While investigating why the client project had little progress, you discovered that your development teams had resource issues. Let’s say a sudden necessity was to get some essential software applications, and it brings up a couple of pieces of work for your DevOps teams.

All this mundane work can entail preparing a presentation for the manager’s approval, sending a letter to HR for budget allocation, then HR writing to the CFO for approval, connecting back to the finance team for disbursal, and so on and so forth.

These are back-and-forth processes and interconnected 一 a lot of interactions happen with HR and IT support. A single silo results in information slipping through the cracks and making it hard for a new person to take the process ahead.

So, do you agree that knowledge is key? If information is not accessible, productivity issues come up at large. For the same reason, your employee support team can be forced to handle the repeated issues and delay customer service delivery.

Knowledge AI, a large language model or LLM-powered solution for conversational AI or chatbot for service desk, makes it easy for your team to search for information.

Maybe you have a self-serve platform in your workplace and leverage automation to some extent.

However, the power of generative AI and large language modelsunleashes great efforts to redefine how your employee support team works and helps you build resilience into operational processes.

If you do not find Knowledge AI quite convincing for the growth of your business, we can give you more reasons why fast information delivery or knowledge discovery is essential for a modern workplace today to work and deliver business results.

Employees need information to work - this is a universal truth.

But, when knowledge is fragmented and lies in a silo, knowledge is scarce.

A support team cannot work. Your employees look clueless and sit idle for hours.

So, why this happens?

Organizations are not able to manage knowledge effectively.

Today, the number of productivity tools has just gone up. On top of it, organizations also use different business tools, such as CRM, ERP, ITSM platforms, etc.

• Communications across these tools are not synced to provide an integrated, unified view of the information.

• In a hybrid work setting, one’s time zone does not match the others. If anyone is unavailable, knowledge delivery can easily be affected.

• There is rarely anyone who can take responsibility for keeping knowledge articles updated and organized. So, knowledge management becomes difficult.

• We can say knowledge is multichannel in more instances rather than knowledge being omnichannel.

• Organizations dedicate time to legacy systems.

As a result, self-serve cannot reach its full potential and offer employees the information they need to perform a task.

The other way, it increases the workload on the employee support team.

Knowledge management not done right can result in information being old and ineffective.

When this type of KM is used to build chatbot conversations such as FAQs or customized responses, employee support can become of no help.

The generated responses may either contain out-of-date or incomplete information for employees.

Say an internal project management tool your employees use has a new version. It means it has new features and functionalities.

Now imagine the existing resource center or KB has no new updates added to the document.

A person unaware of the changes to the application would have difficulty taking control of the app and face productivity issues. It urges him to turn to the self-serve platform. Unfortunately, it can only surface the same old tips and provide no real help, forcing him to seek an agent’s help.

It is a deeper problem inside.

Employee productivity is wasted if an answer is unavailable through FAQs on the self-serve platform or a ticket is on the waiting list for more than a few minutes, if not hours.

In many instances, businesses are seen handling the same issues repeatedly, causing overutilization of agent time and forcing agents to add more time to resolve a common issue. At the same time, employees face disengagement due to loss of productivity.

Over the past few months, we have heard much about Generative AI, which has incredible abilities close to human-level intelligence to understand natural language queries and give back NLP-based answers.

Built on neural networks of deep learning techniques similar to human brains, Generative AI can detect the context in a query and populate the answer for users.

However, large language models used as ‘as is’ can be used for Q&A conversations based on the data they are trained on.

In this specific scenario, Generative AI can answer better and more contextually than regular chatbots, which can only answer queries related to FAQs built with known use cases.

For example, if you ask a chatbot on a company page for financial services, you can see a chatbot with pre-defined query templates. If any of the templates match your queries, you can click it and continue the conversations and solve your problem.

But what if you do not find a match for your query? It will return the same conversation template and ask you to choose to continue. This is utterly irritating.

Training Knowledge AI with the same abilities as Generative AI is a faster way to overcome RPA-based chatbot communications challenges and reduce the knowledge management gap.

If you have business-specific use cases and articles ready to build your KB and layer with the power of Knowledge AI, it is twice as much faster to generate responses to specific queries and provide an answer.

Knowledge AI is an LLM and Generative AI-powered chat interface that retrieves answers by detecting the contexts and intent of a query and provides an NLP-based answer.

Your business may have HR or IT support-related use cases similar to thousands of other functions. So, you can easily gather data, prepare your KB articles, and give access to Knowledge AI to train it with your business-specific use cases and help it solve user problems in real-time.

