hires
• Standardizes agent behavior across teams
• Boosts call quality without micromanagement

4. AI-powered quality assurance

AI scoring tools analyze call recordings using preset criteria like greeting usage, empathy, script adherence, and prohibited phrases.

Some systems allow for customizable scorecards or industry-specific templates, making it easy to evaluate every call fairly and automatically.

Where it helps:

• Uncovers complex issues sooner
• Eliminates bias from manual QA processes
• Saves QA teams hundreds of hours per month

5. Voicebot & live agent collaboration

Voicebots powered by conversational AI can handle common precall tasks, identity verification, account lookup, or simple FAQs before handing off the call to a live agent with full context.

These AI systems use intent detection, voice biometrics, and CRM integration to gather relevant customer data and ensure seamless transitions.

Where it helps:

• Improves the caller experience by reducing friction
• Gives call center agents a head start with contextual data
• Frees up human reps for higher-value conversations

Top 5 AI Call Center Solutions

The call center software solutions that follow are at the top of their game when it comes to making AI accessible and easy to implement.

1. Nextiva

Nextiva combines voice intelligence, real-time coaching, and unified communications in a single AI platform. Specializing in small to medium businesses, we’ve invested thousands of hours into bringing AI call center solutions to businesses just like yours.

While the power of what AI can do is great, the usability and configuration remain simple. For example, Cedar Financial uses Nextiva to boost its agent productivity by 471%.

AI – Cedar Financial – Nextiva Sales Testimonals

Key features:

• Real-time call transcription and speech analytics
• AI-generated call scoring and summaries
• Intelligent IVR and routing with CRM data
• Visual agent dashboards with insights on tone, script use, and talk time
• Scales from SMB to enterprise, with 99.999% uptime
• 24/7 U.S.-based customer support

Ideal for: Teams looking to modernize voice support without patching together multiple tools

2. Invoca

Invoca excels in post-call AI: scoring, routing, and conversation intelligence. It’s ideal for performance-driven environments like sales and marketing. You get both team and individual agent scores alongside suggestions based on customer behavior and traditional call center metrics.

Key features:

• AI call scoring using pretrained industry templates
• IVR and routing based on the caller’s web behavior
• PreSense: screen pops with caller intent before pickup
• Redaction of sensitive call data (SSNs, credit cards)
• Seamless integration with CRMs and ad platforms

Ideal for: Sales and marketing teams that want deep call attribution and post-call intelligence

3. Dialpad AI

Dialpad’s AI acts like a coach during live calls, surfacing suggestions, catching filler words, and helping agents improve on the fly. Often associated with sales teams thanks to its dedicated Dialpad Sell module, Dialpad has been dabbling in AI longer than most competitors.

Dan O’Connell, Chief Strategy Officer at Dialpad, back in 2018, spoke about real-time analysis, automation of record-keeping, and automated call transcription. At the time, this was considered revolutionary for call centers.

Key features:

• Live speech coaching and filler word detection
• AI call transcription and wrap-up summaries
• Integrated WFM and quality analytics
• Built-in voice IVR and chatbot options

Ideal for: Call centers looking to train agents in real time and reduce ramp-up periods

4. Talkdesk

Talkdesk is packed with AI features for both self-service and Agent Assist, all tailored to high-volume call centers. With the call center being the primary product for the company, its major focus has been on doing more with less, thanks to the introduction of AI.

Key features:

• Generative AI for call summaries and agent answers
• AI-powered interaction analytics for sentiment tracking
• Prebuilt AI tools for verticals like health care and finance
• Agent Assist to reduce after-call work

Ideal for: Enterprise teams looking for vertical-specific AI tools and scalable automation

5. NiCE CXone

NiCE CXone, formerly NICE with a capital I, leads in AI analytics and workforce optimization, with predictive routing and robust reporting. A specialist in enterprises and businesses with complex staffing needs across multiple regions, NiCE has been focusing on self-service and performance analytics for many years now.

Key features:

• AI-driven call routing
• Real-time and historical dashboards
• Sentiment analysis and quality management
• Deep CRM integrations

Ideal for: Large call centers prioritizing detailed analytics, staffing insights, and long-term performance trends

Nextiva Helps You Integrate AI Into Your Call Center

There’s no escaping that AI is becoming the backbone of modern voice support. In fact, customers are starting to expect it. If you’re not offering self-service IVRs as your first touchpoint, it immediately feels like you’re going to be on a long call.

Customers don’t want to:

• Queue up
• Explain themselves to different agents
• Wait while you pull up relevant account info

From streamlining call flows to analyzing customer conversations, AI enables you to optimize every part of the call center experience. This transforms the customer journey into a smooth one. The knock-on impact further down the line is that customers remain loyal, renew their contracts, and refer you to friends and colleagues.

If you’re just getting started with AI for your call center, you need a trusted partner to make things simple while implementing complexity.

With Nextiva, you don’t need multiple vendors or clunky add-ons to get the most out of AI. You get one platform, purpose-built for voice, that simplifies call center operations at every level.

Thinking about taking your first steps? See how Nextiva can help today.