In today’s fast-paced business environment, having access to accurate and timely information is crucial. But what happens when workers get trapped in a labyrinth of systems and documents, unable to find the information they need? The result: stalled productivity and innovation. 

In our recent webinar with KMWorld, we delved into the current landscape of enterprise information discovery, the barriers holding enterprises back from delivering business-critical information to end users, and the transformative potential of Knowledge AI. 

If you didn’t have the chance to watch the live webinar featuring Joe McKendrick, analyst and author for Unisphere Research, and Jason Zhou, VP of Solutions, Services, and Customer Success at Pryon, here are the key takeaways: 

The state of enterprise information discovery — 2024 survey results

Joe McKendrick kicked off the discussion by unveiling key insights from the 2024 Survey on Enterprise Information Discovery, of which he was the analyst and author. The results painted a stark picture: despite the digital age’s promises of efficiency, many employees are still struggling to get timely answers from the fragmented content scattered across their organizations. From disparate content management systems to siloed data repositories, valuable knowledge remains buried beneath layers of digital clutter. 

As Joe aptly put it, “Risk increases as access to knowledge assets decreases … Your risk goes up the less access you have to the information you need to serve customers and other parts of your organization.”  

Stalled information access is costing enterprises thousands of hours of lost productivity

The consequences of this information access breakdown are far-reaching. Joe shared more eye-opening statistics from the 2024 survey, revealing how stalled information access is exacting a hefty toll on enterprise productivity. According to the survey, 70% of enterprise leaders report that employees in their organization spend an hour or more looking for a single piece of information. And nearly a quarter (23%) report spending more than 5 hours per piece of information. With employees losing countless hours over an average work week hunting for answers, enterprise leaders need to prioritize solutions to get answers for their teams when and where they need them.  

As Jason Zhou put it, “If you think across your enterprise, there is probably tons of very valuable knowledge from your employee handbooks, your ticketing files, your engineering documentation, all the way through the org. And if the end consumers, whether those are your customers or your employees, had perfect access to those resources and could find the information they need, just imagine what that would mean for the enterprise in terms of an improvement in efficiency and in your ability to just get your job done at the end of the day.”  

Enabling technologies in knowledge management — how Knowledge AI can help

Amidst these challenges, Knowledge AI offers a promising path forward. Joe shared that the top two use cases enterprise leaders are considering AI for this year, as identified in the survey from Unisphere Research, involve helping users better understand and get answers from the content sprawled across their organizations. Knowledge AI platforms do this by unlocking the hidden knowledge buried within enterprise content repositories and transforming that knowledge into answers. By leveraging cutting-edge technologies like computer vision (CV) and optical character recognition (OCR), a Knowledge AI platform reads and understands your content like a human would. Then, when a user asks a question, the platform uses a retrieval-augmented generation (RAG) framework to extract relevant knowledge and turn it into instant and accurate answers. 

As Jason highlighted, “Knowledge AI can really be spread throughout the entire organization and live wherever that information lives to help deliver insights that empower people to be able to better use and make decisions based on that knowledge.”  

Getting started with a Knowledge AI platform

Jason’s top tip for getting started with Knowledge AI: “Meet your users where they are.” This means your Knowledge AI platform should be able to plug into the places where your content is already stored, such as SharePoint, Confluence, S3 buckets, and so on. At the same time, the platform should offer multi-modal solutions for the end user to engage with it quickly and easily. Users should be able to receive answers in existing tools and through different modalities, like text and speech.  

Ready to dive deeper? Watch the webinar highlights or reach out today to learn how Pryon can transform your content into accurate, timely, and verifiable answers via the world’s first enterprise-grade Knowledge AI Platform. 

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