Say your user wants to know how to fix a printer paper jam issue. A Knowledge AI-powered self-serve chatbot can provide a straightforward answer and a supporting article.

At a time when Knowledge AI accelerates knowledge discovery, it also reduces friction by eliminating the need to navigate a whole KB article and speed up the process of resolving an issue.

Knowledge AI from Workativ allows you to build a massive corpus of data or a large language model with Website KB, External KB, and Internal KB. As a result, you can build an efficient KB with the ability to create custom conversation workflows and FAQ-based templates to handle workplace support issues.

Simply put, Knowledge AI is a platform used to upload articles with use cases that provide answers to IT or HR-related queries. It contains ChatGPT-like features to provide answers to users and help them solve problems in real time.

When a query is asked, Knowledge AI searches its large language model built with the articles or FAQs of business use cases. It finds contextual answers to NLP queries by searching the large language mode built on KB articles.

It goes this way,

• A user asks a query in a chatbot powered by Knowledge AI

• Large language models search for a contextual match (for say if it is a PTO inquiry, Knowledge AI searches information for leave balances as well as paid time off)

• If Knowledge AI does not surface an answer, it can seamlessly transfer the call to a live agent

Knowledge AI helps meet various business expectations by allowing your people to work at their best. Let’s find these significant use cases.

• Enhancing Tier 1 IT support is significant for any organization. These supports are common to ensure employee productivity. But, when they have no straightforward solution, the time to resolve these issues is prolonged and causes long downtime.

Knowledge AI provides efficacy for FAQs or custom dialogs to be widely used for multiple common or average support use cases, such as

1. Password reset

2. VPN settings

3. User provisions

4. PTO enquiry etc

Knowledge AI accelerates the pace of Tier 1 support and helps solve employees’ problems at scale.

• Self-serve for employee onboarding reduces the time for HR to dedicate to a lengthier process of functions such as documentation, introduction to the team, asset provisions, etc. Since these processes are automated, the new hire does not need to wait long and feel disengaged with the institutions. With pre-defined and automated workflows, a new hire can easily get assets and access to business emails, applications, and so on and so forth.

• Work-related knowledge discovery is useful for quick information on the project's progress or company details. If you have Knowledge AI embedded in your intranet platform, such as SharePoint, Google Workspace, or Samepage, you can easily provide access to key information for ongoing projects and company details and keep everyone on the same page to become aware of the progress or any new thing happening across your organization.

Knowledge AI improves knowledge discovery, making information easily accessible and providing multiple benefits for organizations to expedite growth.

• Employee productivity boost is the foremost advantage of Knowledge AI, which helps reduce downtime and increase uptime by allowing employees to solve problems by themselves using ChatGPT or a Generative AI-based self-serve chatbot platform.

• Reduction of repeated requests is possible with Generative AI-powered Knowledge AI search discovery. Your employees are more empowered to solve their problems, raising the number of agent tickets in the next tier, reducing workloads for agents, and solving more critical issues at scale.

• Enhanced knowledge repository gives access to information that was otherwise unattainable with KBs without the power of Knowledge AI. As you can upload as many articles with the preferred business use cases, you make information easy to find and help solve a problem.

• Cost reduction has a positive implication on your balance sheet as you save costs for optimized employee and agent utilization. On top of it, you save on tickets being reduced to the service desks or help desks.

Workativ has a leading workplace automation solution to help businesses with their HR and IT support automation initiatives.

Using conversational AI platforms, Workative has enabled businesses to make IT and HR support easy for their people and achieve productivity gains.

Companies across information systems, health IT consulting, and IT services have leveraged benefits with Workativ conversational AI platforms.

Now, we have integrated a large language model or Generative AI into our conversational AI platform known as Knowledge AI to help users build a huge corpus of knowledge and help retrieve information at scale for enhanced workplace productivity.

Leveraging our Knowledge AI, you can rapidly build highly effective KB resources and provide custom solutions to build workflows that solve unique support issues. Choose our Knowledge AI to,

• Upload KB articles as many as you wish

• Customize and edit KB articles at any time to provide the latest information at scale

• Get Hybrid NLU and conversational AI for seamless service desk conversations

As you use Workativ Knowledge AI, you can have the ability to build improved knowledge management by constantly making changes to your existing articles as you scale. With the updated knowledge bases, you ensure your employees always have the latest information to solve problems and enhance productivity.

The flexibility and convenience of getting information at scale go back to making the life of service desk agents easy and helping them efficiently address much more complicated issues, resulting in downtime being short-lived and less repetitive.

If you want to explore more about Knowledge AI solutions from Workativ, contact us today.