With the increasing complexity and remote nature of organizations, data management has become an enormous challenge at the enterprise level. The distributed teams, remote work, and multiple knowledge systems have made it difficult to track down data across the entire enterprise knowledge ecosystem. This knowledge access challenge results in a loss of productivity and employee engagement.
The Impact of Generative AI on Enterprise Search
Generative AI has emerged as a game-changer for businesses in addressing knowledge access challenges. It provides employees with full access to the knowledge they need, and its context, anywhere in the organization. Traditional enterprise search tools cannot reach all the knowledge in an organization, particularly unstructured knowledge such as the information communicated through IM, Teams, Slack, and email.
The Three Major Benefits of Generative AI
There are three major benefits of leveraging generative AI in enterprise search. First, it brings a quantum leap in user experience, providing workers with a digital knowledge assistant that enables them to find precise answers quickly. Second, it automates repetitive tasks and streamlines workflows, freeing up more time for complex tasks and greatly increasing productivity. Lastly, generative AI solutions can be precisely refined for industry-specific and case-specific use.
The Three Pillars of the Trusted Knowledge Model
To bring generative AI into the workplace, it requires a trusted knowledge model composed of three pillars. The first is company knowledge and context, which allows for a trusted knowledge model to form out of the combination of these things. The second is permissioning and data governance, which is being aware of what information the user should and should not have access to. The third is referenceability, which allows users to verify where the system is pulling information from.
Generative AI means moving from questions into decisions, decreasing time to knowledge. With augmented answer-first enterprise search, the user can express the underlying journey and overall decisions that need to be made, and the large language models (LLM) agent brings it all together. An LLM agent can go and figure out all the information that the user might need, collect that information, synthesize it, and deliver it to the user.
Generative AI has transformed how knowledge is accessed and used in enterprises. It can improve employee productivity by facilitating information access and discovery, creating more intelligent, personalized, and effective experiences. Companies can now build searches specifically for the workplace, built for internal searches that work across internal systems. Importantly, these searches are built on a knowledge graph that returns a search that’s more relevant to employees.
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