Call Center Trends for 2026: AI, Voice, Automation, and Risk Intersect

Call centers are changing fast. According to the Vonage Global Customer Engagement Report 2025, just 42% of consumers are very satisfied with their communications with businesses. But they’re embracing change: 25% say they’re likely to try AI-powered support tools for a faster response, a number that will likely continue to grow. And 83% of consumers say they’ve recently used AI-assisted tools like AI-enabled chat and AI-powered search engines. 

This guide breaks down the key call center trends in 2026 and beyond, such as growing call volume, AI adoption, voice automation, fraud prevention, rising CX expectations, and more. 

Why 2026 is a Turning Point for Call Centers

Customer experience expectations are accelerating quickly, and call centers are feeling the pressure. “Companies are no longer judged only by the products they sell. They are judged by the speed, quality, and consistency of their customer experience,” according to Intelliverse. 

With this shift in mind, businesses are reimagining their CX tech stacks and evaluating how the contact center fits into the business strategy. “Enterprises are finally waking up to the latent analytic value in their centers and viewing them as a tool for making desirable things happen, instead of a passive (and expensive) necessity to keep customers at bay,” says Keith Dawson, who leads customer experience expertise at ISG Research.

Even customer interactions themselves are growing in complexity. “Each interaction requires more steps, more systems, more context, and more judgment,” says Peter Hornberger, VP of Sales at Brightmetrics. “Customers are more informed, but not always clearer. Digital journeys have expanded, but they also introduce more failure points and partial attempts that later arrive in assisted channels.”

Higher customer expectations and increasingly complex customer interactions mean that contact centers must adapt. Here are some trends that will define what’s next for call centers.

Call Volumes Are Climbing Faster Than Teams Can Scale

87% of consumers say phone calls are their preferred channel for more complex customer support issues. That said, 75% of consumers prefer self-service for simple issues like password resets and order tracking. The problem is that your agents are already stretched to the maximum. Not only do call centers need to meet this increase in demand, but they also have to deliver all-star service without sacrificing speed. That's a tall order, especially considering that just 7% of executives plan to prioritize this channel over the next few years. (ServiceNow)

61% of contact centers report more emotionally charged customer interactions. So, not only does your team have to manage higher call volumes, but the tone of those calls is also harder to handle. Without better tools, your team can’t deliver consistent service, especially to upset customers. (Calabrio)

When a call goes wrong, how your agent responds can make or break the relationship. Research published in Sustainability in 2025 determined that rapport is a significant predictor of cognitive empathy and emotional empathy towards service providers, and these kinds of empathy influence customer satisfaction and long-term loyalty. The study also showed that service authenticity increases the power of both empathy and rapport: customers who perceived agents as sincere (rather than reading from a script) were more likely to empathize with the situation and be loyal after the fact. Translation for call centers: training your agents to build authentic rapport, particularly in times of service recovery is key to retaining customers. (Sustainability via MDPI)

Agents Are Burning Out Under Growing Pressure

High employee turnover is one of contact centers’ largest pain points. 87% of agents say their job is highly stressful. Average agent tenure sits between 13-15 months. (Servion)

You can’t simply hire your way out of this problem, either. Onboarding costs for one customer service rep can range from $10,000-$20,000. However, the total impact, including lost productivity, can reach $46,000 for each new agent hired. This makes retention equally as important as hiring and automation. (Insignia Resource)

Today there are approximately 3.6 million contact center employees in the United States, which is about 2.5% of the total U.S. workforce. But more than one-quarter (27%) of call centers have 30 or fewer agents. Because more call centers use business process outsourcing (BPO) to save money, real wages for U.S.-based customer service agents have declined 3% in the last 10 years. This indicates that most call centers don’t have access to advanced or enterprise technologies that can help meet customer demands. (Communications Workers of America / Call Centre Helper)

On the other hand, only 7% of contact centers have more than 1,000 agents. The majority of teams don’t have the resources to scale up and handle increased demand. (Call Centre Helper)

