Recently I had an ad-hoc monthly management meeting request. I spent the entire afternoon sifting through countless emails and SharePoint links to find last year’s budget presentations from the different departments. I had to navigate through all those poorly labelled folders, call half a dozen colleagues and subsequently manually compile the information from four different templates. I just submitted 5 minutes before the deadline. Obviously, I missed the family dinner. Trust me, one drink was not enough that night.

– Sam, project manager of a S&P 500 TextCortex client describing his struggle

Knowledge – A Very Costly Enterprise Struggle

Every corporate employee can relate to Sam's experience in one form or the other. In fact, 47% of digital workers struggle to find the data and information they require to perform their actual job. 

Knowledge – A Very Costly Enterprise Struggle

On average, employees spend 9.3 hours a week, or approximately 25% of their time, sifting through information. Considering that enterprises generate 72% of the global GDP, this inefficiency problem equates to a staggering $15 trillion. With recent advances in generative AI (Gen AI), there may now be a viable pathway to address and mitigate this issue, offering hope for increased productivity and reduced frustration among employees.

How Knowledge Management Works Today

Currently, knowledge management is a daunting task for most organizations. Employees often face the pressure of keeping everything up to date and well-structured, while managing their primary work responsibilities. Naturally, it is clear what gets prioritized. The lack of effective governance, process structures and incentives further complicate matters. Either these are non-existent or siloed, resulting in inconsistent results and redundancy. Tools like Google Drive, Microsoft SharePoint, Notion, Guru, or Confluence manage the actual storage, but less the challenge of effective governance topics such as up-to-date authorization, historization/archiving, logical structuring, or effective search functions.

The numbers underlie this grim picture. 22% of all data within enterprises becomes irrelevant every year. Hence, combined with the absence of effective governance, on average around 60% of total data within an organization is outdated. This leads to a lack of trust in enterprise data, with 75% of executives reporting low levels of trust. This challenge will only be accelerated if one takes into account that the average enterprise data volume grows by 30% annually. Consequently, without a robust technology solution, finding relevant information will be more and more akin to searching for a needle in a haystack.

How Can Gen AI Help?

Gen AI enterprise platforms, such as TextCortex, present a significant advancement in solving this knowledge management conundrum. These tools allow for seamless integration across different storage solutions (e.g. Microsoft OneDrive (SharePoint), Google Drive).

Subsequently, employees can prompt their requests and receive synthesized outputs and answers, completed with references that lead them directly to the quoted documents.

This solution does not require introducing new storage solutions nor the necessity of doing an entire data clean-up or restructuring. Additionally, the entire process is fully GDPR compliant, the enterprise data is never stored somewhere else, and it also allows leveraging the existing access management solution. Ultimately, these tools eliminate the frustration of searching for information and enabling employees to focus on tasks that add real value to the business.

See the results from one of our case studies:

  • TextCortex was implemented for Kemény Boehme Consultants as a solution to tackle these challenges and today employees report increased efficiency and productivity (saving 3 work days per month per employee on average).
  • AICX, an ecosystem partner of TextCortex, was integral to the onboarding and helped achieve a 70% activation rate of the team within the first weeks.
  • Employee confidence in using and working with AI increased by 60%.‍
  • The implementation results in a 28x return on investment (ROI).