Service and support organizations face a growing knowledge crisis. It is characterized by an ever-widening gap between the knowledge required to resolve issues efficiently in modern support roles: and the capacity to keep up with the demand using traditional approaches.
The crisis is fueled by high employee turnover, increasingly complex products, poor search capabilities, and critical information siloed in outdated articles, lengthy manuals, unstructured case notes, or in the minds of individuals.
The impact of this knowledge deficit spans industries and regions, leading to longer resolution times, frustrated customers, and an overall decline in service quality.
As a result, enterprise organizations are being compelled to reevaluate their approach to technical service and support or risk falling behind their competitors in an increasingly demanding market.
But as we will see, with highly specialized, domain-specific artificial intelligence (AI), service leaders are now able to transform legacy processes and effectively bridge the gap to end or minimize the crisis. AI can capture knowledge, bring new employees up to speed faster, and provide accurate answers and resolutions, thereby improving both the customer and employee experience.
Factors Contributing to the Knowledge Crisis
Employee turnover in customer service and support is already high and will likely increase as a wave of workers approach retirement, taking decades of experience and deep understanding of processes and technologies with them.
As experienced workers exit the workforce, companies must contend with a critical institutional knowledge gap left in their wake. The problem is compounded by challenges associated with attracting and retaining the next generation of service workers. While the demand for tech support continues to grow, replacing retiring employees and building a dedicated team feels like an uphill battle.
The impact of this knowledge deficit spans industries and regions, leading to longer resolution times…
Overall, the U.S. Bureau of Labor Statistics shows median employee tenure is just 2.7 years for workers aged 25 to 34. In contact centers, this trend of shorter employee tenure, combined with a shrinking pool of prospective workers, has led 63% of contact center leaders to report staffing shortages, according to a recent Deloitte Digital survey.
Beyond staffing issues, companies must overcome the challenges of managing and utilizing all accumulated knowledge effectively to resolve issues.
At large global organizations, resolution knowledge is often scattered across multiple systems in different languages and formats, including manuals, tables, videos, Internet of Things (IOT) data, technician notes and more. This fragmentation of information, coupled with ineffective search tools, makes it challenging to find the needed answers.
Far-Reaching Impacts
The knowledge crisis has far-reaching impacts on the business’ operational efficiency, as well as the customer experience (CX). In more complex service organizations, the time it takes to resolve issues can also have severe financial implications.
Consider the healthcare sector, where downtime of critical equipment, like MRI machines, can result in over $40,000 in lost revenue per day. The ability to quickly respond to and resolve issues efficiently directly impacts customer satisfaction and the bottom line, particularly when service providers must meet strict service level agreements.
As experienced workers exit the workforce, companies must contend with a critical institutional knowledge gap left in their wake.
Poor knowledge management also contributes to employee burnout, which is another key factor driving high turnover. When critical information is scattered across siloed data sources, employees struggle to find what they need quickly, leading to frustration.
Relying on a few experienced individuals to solve problems further exacerbates this issue. Slow response times and difficulty finding the right solution on the first attempt — both symptoms of ineffective knowledge management — can cause companies to lose their competitive edge.
How Tech Can Help Solve The Crisis
To combat compounding knowledge gap challenges, innovative service organizations are leveraging technology that empowers service teams with easy access to the most current and relevant information needed to resolve issues: and end the knowledge crisis.
The knowledge crisis is a complex challenge that requires the implementation of transformational technologies.
Key steps to achieving this transformation include:
- Implementing AI-Powered Solutions. AI cuts through complexity with its ability to analyze massive amounts of information from structured and unstructured data in hefty manuals, articles, case notes, and resolution actions taken.
- This helps employees find the right information when and where they need it, providing actionable insights to resolve issues in a timely manner.
- Creating a Centralized Knowledge Base. Consolidating knowledge into a single system of service intelligence reduces fragmentation and improves access to information.
- Selecting solutions with seamless integrations into existing service platforms and workflows (e.g., CRM systems, chat, service portals) supports user adoption and a positive employee experience.
- Enabling Knowledge Capture and Sharing. Capturing resolution knowledge from data sources is only part of the picture.
- To achieve the highest levels of prediction and resolution accuracy, AI needs to learn from both data and people, in real time, and continually optimize the resolution path. This paradigm shift, driven by AI, also means the work of top-performing technicians contributes directly to providing the most accurate resolution information back to agents.
The knowledge crisis is a complex challenge that requires the implementation of transformational technologies.
By building a single system of service intelligence and deploying AI that captures and shares knowledge, organizations can mitigate the effects of staffing shortages and fragmented data that are currently hindering service operations.
As the labor market evolves—particularly in competitive, technical fields—it’s essential for companies to stay ahead by adopting innovative strategies to manage and maximize their knowledge effectively.
Nurturing Tech-Savvy Agents to be AI Champions
As contact centers address the knowledge crisis, an opportunity arises to identify tech-savvy agents and empower them to champion transformative artificial intelligence (AI) initiatives.
These champions play a pivotal role in successful AI implementation, enhancing the accuracy of results through their own usage and influence on colleagues.
Accuracy and user adoption are interrelated, and both are essential to AI success. For agents interacting with AI, the first prediction must be accurate to build confidence in the solution. If the initial result is inaccurate, agents are less likely to request a second prediction.
At the same time, AI learns from every interaction, meaning that increased adoption and usage will drive greater accuracy over time.
To set themselves up for success, organizations can identify agents who are both subject matter experts and have the technical aptitude to support AI initiatives. Bringing these AI champions into the process early enables them to validate use cases, workflows, and predictions before a broader rollout.
This approach retains talent and provides high performers with opportunities to gain valuable AI experience, creating advocates who make the AI usage programs feel peer-led rather than top-down.
By investing in the career development of tech-savvy agents, contact centers can build a pipeline of skilled service professionals while addressing the knowledge and improving employee satisfaction.
