in Blog

May 31, 2024

Generative AI and Knowledge Management

Author:




Artur Haponik

CEO & Co-Founder


Reading time:




8 minutes


A proper knowledge management system can mean the difference between optimal business performance and utter failure. Without an ideal user integration and adaptation strategy, even the best knowledge management system can produce underwhelming results.

The good thing is that you can always leverage the benefits of an effective knowledge management system without dealing with most of the challenges of managing it. This is only possible through the use of generative AI in knowledge management. By combining both technologies, organizations can solve core challenges in KM, leading to more streamlined business intelligence acquisition and application processes.

This article will explore the role of generative AI in knowledge management and offer insight into how organizations can leverage gen AI to enhance their KM strategies.

Comparing AI and generative AI in enhancing knowledge management

Artificial intelligence (AI) has revolutionized everything, including KM. By offering automated solutions to otherwise tedious, time-consuming, and error-prone tasks, AI has the potential to not only streamline but also make the KM process faster and more efficient.

So, what makes AI so different from gen AI in the context of KM?

For starters, AI focuses primarily on providing automated solutions to tasks that would otherwise require human intelligence. With AI, human-attributed capabilities like speech recognition, visual perception, natural language understanding, and decision-making can be effectively replaced by intelligence systems like virtual assistants, chatbots, and recommendation systems.

Generative AI, on the other hand, analyzes patterns in existing data to create new data instances. This way, generative AI models can produce high-quality outputs that are indistinguishable from human-generated content. The content can range anywhere from text and images to music.

When leveraged correctly, generative AI in knowledge management can help solve several key challenges including creating and applying knowledge, storage, and retrieval, and disseminating knowledge across the organization.

Other key differences include:

Content creation vs knowledge organization

Knowledge management systems are designed to structure information, classify it, and facilitate the search and retrieval of information. Generative AI models, on the other hand, focus primarily on creating content based on patterns learned from training data – they do not organize or manage existing knowledge.

Use cases and applications

Generative AI capabilities to understand natural language and generate relevant content based on user requests make it incredibly effective in several areas, including chatbots, virtual assistants, and generating realistic simulations.

Contrarily, KM systems are better suited to supporting collaboration, knowledge-sharing, and decision-making within the organization, particularly in employee training and customer support.

Human interaction

GenAI’s NLP capabilities enable it to respond to prompts in a human-like manner and can even simulate natural conversation. KM systems lack this capability, which means they can only provide efficient search and retrieval mechanisms without directly interacting with the user.

Enhancing Knowledge Management with Gen AI

A recent survey by Salesforce indicates that nearly 67% of customers have raised their expectations for customer support, with a wide majority opting for companies that provide fast, reliable customer support. [1]

This clearly demonstrates the need for companies to reduce time to knowledge. By providing real-time access to knowledge, customer support and other customer-facing teams can better provide timely solutions, ultimately leading to improved customer satisfaction and overall business performance.

Besides reducing time to knowledge, generative AI can help solve a myriad of other challenges throughout the knowledge cycle in a KM system.

Here’s how GenAI can enhance each step in the KM process:

Knowledge Generation

Up until recently, automated content creation has been a thing of sci-fi movies. However, ChatGPT’s quick rise to widespread popularity demonstrated the value of producing new content almost instantaneously. [2]

The same notion applies in an organization. By enabling teams to generate new data points automatically, organizations can drastically reduce the time taken to collect, analyze, and present information.

Generative AI tools can also help organizations discover previously unknown connections and insights from disparate sources including emails, phone transcripts, chats, and CRM systems.

When leveraged across the organization, generative AI in knowledge management could help generate personalized news and reports for each employee, ensuring they get the knowledge they need without being overwhelmed by irrelevant information.

Theoretically, generative AI tools could also offer other benefits that are not directly tied to the organization. For instance, a Generative AI model trained on industry-wide data could potentially help identify best practices across multiple businesses. This way, organizations and employees could apply tried and tested AI-generated templates to different challenges, reducing their reliance on organizational and peer experience.