Companies Are Deploying AI Faster Than They Can Operationalize It

Nearly all contact centers (98%) are using AI solutions today, but that doesn’t mean those tools are being leveraged. Call centers are deploying AI technology more as small tests and not enterprise-wide implementations that actually provide value. (Calabrio)

88% percent of contact centers are deploying AI at scale. However, while most companies are using AI-powered tools, only 25% have fully integrated AI automation into their daily workflows. (CMSWire)

Artificial intelligence is being used by 78% of companies across at least one business function. While these tools are being used, many contact centers are still struggling to “operationalize” AI when it comes to live agent interactions. (McKinsey)

AI Tools are still in the “trial phase” for most call centers, but adoption is quickly on the rise. 91% of businesses with over 50 employees are currently using AI chatbots at some stage in the customer experience. And customers are increasingly on board: 75% say they prefer AI chatbots for simple inquiries like order tracking, FAQs, and account questions. (Dante)

Voice AI Is Transforming How Contact Centers Operate in Real Time

Voice AI now handles 19% of inbound contact center volume. That’s an increase from just 6% in 2024. (Digital Applied)

By 2028, 70% of customer interactions will start with conversational AI, according to research by Gartner. Voice and conversation-driven interactions will become the entry point into the customer experience. (Gartner)

Traditional call center benchmarks such as time to resolution and answer speed are no longer the sole concerns. They also care about customer emotions. In fact, the global sentiment analysis market was valued at $4.6 billion in 2025 and is expected to reach $11.2 billion by 2032. (ResearchandMarkets)

Voice AI is the future, and adoption is on the rise, too. Interaction and speech analytics usage rose from 28% in 2022 to 37.5% in 2023, so teams clearly want to better understand voice data at scale. (Call Centre Helper)

Automation is great, but call centers still need visibility. It’s no wonder that high-performing call centers are 4 times more likely to use real-time performance monitoring tools to help with visibility. (QEvalPro)

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AI Automation Promises Massive Gains, but Delivery Varies

There’s been an aggressive push toward automation, and for good reason. Experts predict that conversational AI will reduce agent labor costs by $80 billion by the end of this year. (Gartner)

AI is already proving productive in the call center. McKinsey reports that one utility reduced its call volume by nearly 20% and shaved up to 60 seconds off customer authentication times just by adding an AI voice assistant into its current call routing process. Faced with opportunities like these, it's no wonder call center leaders are scrambling to allocate dollars, particularly in a field plagued by turnover. (McKinsey)

Agentic AI is coming to customer service whether you realize it or not. Cisco’s recently released 2025 global study, which surveyed just under 8,000 business and technology professionals, projects that over half of all customer support interactions will be powered by agentic AI by mid-decade, and that figure jumps to 68% by 2028.If you’re a vendor or contact center that hasn’t started developing agentic AI assistants already, you’re late to the game.  (Cisco)

For 66% of businesses, it took more than six months to begin seeing ROI from recent AI implementations. Less than a third are using AI to generate insights, and just over a quarter are utilizing AI within knowledge management. Meanwhile, 62% of contact center leaders say that the successful implementation of AI is critical to their roles, and 27% believe their jobs are at risk if AI initiatives fail to deliver results. (Verint)

Speed doesn’t always equal progress. From 2022 to 2024, Klarna laid off around 700 customer service agents and replaced them with an AI chatbot powering 2.3 million chats per month. Early reports boasted massive productivity gains. Then customer satisfaction plummeted. It’s a headline-making case of automation surpassing experience design. (InflectionCX)

Hybrid Human-AI Workflows Still Come Out on Top 

Most industry leaders have landed on a compromise. Natterbox's 2026 Contact Center Benchmarks report (based on 58.2 million calls and survey of 178 contact center leaders) revealed that 76% have implemented a Human- in-the-Loop model. AI handles tedious, high volume, low stakes work but agents own emotional, high-risk interactions. And the numbers support the rationale: 91% of complex interactions are agent-owned, while AI owns FAQ questions, troubleshooting and anytime access. (Natterbox)

