With CX, There’s a Disconnect Between Expectations and Reality. AI Can Help

Consumers have made their sales and servicing preferences clear: They want to help themselves whenever possible. They will typically start on a company’s website or mobile app, but they expect to easily reach a knowledgeable, helpful, and empathetic live employee if needed.

There is a growing level of frustration and disappointment in customer experience (CX) satisfaction throughout the market—just ask any friend, family member, or coworker, and it quickly becomes clear that there is a major disconnect between customer expectations and the service experience companies are delivering.

Act I: The Battle to Improve CX

Given the effort and investments companies have made during the past 10 years to enhance their CX, it’s logical to assume it should have improved. However, the reality is different. Satisfaction with the CX was lower in 2024 than in 2023, and it seems as if this trend has been playing out for years. The question that needs to be asked is, what can organizations do to reverse course? Moving forward with their longstanding approach clearly isn’t going to work. Now, let’s call this Act I and move on to Act II, because for the first time in contact center history, there is a clear path forward.

Act II: The Rise of AI in Contact Centers

Many types of artificial intelligence (AI)—generative AI (genAI), large language models (LLMs), machine learning, deep neural networks, computer vision, predictive analytics, and others—are advancing contact center capabilities. These technologies are being embedded in contact center systems and applications, including omnichannel routing and queuing engines, outbound solutions, self-service (conversational AI/genAI-enabled intelligent virtual agents), CRM, conversation (speech and text) analytics, workforce management (WFM), automated quality management (AQM), transcription, voice biometrics, real-time guidance (RTG), automated post-interaction summarization, and more. Companies using cloud-based contact center systems likely already have access to some of these AI-enhanced capabilities.

The Disconnect

Many companies are expressing interest in trying some of these solutions via pilots or limited implementations, but they lack the internal knowledge and technical expertise to successfully apply them in their operating environment. Another major challenge is that organizations are unlikely to realize the benefits from AI or any new technology or system without adapting their culture and changing their operating guidelines and procedures to support the updated functionality. Contact centers that add AI-enabled systems without retiring outdated applications and associated activities often end up adding more work and overhead for the department, as well as increasing IT-related expenses. A common example of this is when contact centers purchase an AQM solution to automate their quality management program but continue to perform QM manually. Companies should conduct a pilot with any new system to assess its performance, but once it proves to be effective, the older processes and systems should be retired and resources redeployed.

Building the Bridge to a Better CX

Contact centers and customer service organizations must change if they want to meet the needs of today’s consumers by delivering even an acceptable CX. However, the answer is not simply dropping AI-based systems into the operating environment, as this will not deliver the needed improvements. AI is transformational technology that positions companies to do things differently (and hopefully better). To optimize the enhancements from system changes, the entire servicing ecosystem—everything that happens in the contact center or customer service organization and possibly other departments they interact with—needs to be updated at the same time. This positions organizations to take greater advantage of the technology’s improvements to realize the benefits. Doing this right is a complex and multiphase initiative that should include the following high-level phases:

1. Form a steering or oversight committee to manage the project and identify a senior executive to champion the initiative.
2. Assign a dedicated project manager to keep the initiative on track, on time, and on budget.
3. The committee should draft a CX AI strategy that focuses on the contact center and customer service organizations and is aligned with the company’s AI strategy.
4. Draft a detailed project plan that factors in every aspect of the contact center or service organization—operations, policies and procedures, human resources, and technology—as everything needs to change and be replaced with a new approach and culture. (The project plan should be divided into logical phases lasting three to nine months, where possible.) Coordinate with the company’s AI committee and/or AI center of excellence (or similar function), if these are in place.
5. Identify the top 10 to 20 operational opportunities for process improvement.
6. Identify outdated systems and applications that need to be replaced.
7. Identify AI-enabled systems that can improve the operation.
8. Conduct a detailed system audit to document the needed system changes and expected benefits for each (reduction in maintenance fees, productivity improvements, enhancements to the CX and employee experience (EX), increased revenue, etc.).
9. For every recommended system change, determine all related operational, procedural, and resource impacts and benefits.
10. Scope and prioritize investments and build out the project plan for each item; include a pilot phase for all new systems.
11. Get buy-in from functional managers and senior executives.

It’s ideal to approach the entire project methodically to ensure the contact center or customer service organization is positioned to make all necessary changes. This increases the likelihood of achieving the initiatives’ fundamental goals of improving the CX, EX, and productivity. However, if an operation needs to realize some benefits immediately, an emerging AI best practice is to identify one or two opportunities that can quickly be addressed within the guidelines of the overall strategy and plan. This should only be done when the organization appreciates the importance of changing the related servicing workflows and processes and not just the systems.

While the selected systems vary by company, the most popular choice for contact centers is automated post-interaction summarization, a new application that commonly reduces agent wrap-up time by 20 percent to 40 percent. However, to produce these benefits, companies need to eliminate the requirement for agents to perform this function, modify policies (and possibly their knowledge management system and agent guides), update training and QM programs, retrain their staff, etc. The point is that even when something appears simple, there are likely to be many operational and agent-related functional components that need to be addressed to ensure the system benefits can be fully realized. (And, of course, it makes sense to start by piloting the application to work out all issues before full implementation. 

Final Thoughts

Improving the CX is a priority and goal for most enterprises, but it has been difficult to achieve—although not for lack of trying. AI is transformational technology that has the potential to greatly improve many components of the CX and the performance of contact centers and customer service organizations, but only if it’s rolled out properly. While it’s fine and can be a best practice to start small with one or two AI-related initiatives, contact centers and service organizations will only fully realize benefits if changes are made to the systems and all associated operations and procedures, and more importantly, if the employees who will make the initiative successful are supported throughout the process.

Donna Fluss, founder and president of DMG Consulting, provides a unique and unparalleled understanding of the people, processes, and technology that drive the strategic direction of the dynamic and rapidly trans forming contact center and back-office markets. Fluss can be reached at donna.fluss@dmgconsult.com.

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