In this hyper-connected era and ubiquitous computing world, a tsunami of knowledge is being generated and shared by organisations.  The key concern is that knowledge alone cannot work its magic.  Knowledge should be tied to action to deliver real value in the form of cutting-edge innovations and streamlined internal processes. As technologies advance and ways of working change, knowledge management should also be redefined to achieve maximum benefits. Here is a list of some of the notable knowledge management trends that you cannot miss out on. 1. Cloud Continues to Rule Cloud hosting is a great option that is incredibly flexible and secure. To make the most of a SaaS knowledge management system, you need two things – an internet connection and a device (laptop, mobile phone, or desktop). Modern cloud-based knowledge management systems are based on a subscription model where you just pay for the services you opt for. 2.       Friendly User Interface for Effortless Navigation A good user interface facilitates a smooth interaction between the user and the knowledge management system. It is not just aesthetically pleasing but also responsive, uncluttered, and easy to navigate. 3.       Social Media Elements for Higher Engagement There is a reason why people love using social media. It keeps them connected and informed just with a few clicks and swipes. Features like activity streams, votes, likes, comments and instant sharing facilitate the culture of ‘collaboration with a click’. 4.       Information Mobility Mobile technology is here to stay for a long, long time. One major reason behind this is the heightened convenience and accessibility it provides. Today, most of the knowledge management systems are compatible with mobile phones, making information available in a flash, whether your employees are in the office or working remotely, or traveling. This information mobility promises higher productivity, better decision-making, and borderless collaboration. 5.       100% Customisation To offer feel-good experiences to employees, a knowledge management system must literally feel familiar to read and browse. A lot of information can overwhelm readers, but the way it is presented can make all the difference between good and poor employee experience. 6.       AI-Powered Search for Quick Content Discovery A knowledge management system amounts to nothing if it does not have a powerful search engine. That is why AI-powered search that works at the speed of light is a prominent knowledge management trend for this year and all coming years. Unlike a normal search system, AI-supported search produces the most relevant results after analysing the user’s search history and the context of the query. 7.       Support That Never Sleeps Customers are the primary source of revenue for any kind of business. That makes customer support an important area that cannot be ignored at any cost. Besides knowledge sharing and collaboration, a state-of-the-art knowledge management system can even help in customer support. Seeing this possibility, businesses today are employing knowledge management systems for both internal and external use. 8.       Media-Rich Content for Higher Engagement Traditional knowledge management systems consisted of lengthy documents and guides. Today’s knowledge management trends are in line with what employees want – a seamless and engaging knowledge-seeking experience. More focus is now given to content that is a rich mixture of text, images, and videos. 9.       Real-Time Notifications to Keep Employees Updated Every member having access to your KMS will get instant notifications regarding article updates, new sections created policy changes, and much more. 10.   Pragmatic Analytics for Impeccable Experiences Companies today know the tremendous power of data and analytics. Analytics helps you understand your KMS and related employee experiences in ways you cannot even imagine. Right from what your employees frequently search for to the path they take through your knowledge base, analytics decode every little activity. Analytics gives actionable insights into how many employees access your knowledge base, the language they speak and the country they live in, the bounce rate on specific pages, and much more. 11.   Powerful Collaboration Tools A knowledge management system is slowly becoming an all-purpose tool, with companies now trying to use it for both knowledge-sharing and collaboration. One of the major benefits of a knowledge-based management system is that it facilitates company-wide knowledge exchange. 12.   Flexible Management of User Roles & Permissions One of the notable features of a knowledge management system is its ability to streamline user management and define each member’s roles and responsibilities. You want a culture where employees can contribute their knowledge, share suggestions, and receive feedback, but with some level of governance. Flexible user management with you having complete control of what each user is responsible for is one of the most notable knowledge management trends for the future. 13.   Digital Workspaces A knowledge management system is a social platform where information is shared, organised, and stored securely. A digital workspace is a new idea in knowledge management that keeps your intranet segmented and organised for easy reference. If implemented, it can streamline the way knowledge is managed and shared across departments. 14.   Discussion Forums A knowledge management system is incomplete without a discussion forum. Simply coming to the KMS, sharing and retrieving information from the articles written is old school. Modern knowledge management solutions are equipped with a full-fledged discussion forum where employees can ask questions and get a response within seconds. 15.   Knowledge Bots For Prompt Access to Information The ultimate goal of a knowledge management system is to make knowledge-gathering a seamless, uninterrupted process. Knowledge bots help you achieve just that. Knowledge bots deliver relevant answers at the speed of light through chat or voice mediums. Knowledge bots act as personal assistants giving employees everything they need at a moment’s notice.

