Unshared knowledge costs you a significant amount. Employees find themselves stranded when knowledge is scarce for routine tasks such as password reset or account unlock. It stresses your L1 support as self-service makes knowledge discovery feel like finding a needle in a haystack.

Unfortunately, your L1 support the first line of person-to-person contact is less likely to be reliable and helpful. Also, organizations often want to eliminate L1 support for various reasons, forcing L2 to become L1. With L1 support facing shortages in agent counts, you must rethink the role of your self-service, as relying on only a legacy approach can worsen employee experience. You must focus on the relevance, accuracy, and reliability of knowledge in your self-service.

It is also essential to ensure that self-service helps knowledge become easily accessible and shareable for your employees, no matter where they are. This strategy can help your employees proactively manage problems and reduce their reliance on L1 support. In essence, when you struggle to cope with L1 agent shortages, GenAI-based chatbots can help you fill the gaps and manage everyday routine productivity challenges in the workplace. Read on.

Service desks continue to face challenges filling in for L1 support. As the first line of contact to deliver FCR or first-contact resolutions, L1 support plays a significant role in helping employees solve their problems. However, it is a massive pain for service desk managers as L1 support agents are shrinking in number for various reasons —

• High turnover rates : HDI’s old benchmark data for annual agent turnover claimed that the service desk faces 40% of agent turnover annually. The data still holds relevance in the present context. Based on the data, service desk agents can stay for only 2 ½ years, meaning inexperienced agents need to handle large numbers of calls. This translates into extreme workloads for the L1 support agents, making it a short-lived career choice for them.

• Limited automation support : Service desks leverage automation, but it has limited capacity to allow L1 support agents to use appropriate tools to do their best work. The massive workload of repetitive queries significantly impacts them, making service desk work experiences poor.

• Lack of expertise and experience : It is crucial for service desks to onboard skilled L1 agents to handle employee queries efficiently. However, most L1 support agents need training and development to improve their communication, empathy, and active listening skills. Companies struggling to find the right fit must spend money on employee training and development. To guide employees with the best strategies.

• Increased complexity of IT infrastructure : Different kinds of tools are being implemented for hybrid or remote teams. The lack of relevance in self-service can put pressure back on L1 support as employees need help with diverse technical setups for VPN or M365 suites or connectivity issues.

These are ever-evolving scenarios for service desk managers. They struggle to find the right fit for L1 support and allow employees peace of mind. Improving knowledge access is crucial since this is a prevalent challenge and will become stern with time. It is best to consider GenAI-based self-service chatbots for your support needs.

Chatbots are AI-powered. The difference is that they have specific limitations and can only answer predefined queries. Employees tap into inadequate knowledge when they need unique answers and rely on L1 support.

Generative AI chatbots are LLM-powered chatbots designed to craft unique NLP responses for user queries using their training data and previous and ongoing history of user interactions.

GenAI chatbots leverage vast data repositories via LLMs and third-party repositories to generate accurate, relevant, and valuable knowledge for your employees to help them resolve routine queries and improve productivity rates. This perhaps reduces the tickets to service desks for L1 support.

Every company has unique needs to solve workplace productivity issues. So, the one-size-fits-all concept rarely offers domain-specific knowledge to employees. Integration with off-the-shelf GPT-powered chatbots thus makes knowledge hard to find and bombard L1 support with massive volumes of tickets.

Due to the need for adequate L1 agents, the service desk needs help to address issues and help employees get back to work as early as possible. GenAI chatbots eliminate this pressing challenge, reduce the tickets, and transition to zero-touch service desks. It helps self-service become a powerful knowledge house and provides as much support as possible to lower the dependency on L1 support depending on the following attributes—-

• Domain-specific answers are independent of typical search engine results and help solve as many employee queries as possible.

• Knowledge is always fast, accurate, and relevant, which improves veracity and enhances user adoption.

• Autonomous resolutions reduce wait times for L1 support and provide continuous support.

• Service desks can encourage L2, L3, and L4 support to focus on creative challenges and gain experience.

• Self-service applies LLM or GenAI knowledge to meet user queries and solve problems.

Since Generative AI transforms knowledge management, self-service also transforms employee support and eliminates the workload on L1 support.

