AI-powered Quality Management (Auto QM)

07 Misconceptions about Auto QM in Contact Centers

Are you still relying on spreadsheets and manual reviews to manage your contact center’s quality assurance? In today’s fast-paced digital world, ensuring top-notch customer service is more critical than ever. With the advent of AI-powered Quality Management (Auto QM) solutions, contact centers have a powerful tool to enhance their performance evaluation processes.

Statistics show that implementing AI can improve call center efficiency by up to 40%, yet many managers still rely on traditional methods due to lingering misconceptions about AI. This blog aims to dispel these myths, illustrating the true benefits of Auto QM and how it can revolutionize contact center operations.

Read More: The Future of AI in Customer Retention Strategies

07 Misconceptions about Auto Quality Management (Auto QM)

1. Auto QA Isn’t Accurate Enough to Deploy at Scale

Misconception: Automated QA systems lack the precision and contextual understanding necessary to deliver accurate results, especially at scale.

Reality: Modern Auto QA systems leverage advanced machine learning algorithms and natural language processing (NLP) to achieve high accuracy levels. These systems are trained on vast datasets and continuously learn from new data, improving over time.

Statistics & Examples:

  • According to a study by Gartner, AI-driven QA systems can achieve accuracy rates of up to 95%, rivaling and sometimes surpassing human evaluators.
  • Amazon reported a 90% reduction in defects and a significant improvement in customer satisfaction after deploying an AI-based Auto QA system across its customer service operations.

2. Auto QA Will Replace Human-Led Performance Evaluations

Misconception: Automated QA systems will entirely replace the need for human evaluators, leading to job losses and a lack of personal touch in performance evaluations.

Reality: Auto QA is designed to augment human evaluators, not replace them. These systems handle repetitive and time-consuming tasks, freeing up human evaluators to focus on more complex and subjective aspects of performance evaluations.

Statistics & Examples:

  • A McKinsey report highlighted that AI could automate 45% of tasks, allowing employees to concentrate on higher-value activities.
  • Zappos successfully implemented Auto QA to handle routine quality checks, enabling their human QA team to focus on personalized coaching and development for agents, resulting in a 20% improvement in overall performance.

3. AI-Based Auto QA Is Rigid & Will Provide Generic Results

Misconception: Automated QA systems lack the flexibility to adapt to different contexts and will only provide generic, one-size-fits-all results.

Reality: Advanced AI-based Auto QA systems are highly customizable and can be tailored to meet the specific needs and contexts of different industries and businesses.

Statistics & Examples:

  • Forrester Research found that 70% of companies using AI-based QA reported improved personalization and relevance in their quality assessments.
  • A large telecommunications company used a customizable Auto QA system to address specific customer service scenarios, leading to a 15% increase in first-call resolution rates.

4. Auto QA Is Too Complicated to Install, Onboard, and Use

Misconception: The implementation and onboarding process for Auto QA systems are overly complex and require extensive technical expertise.

Reality: Many Auto QA systems are designed with user-friendly interfaces and offer comprehensive support during installation and onboarding, making them accessible even for non-technical users.

Statistics & Examples:

  • A survey by Deloitte revealed that 60% of businesses found Auto QA systems easy to implement and onboard, with most installations completed within 4-6 weeks.
  • HubSpot’s implementation of an Auto QA system included extensive training and support, leading to a smooth transition and 95% user adoption within the first month.

5. Auto QA Isn’t Secure Enough (Data Privacy Concerns)

Misconception: Automated QA systems are not secure and pose significant risks to data privacy and compliance.

Reality: Leading Auto QA providers prioritize security and compliance, employing robust encryption, access controls, and regular audits to protect data privacy.

Statistics & Examples:

  • According to a report by the Ponemon Institute, 90% of companies using AI-based QA systems have not experienced any data breaches.
  • Salesforce, a major CRM provider, uses Auto QA with stringent data privacy measures, ensuring compliance with GDPR, CCPA, and other regulations, thereby maintaining customer trust.

6. Auto QA Is Too Expensive & Does Not Offer An ROI

Misconception: Implementing an Auto QA system is cost-prohibitive and does not deliver a tangible return on investment (ROI).

Reality: While there may be initial costs, Auto QA systems often result in significant long-term savings and efficiency gains, providing a substantial ROI.

Statistics & Examples:

  • A study by Accenture showed that businesses could see a 30-40% reduction in QA costs and a 25% increase in productivity after implementing Auto QA.
  • A financial services firm reported an ROI of 200% within the first year of using an Auto QA system, primarily through reduced error rates and faster processing times.

7. Auto QA Will Take My Job

Misconception: The deployment of Auto QA systems will lead to job losses as machines replace human workers.

Reality: Auto QA is more about enhancing human capabilities than replacing them. By automating routine tasks, employees can focus on more strategic and creative work.

Statistics & Examples:

  • The World Economic Forum predicts that while AI and automation might displace 75 million jobs, they could also create 133 million new roles.
  • IBM implemented Auto QA in their support services, which allowed their human workers to transition to more complex problem-solving roles, resulting in higher job satisfaction and career growth opportunities.