KM reference (https://www.knoco.com/knowledge-management.htm ) Story-powered communication / business story-telling (https://www.anecdote.com/ ) Real KM - evidence based, practical results (https://realkm.com/ ) Green Chameleon Blog (http://www.greenchameleon.com/ ) APQC (https://www.apqc.org/expertise/knowledge-management ) Knowledge Management Global Network (KMGN) (https://www.kmglobalnetwork.org/ ) Cynefin Co. - making sense of complexity (https://thecynefin.co/our-thinking/ ) The KMedu Hub - The Body of Knowledge for Knowledge Management Education & Training (https://kmeducationhub.de/ ) Gurteen Knowledge Website (https://www.gurteen.com/gurteen/gurteen.nsf/ ) KMWorld (https://www.kmworld.com/ ) Stan Garfield’s KM Site (https://sites.google.com/site/stangarfield ) Step Two Designs (https://www.steptwo.com.au/services/expertise-knowledge-management/ )

Originally published by KMI Dec 06, 2023 | By KMI Guest Blogger Alicia Rother We frequently hear the phrase "knowing more means accomplishing more" in our modern, data-saturated world. Even though organizations possess vast quantities of data, the true challenge does not consist solely of data collection. The true trick is to handle it properly and make sense of it. Thankfully, that's where AI comes in! Artificial Intelligence (AI) is changing the way we store, organize, and use information to better face future problems and gain a competitive advantage. Read on to learn more about how AI is changing Knowledge Management (KM) and the tools that make it happen. Let's see how AI can help! How Knowledge Management (KM) Has Progressed Over Time? In the past, knowledge management relied heavily on manual record-keeping. However, that evolved into digital repositories of knowledge and content management systems. The organized process of producing, gathering, saving, and sharing information within a company is called knowledge management. Conventional methods of knowledge management significantly depended on manual labor, including the setting up of documentation repositories, intranet portals, and databases. But it turned out that these methods required a lot of work, took a long time, and weren't always effective. The digital era has brought up new issues due to the vast amount and complexity of data. It's getting harder and harder for typical knowledge management systems (KMS) to keep up with the fast growth of unorganized data, which makes it harder to access and use knowledge effectively. AI's Role in Knowledge Management AI has changed the way information is managed in big ways. However, knowledge and information management are equally essential to AI. Like in everything else today, this technology is playing an important role here too. If you consider fields like graphic design, AI tools have already taken over conventional methods. Similarly, the data that an AI model is trained for in KM may have a major impact on its performance. The AI is more likely to give accurate responses when it is trained using information that is precise, current, and carefully structured. MIT researchers found that adding a knowledge foundation to a language model improved output and reduced hallucinations. Thus, rather than eliminating the necessity for KM, advancements in AI and machine learning merely increase its importance. The following is a list of 11 different ways that artificial intelligence has been used to solve some of the complex problems that everyone who uses KM solutions has to deal with: ➢ Advanced Analysis: AI can identify patterns and trends in massive data sets and provide useful insights. To do so, AI processes data using statistical models and machine learning methods. By looking at how factors are related to each other, AI can find patterns and trends that people might miss. This is more than just adding numbers together; it's figuring out what the organized data means. KM uses pattern recognition and natural entity extraction to find related information. ➢ Proactive Knowledge Discovery: AI can actively search for fresh, relevant information, guaranteeing that knowledge bases are constantly up-to-date. AI uses unsupervised learning methods to identify patterns in unstructured information, such as association and clustering. This uncovers new insights and goes beyond simple data retrieval. An intriguing example of this use case is how the finance division of a Fortune 500 business uses AI to analyze a variety of economic data to find unusual investment possibilities ➢ Collaboration Tools: Predictive analytics may predict user requirements and offer appropriate papers or meeting schedules based on behavior, enhancing individual productivity. AI teamwork tools let people talk to each other in real-time, share documents, and work together to solve problems. Based on what teams have done in the past, they can get advanced ideas for how to share documents or schedule meetings. ➢ Intelligent Search: AI combines conventional search algorithms with semantic knowledge. It can figure out what the user is trying to say by inferring context from their questions. This makes sure that search results fit what the user wants instead of just matching keywords. Employees may now get accurate, contextually relevant info even when they look for confusing or frequently used phrases. ➢ Content Tagging and Categorization: Artificial Intelligence can automatically tag and classify newly entered data, thus guaranteeing consistency, decreasing redundancy, and eliminating the labor-intensive process of manually classifying data. Using supervised learning, the AI is instructed on pre-labeled data. It is hardly unexpected that KM systems have embraced this feature broadly, as it greatly minimizes the work involved in selecting and organizing content. ➢ Smart Chatbots: To understand what users are asking, chatbots use Natural Language Processing (NLP). These chatbots provide fast access to information, offering essential information on demand. ➢ Expert Systems: AI makes choices in expert systems based on a set of rules that have already been set. The rules come from a human-in-the-loop, which lets the system act like a human expert in certain areas, making sure that accurate information is transferred. When used appropriately, AI-based expert systems can (mostly) replicate human decision-making and transform implicit information into organizational knowledge, which is essential to successful knowledge management. ➢ Recommendations: AI can make suggestions for related content or courses by learning how each user acts, which improves adaptation. With a corporate learning platform, for instance, employees may get recommendations for courses based on their learning history and the preferences of their colleagues in comparable positions. ➢ Virtual Assistants: Virtual assistants employ NLP to interpret user requests and task automation algorithms to perform a range of activities. While these AI-powered tools can process content, set notes, and even summarize long papers, they make KM tools more engaging for users and easier for them to use. ➢ Creating Content: AI can mine datasets, make outlines and reports, and make sure that knowledge bases are always being updated and expanded. It may also use NLP to make sure the content's language is appropriate for the target audience. This feature lets strategy teams automatically make outlines of 50 pages or more documents or a group of documents. The same feature may be used by sales teams for generating battle cards for major rivals or account profiles for mining current clients. ➢ Knowledge Transfer and Sharing: AI may assess user behaviors and propose relevant content to them. This feature could be used by the IT-KM function to automatically offer a new IT training program to workers whose past contacts show they need an update. Tips on How to Use AI in Knowledge Management For organizations to get the most out of AI in KM, they should think about the following strategies: Set Clear Goals: Write down clear objectives for incorporating AI into KM. Having clear goals is important whether you're trying to improve customer service, streamline internal processes, or spur new ideas. Ensure Data Quality: The quality of the data supplied into the system is critical for determining the accuracy and dependability of AI-driven insights. AI models should be updated and improved regularly to make sure they stay useful and effective. Emphasis on User Adoption and Training: Workers should get training on the efficient usage of AI-driven knowledge management systems. To get the most out of AI in knowledge management, people need to know what their job is in this new environment. Prioritize Privacy and Ethical Considerations: Make sure AI systems are fair and neutral and create strict privacy measures. This is essential for trust and data protection. Acknowledge Continuous Improvement: The domains of AI and KM are ever-evolving. To stay ahead of the game, tactics and tools need to be updated and improved regularly. Conclusion There is no doubt that AI will play a big role in the future of KM. By properly incorporating AI into KM plans, firms may achieve unparalleled levels of efficiency, customization, and strategic insight. Getting there will take careful planning and attention to things like data quality, the right way to use AI, getting people to use it, and always being able to adapt to new technologies. The possibilities for growth and advancement are endless as we go forward into the intelligent future of KM.