Customers still want to talk to a person. Even when AI performs well, most customers still prefer to talk to a human. Metrigy's Customer Experience Optimization 2025-26 Report discovered that when given the option 84.7% of consumers want to interact with a human vs. an AI agent. Even more revealing: when customers were guaranteed their issue could be resolved entirely by AI 80.1% still preferred a human agent. (Metrigy)

Humans still win on the metrics that matter most. Speed and accuracy rank as the top two things customers want from a service interaction, and per Kinsta's research, they still credit those attributes to humans overwhelmingly. When asked which agents resolve problems faster, 78.3% of customers said human agents. When asked which agents are more accurate, 84.0% of customers chose humans. If you're heavily weighting AI solutions in your contact center to save time and improve efficiency, keep those numbers in mind. (Kinsta)

Bad AI experiences can cost your business customers. Customers aren’t just saying they prefer humans, they’re taking action. Research from Kinsta shows 49.6% of customers would leave a company’s service entirely due to AI-driven customer service and 41.5% would pay more money for the ability to speak to human representatives. The risk of over-automating your customer experience is potential churn and lost revenue. (Kinsta)

AI is freeing humans up for higher-value work. If there’s one powerful argument for the hybrid model, it’s what AI can free humans up to do. Salesforce found that 93% of service pros at organizations that use AI say it saves them time. By handling simple queries and routine tasks, AI clears the way for human agents to focus on relationship-building and complex problem-solving, the work that's both harder to automate and more meaningful to customers. (Salesforce)

Metrics Are Evolving Alongside AI Adoption

Contact centers still focus on traditional metrics such as abandonment rate, AHT, quality, ASA and agent occupancy. These numbers matter, but AI support and automation will change current standards. (ICMI)

First call resolution continues to be one of the top measures tracked by call centers. According to SQM Group's latest 2024 FCR benchmark research, which analyzes data from over 500 North American call centers, a "good" FCR rate is between 70-79%. World-class call centers have achieved an FCR percentage of 80% or higher. On average, each 1% increase in FCR equates to $286,000 in annual savings for a typical midsize call center. (SQM Group) 

The range for a healthy call abandonment rate is between 2% and 5%. Any number higher than 8% may indicate issues in operations. (Lorikeet CX)

Naturally, taking care of your customers should be your primary focus. But you'll also want to keep an eye on AI-specific performance metrics. Containment rates are one of those KPIs. AI containment ranges from as low as 20-40% for rule-based bots just getting started, to 70% or more for mature AI. Given this, it makes more sense to gauge progress against your past performance rather than a rigid benchmark. (AthenaAI)

Companies Are Chasing ROI Through Automation

Customer self-service only costs $1.84 per interaction vs. $13.50 for live agents. Sounds too good to be true? Consider that only 14% of self-service experiences completely resolve the customer’s issue. Automated service is far from perfect, and this disparity shows why it’s so important to monitor for quality. (Gartner / Gartner)

AI isn’t a magic bullet, but it can deliver amazing ROI if you implement it well. In a recently released 2025 Forrester Consulting study sponsored by PolyAI, enterprise customers shared that they experienced a 391% ROI from their voice AI deployment over three years and saw their investment pay for itself in less than six months. (PolyAI)

When applied successfully, AI can fundamentally change how businesses operate for the better. Research from McKinsey discovered that contact centers using generative AI experienced a reduction in total calls by almost 30%, a decrease in average handle time by over 25%, and an increase in first call resolution by 10-20 percentage points without sacrificing service quality. (McKinsey)

Enterprise adoption of AI is common, but true maturity is not. 92% of companies use AI technology in some capacity, according to Nextiva's 2025 Leader's Guide to CX Trends, but only 9% believe their AI implementation is mature. The difference between those two numbers is significant in ways you might not expect: businesses that have achieved AI maturity are over three times more likely to feel that they're receiving strong value from their investment. (Nextiva)