L1 support primarily handles repetitive queries. These queries often move to the L2, L3, and L4 tiers, extending the time to mitigate employee problems. By unleashing relevant knowledge access, GenAI chatbots provide many compelling use cases for repetitive tasks or routine workflows.

They lay the foundation for employees to apply the right knowledge to resolve these problems autonomously and improve productivity. Appropriate knowledge management through self-service helps employees in the following ways,

1. Real-time knowledge share

GenAI chatbots make self-service independent with unique knowledge-generation capabilities. Apart from that, GenAI chatbots can learn from experiences to generate answers for unique or unknown queries using their training data when synced with third-party resources. Your GenAI chatbot becomes a real-time knowledge-sharing interface for employees, ensuring rapid information discovery and problem resolution.

When integrated with Knowledge AI, Workativ’s LLM-powered hybrid NLU platform, GenAI chatbot interfaces gain the ability to retrieve information from public knowledge and company knowledge repositories. Hence, it cuts short the time to find information and helps share knowledge among employees steadily and answer questions. Your employees are more empowered to focus on DIY activities and help you avoid stress due to shortages of L2 agents.

2. Custom or personalized answers for employees

GenAI chatbots can create customized or personalized answers for your employees. Integration with the company’s various data points, such as CRM, ERP, communication channels, content management systems, HRIS systems, and so on, helps GenAI chatbots fetch the correct information about each individual. Seamless integrations mean GenAI agents in your chatbots can tailor information as per employees’ queries and provide them with much-needed information in a personalized way.

For example, Workativ Knowledge AI uses large language models trained with external data sources to gain abilities like ChatGPT. As a result, it can extract and summarize accurate answers for your employees and personalize responses for them. Let’s say one of the employees wants to know about his salary breakup. Knowledge AI runs vector searches in external data systems and fetches consolidated information to help him clear doubts, save time, and improve productivity without looking for the L1 agents.

3. Contextual knowledge for self-service

AI-powered knowledge management is an intelligent solution for employees to discover contextual answers rather than time-consuming and vague responses, which later escalate issues for L1 support. LLM-powered chatbots efficiently work through formats such as PDFs, Excel sheets, text documents, and CSV files, among others, to generate contextual responses for self-service and drive high-rate employee engagement.

When using Knowledge AI, your self-service becomes smart and helps your employees tap knowledge trapped inside various data formats. Without leaving the Knowledge AI-powered self-service chatbots, your employees can find contextual information right within them and solve problems with conversational AI responses in real-time.

4. Updated knowledge access for rapid responses

Access to the latest knowledge bases helps your employees work independently and find the information they need to solve problems. LLM-powered chatbots always work with updated knowledge repositories because LLMs keep providing updated data using their self-learning capabilities, including knowledge generation capabilities. The real timeliness of responses rapidly solves problems for your employees and eliminates the need to rely on L1 support agents.

Workativ Knowledge AI ensures your employees fetch the latest information by allowing users to update their knowledge repositories as needed. Besides, Knowledge AI applies the same techniques as unsupervised learning to update its knowledge and rapidly respond to employees' unique queries. With the help of rapid responses, Knowledge AI eliminates wait time and takes ITSM towards zero-touch employee support.

5. Predictive analytics for proactive outreach or resolutions

Since GenAI chatbots are backed by Generative AI or large language models, they can gain better prediction capabilities to prevent outages before they happen. The seamless integration with application systems or employee databases helps LLMs improve monitoring and automate alerts when an employee is supposed to run software updates or implement password resets to help them prevent downtime.

When your chatbot uses Knowledge AI, it can unleash unique predictive capabilities to automate alerts and inform employees of necessary actions to maintain uptime. As a result, there is no unexpected downtime, which may otherwise need L1 support assistance.

6. Intelligent routing of support queries

GenAI chatbots allow L1 support agents to eliminate guesswork or prevent too much effort before escalating the ticket to the right team. GenAI chatbots use LLMs to build predictive models to analyze better the right team suitable to prevent the issue. For example, suppose a ticket contains a topic such as BSOD. In that case, whereas the L1 support agent is too novice to understand the term, LLM-powered chatbots can use predictive models to understand the context of the query and escalate the ticket to the desktop team.

Similarly, Knowledge AI makes information retrieval flexible for L1 support and helps L1 support agents escalate tickets to the right team. This can reduce the work pressure on L1 support agents and improve their experience for long-term retention.

