Enterprises are sitting on mountains of data, and the challenge isn't just collecting this information; it is about effectively managing and extracting knowledge from it. Artificial Intelligence (AI) is emerging as a transformative force in knowledge management(KM), reshaping strategies, addressing challenges, and paving the way for a future where knowledge is a competitive advantage.
In this blog, we will explore how AI is reshaping knowledge management (KM) and the knowledge management systems (KMS) that enable it:
Knowledge management has come a long way from its early days of manual record-keeping to digital knowledge repositories and content management systems.
Knowledge management involves the systematic process of creating, organizing, storing, and distributing knowledge within an organization. Traditional knowledge management approaches relied heavily on manual efforts, such as creating databases, intranet portals, and documentation repositories. However, these methods proved to be labor-intensive, time-consuming, and often inefficient.
The sheer volume and complexity of data in the digital age has also created new challenges. Traditional knowledge management systems (KMS) struggle to keep pace with the rapid accumulation of unstructured data, making it increasingly difficult to access and leverage knowledge effectively.
AI has emerged as a game-changer in the world of knowledge management. However, information and knowledge management are also key to AI.
The information an AI model is trained on can have a significant impact on its performance. If the AI is trained on accurate, up-to-date, and well-organized information, it will tend to respond with answers that are accurate. Research from MIT has shown that integrating a knowledge base into a language model tends to improve the output and reduce hallucinations. This means that AI and machine learning advancements, far from superseding the need for knowledge management, make it more essential.
Here's how AI is transforming the landscape:
In the era of information overload, AI could transform knowledge management into a strategic asset. As organizations leverage AI to capture, organize, and apply knowledge effectively, they gain a competitive edge in a fast-paced, data-driven world.
Opportunities of AI for knowledge management
The impact of AI on knowledge management systems (KMS)
Knowledge Management Systems are software platforms that facilitate the creation, storage, retrieval, and dissemination of knowledge. AI has revolutionized KMS in several ways:
Success in AI-driven knowledge management requires a clear strategy, a commitment to data quality, and a proactive approach to future trends.
Atlas by ClearPeople is a governance-by design platform that addresses the challenges and risks of an enterprise AI rollout. Atlas lets you take full advantage of Generative AI enterprise capabilities without compromising governance and compliance.
Atlas auto-tags content based on context, making it better anchored and instantly identifiable by Gen AI and Microsoft 365 Copilot. Also, by enabling relevant policies to be applied, Atlas can help to ensure you are compliant with strict governance requirements.
Atlas’ provisioning capabilities aid organizations in automating the assignment of content metadata according to contextual factors. Categorizing all enterprise content ensures a seamless transition into Microsoft 365 use, enabling organizations to immediately take advantage of AI capabilities, thereby improving its ROI (return on investment), effectiveness, and business benefits.
Atlas’ AI feature enables users to safely engage with AI through the organization’s private enterprise LLM (Large Language Models) (in Azure OpenAI services), ensuring compliance with organizational policies.
Atlas AI includes governance of organizational Terms & Conditions for end-users to confirm and sign before use, cost control governance, permission driven usage controls, as well as signposting of various guardrails.
Atlas AI will inject warnings into copied content, and will include citations and source references, to drive user behavior towards taking editorial control and ownership.
Finally, by augmenting the prompts with both contextual clues (using Atlas’ metadata model) as well as Atlas’ unique Knowledge Collections for AI, Atlas AI improves the accuracy of AI-driven content creation, reducing the likelihood of incorrect information and hallucinations.
A guide to getting ready for Gen AI and Microsoft 365 Copilot.
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