AI Is Introducing New Risks

Call center automation does a lot of good, but AI isn’t without its problems. 71% of contact center leaders say ethical concerns, data privacy issues, and regulatory challenges will limit AI adoption. (Calabrio)

Unfortunately, some call centers believe the risks just aren’t worth it. In fact, experts believe agentic AI abandonment will be an upcoming call center trend. Gartner predicts that more than 40% of agentic AI projects will be abandoned by 2027 due to cost, unclear value, and lack of controls. (Gartner)

The same tech powering contact center transformation is also giving fraudsters better tools than ever. Deloitte's Center for Financial Services predicts generative AI-enabled fraud losses in the U.S. will balloon to $40 billion by 2027, up from $12.3 billion in 2023, which is a compound annual growth rate of 32%. (Deloitte) 

Only 28% of contact centers say their teams have deep knowledge of data privacy best practices. The takeaway for contact center leaders is simple: If your AI plan doesn’t include safeguards, it’s not a plan at all. (Zendesk)

Of course, keeping everything secure can be difficult when your stack is spread across different platforms. Only 3% of contact centers operate on one platform, with teams using an average of 3.9 tools. With such fragmented visibility, it can be difficult to identify compliance and risk levels throughout a call center. (Puzzel)

Fraud Is Increasing Across Voice Channels

Unfortunately, scammers are using voice channels to commit crimes. 43% of business leaders say fraudsters increased their attacks on call centers over the past year. (HYPR)

Fraud exposure on voice calls is rising. High-risk calls into U.S. call centers increased 33% year-over-year, going from 4.5% to 6.0% of total calls from 2023 to 2024. Few call centers are prepared for this level of fraud. (HYPR)

Agents can’t be expected to know when to flag a fraudulent call just based on intuition. Across 56 studies, with more than 86,000 participants, one meta-analysis published in 2024 in Computers in Human Behavior Reports found that humans were barely better at detecting deepfakes than flipping a coin. Average accuracy was only 55.5% across studies, which is not statistically different from chance. With audio specifically, humans fared even worse, with a wider margin. The takeaway for contact center leaders? There’s no substitute for voice authentication and AI-powered monitoring tools. (ScienceDirect)

Most concerning for the industry overall: AI-related complaints and losses accounted for 22,364 complaints and almost $893 million in one year. This is a category that scarcely existed in IC3 reports three years ago. Tech support fraud and computer repair services accounted for close to 48,000 complaints and $2.1 billion. They rank in the top five crime categories by dollar amount. If you’re running a contact center that houses customer personal information and conducts financial transactions at scale, those numbers should speak for themselves on why to take preventative measures with authentication, monitoring, and fraud detection. (FBI IC3 2025 Annual Report)

Fraud threats to contact centers are coming not only from outside attackers but are also coming from within contact centers themselves. According to the FBI's 20th Annual Internet Crime Report (IC3), illegal call center activity resulted in more than 80,000 complaints with over $2.9 billion in losses in 2025. Often run by organized crime groups, these fraudulent call centers pretend to be customer service representatives from legitimate brands to steal money and sensitive information from victims. (FBI IC3 2025 Annual Report)

Organizations Are Rethinking How They Verify Callers

Scammers have realized phones are a prime avenue for impersonation, with call centers becoming the go-to targets. You can see the response in action: the voice biometrics market is expected to expand from $1.1 billion in 2020 to $3.9 billion by 2026, as companies scramble to replace antiquated knowledge-based authentication with solutions that can truly confirm who is on the other end of the line. If a scammer can use widely available AI tools to clone a caller’s voice in seconds, “Please confirm your mother’s maiden name” is no longer a valid security check. (Markets and Markets)