Comparing Auto QM Vendors

When comparing Auto QM vendors, it’s essential to evaluate them based on features, pricing, and support. Here’s a look at some of the leading Auto QM vendors in the market:

NICE inContact

  • Features: NICE inContact is a leading player in the contact center technology space, offering advanced analytics and AI-driven quality management. The platform includes real-time performance tracking, allowing managers to monitor agent interactions and performance metrics continuously. This enables quick interventions and continuous improvement in service quality.
  • Pricing: NICE inContact utilizes a scalable pricing model, typically requiring a quote for accurate cost estimation. This approach allows for flexibility in pricing, accommodating various sizes and types of contact centers. The scalable model ensures that as contact centers grow, the solution can scale with them.
  • Support: NICE inContact provides extensive resources, including detailed training programs and a robust support system. Their support services are designed to ensure that clients can effectively implement and use the platform, with ongoing assistance available as needed. This comprehensive support helps contact centers to quickly adapt to the new system and continuously optimize their operations.


  • Features: Observe.AI offers a suite of features designed to enhance contact center performance through AI-driven transcription, automated quality management, and real-time agent coaching. The platform provides detailed insights into agent interactions, allowing for immediate performance improvements and personalized coaching.
  • Pricing: Observe.AI employs a customized pricing model, which varies based on the size and specific needs of the contact center. This flexible approach ensures that clients only pay for the features and capacity they require, making it a scalable solution for growing businesses.
  • Support: Observe.AI is known for its excellent customer service, providing dedicated account managers and 24/7 support. This ensures that clients receive personalized assistance and can resolve any issues promptly. The vendor also offers comprehensive training resources to help contact centers maximize the benefits of their AI-driven tools.


  • Features: MiaRec stands out for its comprehensive quality management suite, which includes advanced speech analytics and sentiment analysis. The platform allows for customizable evaluation forms, enabling contact centers to tailor the quality management process to their specific needs. MiaRec’s features are designed to provide deep insights into agent performance and customer interactions, helping managers to identify areas for improvement and optimize overall service quality.
  • Pricing: MiaRec’s pricing is straightforward, set at approximately $50 per agent per month. This cost includes access to a wide range of functionalities, making it a cost-effective solution for contact centers looking for a robust quality management system without hidden fees.
  • Support: MiaRec is renowned for its robust customer support, offering extensive training and onboarding assistance. The platform is designed with ease of use in mind, ensuring that even those with minimal technical expertise can quickly get up to speed. MiaRec provides ongoing support to ensure that clients can fully leverage the capabilities of their Auto QM solution.


  • Features: CallMiner offers powerful speech analytics and automated scoring, providing detailed performance insights. The platform is designed to deliver deep analysis of customer interactions, helping contact centers to understand customer sentiment and improve agent performance. CallMiner’s advanced analytics capabilities make it a valuable tool for quality management and performance optimization.
  • Pricing: CallMiner offers customizable plans based on the specific requirements of the contact center. This flexible pricing model ensures that clients can choose the features and services that best meet their needs, making it an adaptable solution for various types of contact centers.
  • Support: CallMiner provides comprehensive support options, including thorough onboarding, training, and continuous customer support. Their support team is available to assist with any issues that arise, ensuring that clients can fully leverage the platform’s capabilities. This ongoing support is crucial for maintaining the effectiveness of the quality management system and ensuring continuous improvement.

Integrating Auto QM with Other Technologies

CRM Integration

Auto QM solutions can significantly enhance the capabilities of your CRM system by providing deeper insights into customer interactions. Integration allows for:

  • Seamless Data Flow: Automatic syncing of call evaluations and transcripts into the CRM for comprehensive customer profiles.
  • Enhanced Customer Insights: Combining QM data with CRM records offers a holistic view of customer interactions, improving service quality and personalization.
  • Streamlined Workflows: Reduces manual data entry and ensures that all relevant information is easily accessible within one system.

Omni-Channel Support

Modern contact centers operate across multiple channels, including phone, email, chat, and social media. Auto QM solutions can:

  • Unified Quality Management: Evaluate and manage interactions across all channels from a single platform.
  • Consistent Standards: Ensure consistent quality and performance standards across different communication methods.
  • Comprehensive Reporting: Provide insights into customer interactions across all channels, helping to identify trends and areas for improvement.

AI Ecosystem

Auto QM solutions are an integral part of the broader AI ecosystem within a contact center. They contribute to:

  • Improved Decision-Making: AI-driven insights from Auto QM can inform strategic decisions and operational improvements.
  • Enhanced Automation: Integrating Auto QM with other AI tools, such as chatbots and predictive analytics, can automate routine tasks and improve efficiency.
  • Continuous Improvement: AI systems learn and adapt over time, continually refining quality management processes and outcomes.


AI-powered Quality Management (Auto QM) solutions have the potential to transform contact center operations, offering comprehensive performance evaluations, customization, ease of use, and significant ROI. While misconceptions and fears about AI persist, the reality is that these tools are designed to complement human efforts and enhance overall efficiency. By embracing Auto QM, contact centers can achieve better performance, improved job satisfaction, and greater operational success. Explore how AI can benefit your contact center today and unlock the full potential of your quality management process.

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