Customer Experience

The GenAI-driven contact center revolution

How AXM and CX are reshaping total experiences inside the contact center

Contact center agents are the linchpin between organizations and their clientele. As the demand for exceptional customer service continues to rise in the total experience economy, managing the agent experience becomes paramount. This is where Agent Experience Management (AXM), as a discipline, steps in, employing techniques to optimize every facet of agents’ professional lives. In this transformative era, Generative Artificial Intelligence (GenAI) is emerging as a powerful ally, reshaping AXM and propelling it to unprecedented levels of efficiency and personalization.

However, there is still a gap between the expected and the delivered customer experience. To minimize the disconnect, businesses should focus on embracing Total Experience as a discipline. Total Experience encompasses not only customer experience (CX) and employee experience (EX) but also operational experience (OX). What’s more, CX and AXM work together, forming the backbone of a holistic strategy that fosters brand differentiation, customer satisfaction, and business growth.

The landscape of AXM: challenges and solutions

Contact centers face multifaceted challenges, including agent burnout, high turnover rates, and the complexity of managing remote agents. Solutions geared towards Agent Experience Management (AXM) address these issues by creating a positive work environment, providing clear expectations, and offering continuous training and development opportunities. Integrating Generative AI (GenAI) in AXM introduces a transformative wave, promising more efficiency, personalization, and insight.

The GenAI Revolution in AXM and some use cases

GenAI, with its arsenal of intrinsic technologies like natural language processing (NLP), machine learning (ML), Large Language Models (LLM), and automation, is set to revolutionize AXM. Several use cases illustrate the symbiotic relationship between contact center agents and GenAI tools.

  • AI-powered real-time virtual assistants and chatbots equipped with NLP and ML capabilities can assist agents during customer interactions, handle routine queries, and provide real-time suggestions. This reduces cognitive load, ensures accuracy, and maintains compliance with industry regulations.
  • AI-based Incident Categorization and Call Summarization is where AI automates the categorization of customer inquiries and enhances call summaries, streamlining processes and providing valuable insights for improved generative AI self-help tools.
  • Also, AI-driven real-time analytics and insights tools that monitor agent-customer interactions in a live call can trigger proactive supervisor intervention, coaching, and the continuous improvement of agent performance.
  • Furthermore, AI can help automate the evaluation of agent performance, replacing costly manual processes and enabling efficient assessment of interactions, ensuring only low-scoring calls receive attention. Although this capability has been around for some time, we can say that today, it is much more mature with the advancements in higher speech-to-text accuracy and AI-aided scalability. 
  • GenAI algorithms can also be leveraged in predictive agent support where AI can closely predict customer needs and agent behavior, dynamically allocating resources and determining training deficiencies, ensuring efficient interactions.

Benefits of GenAI in AXM

The integration of GenAI into AXM strategies yields numerous benefits, starting with the automation of repetitive tasks to reduce agent workloads and errors. This allows agents to focus on meaningful customer interactions, leading to faster issue resolution and improved morale. With AI-driven personalization and real-time analytics, agents are able to provide tailored solutions, resulting in higher customer satisfaction and loyalty. Furthermore, empowered agents equipped with GenAI tools experience increased job satisfaction, reducing turnover rates and associated recruitment and training costs.

The road ahead while embracing the GenAI-powered AXM era

Organizations that embrace generative AI and large language models (LLM) will be better positioned to deliver exceptional customer and agent experiences. Investment in AI technologies, ethical frameworks, and training programs is imperative to prepare agents and systems for this transformative era.

Despite its promise, adopting GenAI in AXM comes with challenges. There may be ethical concerns and data privacy issues, and thus, the need for continuous training and adaptation must be carefully addressed. Transparency and fairness in algorithmic decision-making are crucial, and robust data privacy measures are necessary to maintain customer trust.

The OpenText Agent Experience Delivery solution

OpenTextTM presents a comprehensive solution to Agent Experience Management challenges faced by contact centers. Our Agent Experience Delivery offering addresses agent productivity and workload distribution and provides easy access to tools, resources, customer insights, and operational data. Our Agent Experience Delivery solution is designed for the dynamic landscape of the total experience economy, and it emerges as an indispensable asset, facilitating seamless agent-customer interactions and contributing to organizational excellence.

The transformative power of GenAI is unlocking new possibilities for improving agent efficiency, enhancing customer engagement, and ultimately driving business success. Embracing this technological evolution is the key to thriving in the GenAI-powered AXM era.


Unlock insights to improve agent productivity and experience with AI and Agent Experience Management tools. Download our AI-powered AXM report.


Alex Martinez

Alex is a Senior Product Marketing manager at OpenText with over 20 years experience working with customers and partners across multiple verticals with a strong focus on the Healthcare and Financial Services markets. He is keen on guiding customers through their digital transformation journey, taking a solution-oriented approach to solving their day-to-day problems.

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