7. Personalized training for L1 support agents

As many data backed that companies would try to eliminate L1 support agents due to high training costs. The good news is that service desk managers can utilize GenAI to reduce training costs and time and train them appropriately by accessing knowledge effectively.

Knowledge AI powers GenAI chatbots to help L1 support with custom knowledge resources produced using employee historical data, ongoing interactions, actions taken, etc. Additionally, Workativ provides a shared live window for agents. For L1 support agents, the shared inbox helps them create AI summaries to share with higher-tiered support. They can also ask for relevant articles to respond to employees and resolve their queries. This is none less than on-the-job training with relevant hands-on experience for L1 support agents; thus, service desks can reduce shortages and attrition.

Knowledge is critical to improving employee productivity and experience. Inaccessible knowledge has a longstanding implication for enterprises. A report by Panopto claims that 60% of employees need help finding information from their colleagues and teams. Surprisingly, delays in knowledge sharing cost companies $40.6 million due to productivity losses annually.

But AI-powered knowledge management unleashes fantastic benefits for your company and employees. Find them below—-.

1. Digital-first employees

AI-powered knowledge management rapidly helps you transition to digital transformation without breaking the bank. As you deploy Generative AI chatbots powered by Workativ Knowledge AI, your employees gain easy access to knowledge and become more empowered to solve their problems and prevent L1 support assistance.

2. Increased agent efficiency

L1 support attrition would come down due to GenAI-powered chatbots, which enable employees to empower themselves and solve their problems. Knowledge AI reduces the mean time to respond (MTTR) for repetitive tasks, thus freeing up L1 support and encouraging them to focus on creative activities.

3. Relevant information

GenAI-powered knowledge ensures that information is relevant and accurate; thus, employees are more in control of solving their problems autonomously. When combined with Knowledge AI, it gives you the benefits of the RAG approach, which brings in the power of LLMs and current knowledge from your enterprises’ systems. This ensures you gain contextual responses and prevent hallucinations to improve response and user interaction.

4. Scalability and cost efficiency

As you expand, your service tickets can grow, too. For the good, Knowledge AI-powered chatbots boost knowledge sharing for self-service and allow employees to solve problems autonomously. It reduces the ticket volumes to service deks and eventually helps save costs.

Robust knowledge management drives employee engagement to solve more support queries in an autonomous way. Even though shortages of L1 support agents are a starking issue, you can balance it with the proper application of GenAI chatbots. It boosts self-service and resolves support problems efficiently.

Self-service needs relevant and accurate knowledge to drive employee engagement and efficiency and manage the shortages of L1 support agents. It is evident that stale or vague knowledge has employees relying more on L1 support for even a very common query. However, making knowledge readily available and relevant makes your self-service powerful and efficient in boosting employee productivity.

Generative AI transforms knowledge management at a large scale and makes resolving issues easy. Knowledge AI aims to enhance knowledge management for employee support and help build robust GenAI chatbots to elevate employee experience, including overcoming the challenges of shortages of L1 support. Want to learn more? Book a demo today.

1. What is the easiest way to combat L1 support shortages?

The quick and easy way to combat L1 support shortages is to transform self-service with robust knowledge management. By layering in the power of LLMs and external resources grounded in the enterprise’s proprietary data, you can turn your self-service into a powerful knowledge house.

2. How can your GenAI chatbots boost self-service?

When applied with the RAG approach, GenAI chatbots boost self-service capabilities by unleashing comprehensive knowledge access for employees. This approach is instrumental in making employees independent and removing the need to rely on L1 support for routine queries.

3. What are the benefits of GenAI chatbots for your self-service?

GenAI chatbots can reduce the time it takes to handle queries autonomously, helping boost MTTR. On the other hand, employees are fond of using self-service and relying less on L1 support. Relevant and accurate information helps improve resolution rates and cuts down service desk costs. Employees also enjoy enhanced knowledge sharing, which improves engagement and reduces attrition.

4. How can you effortlessly build a GenAI chatbot focusing on enhanced knowledge management?

Workativ Knowledge AI provides the right LLM-powered platform to layer your self-service with advanced knowledge management capabilities. It provides the benefits of hybrid NLU, which eases information retrieval from public knowledge and information grounded in the enterprise’s knowledge systems to improve knowledge-sharing and problem-solving and remove hallucinations.