According to a study conducted by International Data Corporation (IDC), Fortune 500 companies lose approximately $31.5 billion annually by failing to share knowledge. The inability to share knowledge can cause substantial business losses, making it critical for organizations to upgrade their knowledge management strategies, including the adoption of robust knowledge management technology.
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Knowledge sharing is a critical stage of the knowledge management cycle and deals with an organization’s ability to acquire, organize, and share knowledge with different teams. For example, in every organization, IT support teams are constantly flooded with support tickets from employees and customers, which requires them to fix issues with agility and ease. To deliver this valuable technical support, they need to have all the required information at their fingertips. Therefore, it’s important to establish a solid knowledge-sharing culture that boosts the efficiency of IT teams in contributing value to the organization.
Knowledge hoarding is a big challenge organizations face today. To this end, artificial intelligence (AI)-enabled tools have considerable potential to manage data and help organizations to transform people’s experiences and knowledge accumulated over time into collective knowledge for the organization.
4 ways AI can improve knowledge sharing and bolster the efficiency of ITSM teams
1 – AI elevates knowledge discovery
The rapid rise in data volumes makes it difficult for organizations to organize information and share it with the right people. To better enable knowledge sharing, the first step is to make all the data and information held across the organization readily available and accessible to technical support teams.
Unlike with traditional IT service management (ITSM) tool search, an AI-enabled conversational user interface makes interactions with computer systems easy, seamless, and human-like. Semantic search understands the intent and context to interact with users and delivers relevant content stored in backend systems.
IT teams need to work quickly, so they need technology solutions that can understand their needs. An AI-powered knowledge base uses natural language processes to deliver the right content to the user by interpreting human speech and conversational patterns. AI also enables auto-tagging of content pieces, making it easy for IT support staff to discover knowledge base articles and FAQs and enhance their service quality.
2 – AI boosts team productivity through better knowledge sharing
To work efficiently and productively, IT team members need to communicate effectively with one another and stay aligned with the fundamental objectives and values of the organization.
An AI-powered centralized knowledge base for support agents increases the efficiency of IT, support teams, by providing them with a single source of truth platform for all their data needs. Support teams can easily access the relevant information for their use case without having to segregate data, helping them resolve more support tickets more quickly.
Embedding AI in organizational workflows improves teams’ problem-solving capacities by automatically getting primary user data from backend servers. With ready access to contextual data, support teams can apply their technical skills to troubleshoot complex issues. They can leverage bite-sized deliveries of data instead of going through long text-based documents, resulting in increased productivity. With a unified knowledge repository and standardized workflows, team members can make better decisions in real-time and stay compliant with business standard operating procedures.
3 – AI tracks user engagement to deliver better experiences
To share knowledge better, it’s vital to track knowledge consumption and application for different organizational needs.
Machine learning is one of the significant AI capabilities that improve user experiences by tracking their journeys and learning about their behaviors. It uses collective memory to elevate users’ search experiences and suggests sentences to increase knowledge findability. AI also prevents knowledge from becoming obsolete by tracking users’ search activities. It uses data to identify knowledge gaps and suggests updates quickly.
A robust knowledge-sharing platform avoids information overload by sharing the right knowledge with the right people. AI-backed micro-segmented analytics provide enterprise-wide visibility of content for better user experiences. It shares detailed reports of user engagement tracking down top-performing content and the time it takes to resolve specific queries, helping content creators to push relevant content to different support teams from the backend.
4 – AI helps to foster a culture of learning (as well as knowledge sharing)
Knowledge sharing can only happen in organizations when employees learn new skills and apply them to organizational needs. It’s practically impossible for IT teams to know everything all the time. The rise in technological advancements requires organizations to make it easy for employees to learn new things and enhance their skills. Creating a knowledge base management system equips support teams with advanced knowledge-sharing tools to help them handle multiple tasks efficiently.
It also makes it easy for users to acquire new knowledge, helping new employees learn things faster. Knowledge-sharing platforms significantly reduce the new employees’ training costs and time to foster an active learning culture in the organization.
Besides training employees and getting them up to speed with new information, it’s equally essential for organizations to retain the vital know-how by encouraging people to share their knowledge. To this end, knowledge base articles and FAQs are a great way to integrate subject matter experts in sharing their knowledge and disseminating the information across the organization.
AI can boost the knowledge management strategy of an organization by retaining vital information for future use, deriving actionable insights from data, and helping people acquire knowledge faster and efficiently.
Source: itsm.tools.com
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