Keynote - Knowledge Management In The Age Of AI
People & Blogs
Introduction
In the evolving landscape of knowledge management, particularly at Deloitte’s global knowledge management center of excellence based in Tel Aviv, we are witnessing a profound transformation fueled by AI and machine learning. Our center not only serves our local members but also has global reach, dedicating a substantial portion of our work—around 80%—to supporting various member firms worldwide.
One compelling narrative we encountered recently was the Phillips case study, which we will delve into shortly. Last year, we explored the immense potential of AI through the lens of another case involving Toyota. These examples are significant benchmarks that demonstrate our commitment to developing pragmatic AI solutions within knowledge management (KM).
The Pragmatic Use of AI in KM Solutions
While knowledge management inherently encompasses more than sheer technology—including governance, processes, and taxonomies—today's focus will be on the technological capabilities AI and machine learning present. I will showcase five practical examples:
1. Personalization of User Experience
Consider the Netflix recommendation engine: it clusters users based on similar preferences, learning their usage patterns. However, many organizational knowledge management solutions still offer a generic interface and content arrangement—regardless of the user's role or seniority. Users expect a fully personalized experience in the workplace akin to what they enjoy on platforms like Netflix and Amazon. The first recommendation for enhancing KM solutions is creating distinct personas and customizing the user experience, encompassing the user interface and content.
2. Conversational Interfaces
Chatbots represent a notable shift in user interaction. Research indicates that Millennials and Gen Z prefer conversational interfaces over traditional search engines. For instance, our developed chatbot, Delaney, can understand natural language queries and provide relevant answers. The chatbot application can differentiate between inquiries, which traditional search engines struggle to accomplish, streamlining the user's experience.
3. AI-Powered Typing
Our team has developed technology that enables autocomplete features for sentences and phrases, promoting efficiency. By leveraging historical data from similar users, the system can suggest full sentences, improving the collective knowledge representation without requiring individuals to start from scratch.
4. Auto-Tagging and Classification
Auto-tagging and auto-classification are game-changers in knowledge management. By implementing tools that automatically add metadata to documents, organizations can avoid the common barrier of manual data entry that hinders user adoption. Setting up these capabilities is now a basic requirement in our solutions.
5. Digital Adoption Platforms
AI-driven digital adoption tools have emerged to enhance user engagement. They analyze usage patterns and suggest resources dynamically, reducing dependency on IT Help Desks. Tools like WalkMe notify users about common stumbling blocks within software interfaces, guiding them to solutions and boosting overall adoption rates.
In summary, these five examples illustrate how leveraging AI in knowledge management can result in more efficient, personalized, and user-friendly solutions adapted to the needs of diverse personas.
We invite you to visit us at booth DE206 for further insights and discussions about the transformative power of AI in knowledge management.
Keyword
- Knowledge Management
- AI Solutions
- Machine Learning
- Personalization
- Conversational Interfaces
- Chatbots
- Auto-Tagging
- Digital Adoption Platforms
- User Experience
FAQ
1. What is the role of AI in knowledge management?
AI enhances knowledge management by providing personalized experiences, automating data classification, and facilitating user interactions using chatbots.
2. How does personalization improve knowledge management?
Personalization tailors content and user interfaces to individual user preferences and roles, making it easier for them to access relevant information.
3. What are the benefits of using chatbots in organizations?
Chatbots facilitate natural language interactions, enabling users to obtain information efficiently. They can understand context and differentiate between various inquiries.
4. Why is auto-tagging important in knowledge management?
Auto-tagging automates metadata addition to documents, significantly improving user adoption by eliminating the requirement for manual data entry.
5. How do digital adoption platforms enhance user engagement?
These platforms analyze user behavior and proactively offer assistance and information, streamlining the learning curve and increasing software adoption rates.
