- June 20 2024
- 10:00 AM EDT
- Online Event
Overview
In today’s increasingly data-driven world, the age-old saying “knowledge is power” resonates more deeply than ever before. As businesses accumulate vast amounts of data, the real challenge isn’t only about collecting information, but effectively managing and extracting valuable insights to fast-track the desired outcomes. GenAI is emerging as a revolutionary force for transformative Knowledge Management (KM). It reshapes the knowledge creation and curation process, enables quick access to information, and aids in creating knowledge resources with higher accuracy and speed.
In this webinar, our experts discussed how GenAI is transforming KM and how different technology accelerators can be leveraged to get the most out of your KM program.
Speakers
Shobhit Saxena
Associate Director, Product Lead, Evalueserve
Michal Radziuk
Director, Customer Success Lead, Evalueserve
Nate Bourns
SVP Global Strategy, DAI
Here's a sneak peek of what you'll discover from this webinar:
- Understanding the Current KM Landscape: The concept of 'Knowledge Management' is constantly evolving and is now known by different names such as enterprise intelligence, unified knowledge, etc. This shift is driven by the convergence of KM with various use cases, leading to different teams and functions adopting decentralized initiatives and new names for their knowledge management efforts. There has also been a noticeable increase in discussions about KM as a business objective - investment decisions are being made faster and there is an increased coverage of KM solutions by technology analysts. However, the business objectives associated with it remain the same, such as reducing duplicative work, tapping into tacit knowledge, retaining knowledge, and using knowledge as a tool for competitive advantage. KM is now being factored into the overall strategy at the highest level for many businesses.
- How Business Leaders are Approaching KM: Business leaders today are looking for effective knowledge management strategies. There is a growing realization that GenAI is revolutionizing what can be achieved and leaders are looking at ways to explore its full potential in the knowledge management space. A crucial consideration is developing custom tools and approaches. However, it is also being considered that the performance of consultants can suffer when dealing with challenges beyond custom tools and it can be hard to pinpoint exactly where the boundaries of these challenges lie as they are always evolving. To address these challenges, business leaders need to revisit basic business principles. The starting point should always be to identify areas where maximum value can be generated and then work backward to design a solution that enables users to benefit in the long term from a knowledge management program.
- Key Legacy KM Challenges to Consider: It's important to note that AI and GenAI alone cannot effectively improve a KM program without proper data organization and tagging. Businesses, including global consulting firms, generate thousands of documents daily, simply applying GenAI without structured data will result in suboptimal outcomes. Data annotation is a significant legacy challenge. Providing additional context to various knowledge assets with meta tags and labels can be complex due to the unique taxonomies and changing complexity of data assets within each organization. In addition, other legacy challenges such as duplication, document versioning, and redundancy should be taken into consideration as well. Hence, it’s important to first solve these fundamental issues related to data annotation and document parsing. The old saying "garbage in, garbage out" applies well to generative AI as well. On the other hand, it’s also important to solve ancillary issues such as ensuring user adoption and better integration across decentralized business processes.
- Adoption of GenAI Tools from a User Perspective: The adoption process for GenAI features and non-GenAI features in a product is quite similar, but the barriers for users are different and possibly more complex. The process can be visualized as a funnel, starting with creating awareness about GenAI features and then activating users to ensure engagement, loyalty, and advocacy. The challenges for generative AI features are unique for users. For example, building trust may be more difficult due to concerns about the quality of output, security, and data confidentiality. Additionally, there may be skill gaps, as not everyone is an expert in prompt engineering. Furthermore, the usage patterns for generative AI features may differ slightly from traditional features. For example, user sessions for GenAI features may be shorter but more frequent. This usage pattern needs to be considered at the product design stage, ensuring that the user experience reflects these new usage behaviors. When building adoption strategies, education and trust aspects need to be considered as well.
- GenAI Beyond Chatbots with Real-world Applications: One important application for GenAI in KM is content management - GenAI can play a crucial role in annotating data, automatically tagging documents and content, and summarizing large and complex documents. GenAI can also be used to create summaries and initial drafts of content to speed up the marketing, sales, and pre-sales processes. Another use case is around sanitizing content, especially when sensitive information needs to be removed before making it available organization-wide for knowledge sharing. GenAI in KM can also be leveraged for unified insights generation from both structured (e.g., Excel databases) and unstructured datasets (e.g., text-heavy content, images). GenAI can help reduce barriers to data consumption and provide more contextualized and in-depth responses, allowing for a deeper understanding of data trends and enabling users to explore the reasons behind certain events.
About Publishwise
An AI and Gen-AI powered platform that lets you swiftly look up past content (RFPs/RFIs, DDQs, Marketing Content, and other knowledge assets) using Modern Search and Recommendation Engine. The search functionality is backed by a customized Semantic Engine. The Recommendation Engine uses NLP and ML for content recommendations. The platform can be easily integrated with CRMs and content management systems. Key features:
- Create - A GenAI module to auto-generate the first draft of content such as RFP responses, investment memos, document summaries, blogs, company profiles, etc.
- Converse – GenAI powered Digital Assistant allows users to find information via natural language and offers a unique user experience and features
- Discover - NLP and Machine Learning recommendation engines to parse large documents into sections and recommend relevant content
- Search - Semantic Search eliminates the need-to-know exact keywords and focuses on the knowledge needs of the user
- Integrate – Seamless integration with internal and external data sources & applications for maximum value creation (CRMs, SharePoint, Box, etc.)
About Evalueserve
We’re a leading technology-enhanced managed services provider. Our insights and analytics solutions optimize your workflows, accelerate decisions, and scale business impact. We support our clients in achieving maximum impact by turning information and insights into decisions with dynamic AI/GenAI-driven products and solutions delivered by our 5,000+ domain experts.