Editorial
The Gist
- AI is expanding its influence in the contact center. From intelligent routing to analytics and chatbots, AI is reshaping how service teams operate and scale.
- Human agents remain essential for complex, high-stakes moments. Even with automation gains, customers still rely on skilled agents for empathy, nuance and personalized resolution.
- AI augments—not replaces—agent performance. Tools like sentiment analysis, QA automation and real-time coaching help agents work smarter, train faster and deliver more consistent experiences.
When it comes to customer service and customer experience (CX), the emergence of AI has made quite an impact in the contact center. That’s true whether it’s through AI-driven analytics, the development of natural language chatbots or functions like intelligent call routing.
Through all the AI-based breakthroughs in the contact center, we have to keep in mind that self-service methods still require a certain amount of the human element to provide superior customer engagement. Highly skilled human agents are preferred when resolving complex issues, or to personalize the experience for a deserving, loyal consumer.
Balancing Automation With Human-Led Service
Yet AI-driven tools can contribute immensely to human customer support efforts, especially when it comes to training and Quality Assurance (QA) techniques. Media reports show that use of AI in Quality Assurance is estimated to become a $4 billion market by 2026, increased from $426 million in 2019. Technology has incorporated call monitoring, analytics and reporting for years, and now AI is refining and evolving those functionalities, and applying them across a range of communications channels like text, email, and chat for superior outcomes in customer engagement.
Table of Contents
- The Skinny on AI-Powered Quality Assurance
- Identifying When to Pivot Strategies
- Multilingual Translations
The Skinny on AI-Powered Quality Assurance
Much of customer engagement still depends on the agent’s ability to navigate and diffuse potentially volatile interactions. The reality of customer service is that the consumer is frequently disgruntled or irate. Even the best agents require training and support to sharpen their interpersonal skills. PwC’s AI Agent Survey shows that only 35% of companies claim to have implemented broad adoption of AI agent technologies, so there is ample opportunity for organizations to take better advantage of these tools and methods.
How AI Enhances Agent Skill Development
AI-based speech recognition and sentiment analysis technology can evaluate speech patterns during customer communications, recognizing when they become strained or emotional. According to reports, sentiment analytics recently edged-out marketing analytics as the top use of AI analytics in contact centers worldwide. Detection and documentation of these variances during agent conversations become part of granular data analytics reports that can be used by business owners to evaluate the performance of agents and the success of their engagements.
The Productivity Gains of Always-On Monitoring
One true benefit of AI is that, unlike live employees, it is tireless. Effective AI-based monitoring can review and aggregate 100% of customer interactions. This is compared to traditional manual quality assurance efforts, which typically can only review a representative amount of their company’s interactions on a regular basis. When using live personnel, it’s prohibitively laborious and time-consuming for employees to devote their time to scrutinizing a comprehensive record of customer engagements. It’s an ill-advised use of manpower, since only a fraction of engagements warrant intervention.
This is a perfect application for AI, where the technology relieves contact center supervisors of rote tasks, yet increases productivity and creates a comprehensive data log that can be used to enhance service.
Related Article: Some Consumers Find Zero Benefit With AI in Customer Service
Identifying When to Pivot Strategies
AI-powered analyses can verify whether agents stay on script or how long it took to resolve an issue. Companies can identify which agents need support, or can detect datapoints such as whether more stressful customer relations occur during peak operations when staffing is short, or in conjunction with a holiday or promotion. This can help business owners pivot their strategies or augment their staff at specific times, accurately addressing the challenges that result in less-than-ideal scenarios. As per survey research, 97% of organizations noted an increase in quality assurance productivity after incorporating AI-powered QA processes (DevQA).
How AI Functions as a Real-Time Coach
This table highlights key areas where AI provides live guidance to agents and improves contact center performance.
| Capability | What AI Does in Real Time | Impact on CX and Operations |
|---|---|---|
| Sentiment Detection | Identifies rising customer frustration, stress or tonal shifts as they occur. | Enables agents to adjust empathy, tone and approach instantly. |
| Agent Coaching Prompts | Provides mid-call suggestions such as de-escalation cues or script reminders. | Improves agent confidence, reduces errors and elevates call quality. |
| Escalation Alerts | Signals supervisors when an interaction is likely to intensify. | Allows timely intervention before situations worsen. |
| Pattern Recognition | Evaluates language, pace and inflection during conversations. | Offers data-driven insights that deepen agent skill development. |
| Contextual Knowledge Support | Surfaces relevant policies, answers or next steps on the spot. | Shortens handle time and strengthens resolution accuracy. |
Real-time voice analysis has grown in sophistication. AI can learn from vast samples of speech data, continuously analyzing real-world patterns, linguistical structures, and varied accents through “deep learning neural networks.” The technology can decipher the mood, urgency and intent of customers based on vocal inflections—on the spot. AI-based agents can be used to coach live contact center staff during tense interactions as they unfold, enabling agents to course-correct before a situation escalates. AI tools can also alert supervisors to intervene when the moment arises.
AI technologies can review a compilation of customer interactions from a variety of communication channels like texts, emails, phone calls and chatbots. This provides a more detailed overall illustration of the performance of individual agents, or of the contact center as a whole. Insights can be used to improve training techniques, call scripts and marketing plans.
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Understanding Channel Preferences Through AI
It also identifies what types of channels the company’s customers prefer, and for what purposes. For instance, phone-based customer service continues to decline, as self-service continues to gain attention in specialized verticals like the automotive lending industry. Texting is used more frequently in collections departments. As a provider of business process services, we often see archetypes like these revealed through AI-based analytics, and we advise our clients to shift their customer engagement offerings accordingly.
Related Article: Human-Guided AI Is the Future of Customer Experience
Multilingual Translations
AI-based tools can also facilitate the translation of instructions and dialogs, reducing the burden on multilingual agents. Although live agents with proficiency in multiple languages are essential when doing business in certain regions, AI can provide welcome support in this area. It allows companies to use multilingual agents for more urgent customer issues. Close to 40% of marketers incorporated AI-based translation into their 2024 strategies, with 83% demonstrating confidence in translation quality, according to findings from AI-based communications provider KUDO.
The Value of Digitally Assisted Human Support
Although nothing will soon replace human respondents for empathy and complex decision-making skills, this strategy is what we call “digitally assisted human efforts,” where agents leverage state-of-the-art technologies to ensure the success of their initiatives. This is the notable upside to AI in customer experience. It has the ability to streamline and augment the work of proficient humans. It allows talented and attentive customer service employees to develop more effective and high-quality skills through data intelligence, leading to more quality interactions, increased customer loyalty, and repeat business.
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