Knowledge Storage

The total amount of data created, copied, and consumed globally is expected to grow tremendously, reaching more than 180 zettabytes in 2025, up from 64.2 zettabytes in 2020. [3] While this might seem like a good thing for organizations looking to leverage their collected data for business intelligence, having too much data without a proper means to access, search, analyze, and share it might breed more challenges.

With Gen AI, organizations can effectively collect knowledge from large datasets and record it for future use. For instance, when faced with a previously dealt-with problem, employees can use Generative AI tools to search, organize, and summarize previous instances of the same problem, enabling them to find a viable solution promptly.

Organizations could also benefit from Generative AI tools’ deep learning capabilities. Generative AI tools can learn from an organization’s existing knowledge and communication flows and use the patterns learned to decide what messages and documents to bring to users’ attention. Take Google’s Gmail algorithm [4], for instance. It automatically suggests email recipients based on patterns learned from analyzing the recipient’s social groups.

The benefits of utilizing generative AI in knowledge management aren’t just limited to knowledge creation and storage – they also facilitate seamless knowledge retrieval. They do this by enabling employees to interact with KM systems through natural language processing.

Much like an internal ChatGPT, employees in different teams can instantaneously retrieve the right answers to a problem rather than having to sort through tons of organizational documents or use search engines. By giving employees the right answers to specific problems, Gen AI tools can make the knowledge retrieval process faster and more intuitive.

Knowledge Distribution

Knowledge sharing is a serious problem for many organizations, especially large organizations operating in multiple locations. While employees may be able to share information with their colleagues working in the same physical location, sharing information with teams in other geographical locations can be quite challenging.

Generative AI tools can help break down some of these communication barriers by allowing organizations to build more interconnected knowledge systems, enabling employees in different locations to access knowledge and collaborate more effectively.

Real-life use cases of generative AI

Despite being a relatively new technology, Gen AI has seen widespread utilization in KM across various industries and applications. Some of the most notable use cases of this revolutionary technology include:

  • Automatic FAQ Generation

Creating FAQs can be quite challenging for organizations. It requires a tremendous amount of time and human resources to go through customer queries and create appropriate responses. However, companies leveraging Generative AI tools can automatically generate FAQs by using Generative AI tools to analyze customer queries and generate a list of FAQs and their corresponding answers.

  • Content Summarization

All organizations, regardless of size and industry, have some measure of lengthy documents with important information. However, accessing this information in its expanded form can be quite tedious and time-consuming.

Gen AI tools can make it easier for organizations to summarize documents and access information in a more easily digestible manner. For instance, customer service agents can get quick access to relevant information, leading to faster issue resolution times and improved customer satisfaction.

  • Trend Analysis

Many companies are leveraging Generative AI to analyze large datasets and predict emerging patterns and trends. Ultimately, this helps different teams within the organization anticipate challenges and respond to evolving market needs.

Final thoughts

Generative AI is poised to revolutionize knowledge management. The analytics and NLP capabilities of Gen AI enable it to effectively address some of the biggest challenges of managing a KM system.

For instance, Generative AI can help enhance KM at every step of the process, right from knowledge creation and acquisition to knowledge distribution.

As the technology matures and more organizations realize the benefits of integrating Gen AI into their KM systems, we’re poised to see further improvements as tech companies grapple to satisfy the ever-increasing demand for faster, more reliable systems.

References

[1] salesforce. com. What Are Customer Expectations, and How Have They Changed? URL:
https://www.salesforce.com/resources/articles/customer-expectations. Accessed on May 27, 2024
[2] Reuters.com. ChatGPT sets record for fastest-growing user base – analyst note. URL:
https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01. Accessed on May 27, 2024
[3] Statista. URL: https://tiny.pl/d5cz6
[4] Google Blog. 6 Gmail AI features to help save you time. URL: https://tiny.pl/d5czb. Accessed on May 27, 2024



Category:


Generative AI