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Organizations everywhere are understandably thrilled about AI and the potential it has to transform business functions and improve efficiency, productivity and customer service. But not all AI is created equal. AI models are trained off large language models (LLMs), which ideally will be large bodies of text that are accurate and up-to-date. They also require a knowledge management system that is trained on organizations’ CX data as well as general internet data. If knowledge management isn’t founded in this CX data, then even the greatest LLM will have limited impact.
Without good knowledge management practices, AI and machine learning will not have access to the right data to live up to organizations' expectations. Creating a future-ready workplace means that organizations must learn how to adopt AI in the most effective way possible. Here’s how they can reconsider their knowledge management strategy to better take advantage of AI technology and capabilities.
The Impact of Poor AI Tools
Knowledge management of an organization's internal assets and data must be well-organized, accurate and up-to-date. Without this, they will not get the ideal results from their AI solutions and customers may receive incorrect answers to their questions. Potential outcomes include irrelevant, poor quality and untrustworthy information that creates more problems than it solves.
For example, if an organization uses a generative AI-enabled chatbot to manage customer service chats, the quality of data that the chatbot is trained on is very important. AI-powered knowledge management systems can hold a lot of sensitive customer information (such as financial information), and a chatbot can be more at risk of leaking sensitive customer information if it has not been trained properly.
Further, hallucinations occur when factors such as insufficient training data or biases in data cause incorrect or misleading results in an AI model. Organizations cannot realize the transformative benefits of AI when they cannot even trust its results. Avoiding hallucinations requires a collection of knowledge that is up-to-date and continually improving.
Barriers to Accomplishing Excellent Knowledge Management
Creating an agile knowledge management practice takes a lot of time and effort. Capturing and maintaining an accurate, well-organized knowledge base is no easy feat. According to a survey by Precisely, data scientists spend 80% of their time cleaning, integrating and preparing data, all while dealing with data in multiple formats including documents, image files and videos. This is time-consuming, laborious work.
Another difficulty in the modern workplace is that the fast pace of change and innovation requires organizations to collect, maintain and update information even more quickly than before. It’s now more difficult for employees to manage this on their own.
In this way, knowledge management and AI capabilities have a unique push-pull relationship. Each of them can influence the other in positive ways. Just as strong knowledge management practices makes AI more accurate, strong AI tools make it easier to go through and organize all of the pieces of data that exist in an organization.
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Knowledge Management as the Foundation of Great AI
Sound internal knowledge management practices improve AI applications in many ways. An accurate data set used in knowledge management practices will reflect real-world experiences from an organization. In the case of customer service data, this means that the data set will show a variety of types of interactions, from the most common experiences to the very rare edge cases. Diverse, comprehensive data like this will help organizations decrease their risk of hallucinations when using AI.
With this in mind, organizations should consider solutions that give them an easy way to manage internal data, continually update the company data pool and simplify the process as much as possible for users so that they are not bogged down by the large amount of data. Once organizations accomplish this, it will become that much easier to give customers a positive experience through AI.
Start Improving Your Knowledge Management Practices Now!
Enabling AI through great knowledge management practices is key business imperative for organizations looking to excel. NICE’s newest product, Enlighten Autopilot Knowledge, takes this imperative and makes it a more seamless, accessible goal for organizations. By combining both its conversational bot technology and its knowledge management capabilities, NICE makes it easy for organizations to set up a knowledge base and connect it with a bot builder. The resulting conversational solution can deliver customers relevant, accurate information on customer service channels anywhere. By adopting Enlighten Autopilot Knowledge, organizations can begin their journey toward more effective customer interactions.