Knowledge Management is the process of creating, retaining, sharing and better utilising the knowledge and information assets of an organisation to achieve its objectives. KM Week - 16 to 21 October 2023

PHOTOS PROGRAMME

KMSA Webinar: Knowledge automation through using Generative AI ​ Tuesday, 12 March 2024 13:00 - 14:00 CAT In this webinar, we will discuss the potential contribution of Generative AI in information processing and generation. Generative AI, such as GPT-3, enables the automation of knowledge-intensive tasks by synthesising human-like responses based on the prompting input provided. This technology can rapidly generate diverse and contextually relevant content, streamlining tasks like content creation, customer support, and even code generation. The ability to support knowledge processes with generative AI not only increases efficiency but also allows for the scaling of intellectual capabilities across various domains. However, ethical considerations, responsible use, potential biases, accuracy and the skill to develop good prompts need to be carefully addressed as we navigate the evolving landscape of knowledge automation through Generative AI. The emphasis on the human touch from the human-centred society (Society 5.0) will be contextualised from a knowledge management perspective. SPEAKERS Prof Marlene Holmner Prof Holmner obtained a BA degree from the University of Pretoria in 1995, and a BA (Hons) Information Science (Cum Laude) in 1997. This was followed in 1999 by an MA Information Science (Cum Laude) from the same institution. Prof Holmner completed her D (Phil) in 2008 with the title: A critical analysis of information and knowledge societies with specific reference to the interaction between local and global knowledge systems. Prof Holmner joined the Department in 1995 as tutor and has been lecturing in the department for the past 25 years. During this time, she delivered numerous conference papers covering aspects such as ICT for development and bridging the digital divide. Prof Holmner is the chair of the marketing committee of the School of Information Technology and is a Microsoft Certified Professional and is a member of the Africa Network for Information Ethics. Prof Martie Mearns Prof Martie Mearns is an Associate Professor and contract lecturer involved at the University of Johannesburg, where she mainly teaches research methodology at Honours and Master’s level. At the University of Pretoria, her lecturing tasks are focussed on the field of information science and knowledge management, aspects of the fourth industrial revolution and competitive intelligence on undergraduate and postgraduate levels. She has been involved in higher education tuition and research since 1998. Ms Anika Meyer Ms. Anika Meyer is a Lecturer in the Department of Information Science, University of Pretoria. Her journey as a dedicated and passionate lecturer and researcher in the Department of Information Science, at the University of Pretoria, commenced in January 2015. She completed her Master's studies in 2016, titled: Information behaviour in academic spaces of creativity: a building science pseudo-makerspace. She is currently enrolled for her doctoral studies at the Department of Information Science, University of Pretoria, titled: Information sharing in participatory design of a virtual academic creative space. REGISTRATION FEES: ​ Paid up KMSA Members: No charge Non-KMSA Members: R450 Online registration is now closed, should you still wish to register please contact kmsaservices@vdw.co.za