Call centers are starting to realize that knowledge-based authentication doesn't work. Per the Identity Management Institute hackers can correctly guess the answers to standard KBA security questions up to 20% of the time. When guessing won't work, breached data and data scraped from public aggregators can easily be bought. But the greatest irony of all is that KBA's are tougher on real customers than they are on criminals: consumers forget an average of 20% of their answers within six months of creating them. That means in a contact center context, a significant percentage of authentication failures are actual customers being denied access by technology that was hopelessly broken years ago and is now actively harmful thanks to AI voice cloning. (Identity Management Institute)

The anti-fraud solutions meant to protect banks and fintechs are alienating their customers faster than ever. Per Modulate's recently published 2025 State of Voice-Based Fraud survey, conducted in partnership with Banking Dive, 44.2% of organizations say they've experienced higher verification related complaints from legitimate customers. 38.3% say customers trust them less. Both frustrations are the direct result of security friction bleeding into regular service experiences. If your organization can't confidently distinguish between a legitimate caller and fraudster quickly and efficiently, you're paying the price in satisfaction surveys and lost loyalty. (Modulate)

Contact center executives are taking action rather than waiting for the threat to level off. In Modulate’s 2025 State of Voice-Based Fraud survey, 91.5% of respondents said they plan to boost spend on voice fraud prevention solutions, and when presented with a list of capabilities and asked what singular one would provide the biggest boost, AI-powered voice fraud detection came out ahead of the pack. This marks a shift from years past where the industry questioned whether voice fraud was even a legitimate threat. (Modulate)

How Voice-Native AI is Transforming Call Center Operations

AI is going to fuel more and more customer service conversations. But for call centers to win, AI needs to understand conversations like a human would. By using voice-native AI platforms like Modulate, call centers are driving a transformational shift where they mine deeper insights and trigger actions from every interaction.

Gone are the days of transcript-only analysis. Modulate’s Velma voice intelligence platform understands the entirety of a voice conversation. By evaluating tone, pauses, interruptions, pacing, and raised stress levels, Velma can detect frustration, tell if there are risk factors present, determine customer dissatisfaction, and pinpoint behavior changes throughout customer interactions, all in real-time.

Trained on more than 500 million hours of real-world conversations, Velma is effective even in noisy and complex call center environments. See how Velma’s voice intelligence can help your customer service team understand every conversation. 

Frequently Asked Questions

When should contact centers start using AI tools?

AI is not a silver bullet, and it’s only as effective as your processes allow. If your contact center is spinning its wheels on basics like overflowing data siloes, manual QA testing, or inconsistent workflows and procedures, adding AI to the mix will only amplify these problems. Before adopting AI tools, make sure you have solid processes and total visibility into your data, as well as a strategy for monitoring your AI initiatives.

Where do most contact centers go wrong when scaling AI?

Contact centers fail when they scale too fast with too little guardrails. It’s tempting to dive in headfirst to achieve cost savings, but many companies don’t take the time to understand how the AI actually behaves during customer conversations. 

Without the ability to monitor conversations in real time, small problems can snowball. Conversations with customers are especially prone to grey areas and nuance, so risk increases when you don’t have any controls or visibility over the voice experience.

What can we expect from customer service in a world of hybrid AI and human teams?

In the future, customer service teams will use bots to automate busywork and route the rest of the conversation to a human agent. Hybrid AI/human workflows let you automate the mundane stuff while still providing the human elements your customers expect, like empathy and personal connection.

While AI will never replace human customer service agents, bots can take care of mundane tasks to free up your agents.

What role will real-time analytics play in customer experience?

Call centers have come a long way from simply reviewing transcripts and call recordings. Reactive analytics misses the opportunity to improve a call in progress. Real-time analytics can help teams detect customer frustration, risk of escalation, compliance mistakes, and fraud.

What’s the advantage of voice-native AI over transcript-based AI?

While transcript-based AI can analyze the words being spoken after they’ve been converted to text, voice-native AI also pays attention to how something is said. 

Voice-native AI analyzes both speech and acoustic behavior to provide deeper insights about sentiment, fraud, urgency, and conversational dynamics. This includes tone of voice, pacing, interruptions, speech fillers, stress levels, and emotional intensity.