As we discussed in Part 1 of this series, Conversational AI offers powerful tools for natural human-machine interaction. This second part in the series explores its application within Knowledge Management (KM).
Briefly put, Knowledge Management (KM) comprises the processes of organising, storing, managing, using, and sharing organisational data and knowledge.
In most enterprises, knowledge is essential to operations; it influences virtually every decision and action. But collective organisational knowledge and information is often locked away in archives or complex databases; with traditional KM methods, retrieving it often means one needs to navigate complex search interfaces or browse through extensive documentation.
Conversational AI makes it possible to access organisational knowledge through straightforward, human-like interactions. It enables users to naturally converse with virtual assistants or chatbots and immediately receive accurate responses.
Convenience apart, such interaction reduces frustration and increases user engagement. Consider, for instance, an engineer at a manufacturing firm who needs detailed compliance information for a certain component. Traditionally, this might require sifting through technical documentation, contacting a supervisor, or waiting for information from other departments. With Conversational AI-driven retrieval, the engineer could just ask: “What are the compliance specifications for GP493N2?” and immediately hear the relevant information spoken by a chatbot.
AI-powered knowledge management improves organisational productivity because information retrieval becomes quick and intuitive. It also improves consistency in responses, reduces human error in information delivery, and—where needed—provides insights into users’ information-seeking behaviour and their information needs.
Real-World Applications and Use Cases: Stories of Intelligent Assistance
Conversational AI systems powered by LLMs use a combination of pre-trained knowledge and real-time data retrieval. For domain-specific or up-to-date information —such as medical guidelines or legal precedents—LLMs might retrieve knowledge from external knowledge bases, institutional KM systems, internal documents, or live sources.
Here are some examples of how organisations use Conversational AI in KM to streamline information access, save time, reduce operational costs, enhance decision-making, and improve user satisfaction.
Conversational AI in healthcare—in the form of chatbots and virtual assistants—integrated with KM systems drives better quality of service and better health outcomes. It enables doctors and nurses to use voice commands to quickly access patient histories, medication information, and medical guidelines. This significantly reduces the time they might have spent manually reviewing databases or physical files.
AI in healthcare offers numerous other benefits: It speeds up diagnoses that use radiology (X-rays, CT scans, MRIs, and such); it saves doctors time by handling routine tasks and helps them keep up with advances in medicine; it identifies people at risk for certain conditions.
But it’s important to see that in the general sense, AI in healthcare has its pros and cons, its ups and downs. An example comes from IBM’s AI system called Watson Health, which was once believed to have the potential to transform diagnostics and treatment in cancer. Over the course of a decade, it turned out that this just wasn’t true—and the system was sold off in early 2022.
Law firms are using AI-powered knowledge management to improve efficiency in legal research and analysis. A 2023 Goldman Sachs report claimed that 44% of tasks in the legal profession could be automated by AI; a 2024 survey by Clio—of about 1,000 lawyers and 1,000 members of the general public—indicated that this was true of nearly 75% of tasks performed at a typical US law firm. The Clio survey found, unsurprisingly, that the tasks most suitable for automation were gathering, documenting, and analysing information.
AI assistants can eliminate most of the need for manual research by swiftly locating and summarising case law, precedents, and statutes from extensive legal databases. Lawyers gain insights more quickly, which frees up time for decision-making and other high-level tasks.
Organisations that manage extensive product information are using Conversational AI to streamline their internal KM processes. Such companies typically struggle with managing and retrieving information using traditional methods; AI chatbots integrated into knowledge bases provide customer service agents instant access to detailed product data, troubleshooting steps, and warranty terms. A 2023 study by researchers from Stanford and MIT—based on data from more than 5,000 customer support agents—found that the introduction of a gen AI-based conversational assistant increased productivity by 14% for all agents and 34% for novice agents. Beyond productivity improvements, simplified knowledge retrieval improves customer satisfaction and reduces operational costs.
Educational institutions use Conversational AI to manage informational resources for students. AI-powered chatbots integrated into centralised knowledge bases answer routine questions: Questions about course details, enrolment processes, financial aid, and campus resources. This reduces administrative workload, ensures consistent information delivery, and affords students 24/7 access to information.
But Conversational AI can do much more than deliver documented information. As just one example, in 2018, Deakin University in Australia launched Genie—a voice-controlled digital assistant that runs on students’ phones—to help them manage schedules, assignments, and “all general aspects of university life.” Students at Deakin can ask Genie virtually any university related question such as when an assignment or a library book is due, a class timetable for the coming week, on-campus directions, and suitable educational resources for a class they’re taking.
In corporate training and employee onboarding, Conversational AI enables new hires to verbally ask AI systems about company policies, operational procedures, compliance guidelines, and such—and immediately receive accurate answers. The result is a more efficient onboarding experience because learning is accelerated for new hires, knowledge dissemination is consistent, and HR staff is freed from having to answer the same enquiries over and over.
Many large companies have implemented Conversational AI in this area. In 2023, Walmart began using a gen AI tool that—among other things—helps new hires during orientation. The company also uses an AI voice assistant, Ask Sam, that helps in-store associates by answering spoken questions about products, prices, and so forth. Then, in 2021, global banking giant HSBC deployed a chatbot called Operational Resilience and Risk Application (ORRA), which answers employee queries on internal policy in diverse operational areas including risk management and data privacy.
Very significantly, in 2018, IBM deployed an internal chatbot called AskHR for the benefit of its employees worldwide. AskHR answers routine questions about HR policies, benefits, and onboarding tasks. As of 2024, AskHR was handling fully 94% of IBM employees’ HR-related queries.
Governmental organisations are increasingly deploying Conversational AI, often through online portals and dedicated mobile apps, to ease public access to extensive records and informational resources. AI-powered chatbots help citizens quickly and easily find information about government programs, regulatory guidelines, and available public services. This doesn’t just reduce the barriers to information access; effectively, it also improves access to services. In turn, this enhanced accessibility improves transparency, citizen engagement, and their trust in Government.
An excellent example of Government using AI for public benefit—specifically, to communicate information in easily understandable form—comes from March 2025: The Arizona Supreme Court began using virtual reporters to report and explain every ruling made, and opinions expressed, by justices. The goal of the Court with this move was to promote trust and confidence in the judicial system; the Chief Justice expressed the idea that such virtual reporting could help the public better understand the underpinnings of complex legal decisions.
The applications we’ve explored highlight how Conversational AI combined with effective KM enhances organisational efficiency and information accessibility. But even with the remarkable capabilities of AI, human expertise remains essential: It is required to ensure the accuracy, relevance, and continual improvement of AI-powered knowledge management systems.
Humans and AI in KM: Collaboration and Empowerment
As organisations increasingly integrate AI into their knowledge systems, humans will increasingly focus on supervision, ethical considerations, and strategic alignment to ensure that KM systems remain human-centred: While AI can automate many aspects of KM, it should ultimately serve as a tool to augment human capabilities. For effective AI-enabled KM, humans need to perform numerous critical functions:
Knowledge managers should ensure that AI models are trained on accurate, current, and relevant information to maintain the integrity and reliability of organisations’ knowledge bases.
Complex or nuanced questions should be addressed by subject matter experts and experienced employees—questions that require human judgment, emotional intelligence, or problem-solving skills that are beyond current AI capabilities.
Regular, detailed feedback should be provided to AI systems by developers and user experience specialists. Such feedback guides the ongoing development of the systems so their output aligns with organisational objectives, ethical standards, and user requirements.
Compliance officers and ethics committees must oversee the deployment of AI-powered knowledge management systems. They must ensure responsible use and accountability for the considerations of data privacy, transparency, and the ethical implications of automated decision making.
The Future of KM is More Intelligent and Adaptive
As AI evolves, KM will become increasingly intelligent and adaptive. AI-powered KM systems will be able to anticipate user needs and provide timely information and insights before they are explicitly requested. They will support multimodal interactions—which integrate voice, text, and visual inputs—in information retrieval to create even more natural and engaging user experiences. The incorporation of emerging technologies such as augmented reality and virtual reality (AR and VR) will further enhance KM by enabling immersive access to information.
Future KM solutions are expected to leverage advanced predictive analytics to identify knowledge gaps and proactively address potential information bottlenecks in organisations.
As responsibility and accountability in the use of AI increase, strong ethical frameworks and transparency standards will become increasingly important.
In conclusion, Conversational AI will continue to transform KM. Organisations will need to responsibly adopt this powerful technology with a strong emphasis on data accuracy, privacy, and ethical considerations.
What’s Next in this Series?
In Part 3 of this series, we will explore Conversational AI in Customer Support Automation, examining how AI-driven solutions improve customer interactions and streamline service operations.
How do you see AI transforming Knowledge Management in your organisation? Share your thoughts in the comments!
References and Further Reading
- 10 Knowledge Management Challenges [and How to Tackle Them] (Knowmax)
- 5 ways IBM is using AI – Case Study [2025] (DigitalDefynd)
- AI agents for human resources [HR] (IBM)
- AI in healthcare: The future of patient care and health management (Mayo Clinic)
- AI is shaping the future of knowledge management (ClearPeople)
- AI transparency: What is it and why do we need it? (TechTarget)
- Arizona Supreme Court explains why it’s using AI reporters (Arizona’s Family)
- Arizona Supreme Court taps AI avatars to make judicial system more publicly accessible (Arizona Daily Star)
- Better health outcomes with AI-powered virtual assistants (IBM)
- Deakin’s Genie: a virtual digital assistant out of the bottle (Deakin University)
- Generative AI at Work (National Bureau of Economic Research)
- Helping Associates Succeed at Work, While Elevating Customer Service & Safety (Walmart)
- How to Develop an Effective AI Governance Framework? (Securiti)
- HSBC deploys Dialogflow, easing call burden on policy experts (Google Cloud)
- Human and artificial cognition (ScienceDirect)
- IBM Watson: From healthcare canary to a failed prodigy (Healthark insights)
- Legal Trends Report (Clio)
- Multimodal Search: Transforming Workplace Knowledge Access (GoSearch)
- Seven market knowledge management trends to be aware of in 2025 [powered by AI, of course] (Market Logic)
- The CHRO of IBM reveals what went wrong with their initial AI chatbot rollout—and how they shifted strategies (Fortune)
- The Genie is out of the bottle, and at your service – a glimpse into the future (Terminalfour)
- The Potentially Large Effects of Artificial Intelligence on Economic Growth (Goldman Sachs)
- Top Knowledge Management Trends and Statistics in 2025 (Helpjuice)
- Walmart rolls out generative AI-powered assistant to 50K employees (CIO Dive)What is knowledge management? (IBM)
Table of Contents
