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Pharmaceutical, Life Sciences

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Features

Promises and Perils of AI for Enterprise Knowledge Management

This survey reveals both excitement and trepidation around enterprise AI adoption for knowledge management. Long-standing problems around information access, data quality, and speedy acquisition of needed information are the puzzle pieces that AI has the potential to solve.

Overcoming data silos: A range of options

The options are many and varied when it comes to taming silos. The specific approach should depend on the use case, the organization's existing knowledge assets, and the strategic goals.

Modern KM tools and techniques for collaboration

Modern collaboration means and mechanisms ultimately make it easier, less risky, and more productive for organizations to work together within business units, between them, and between organizations. Constructs such as data mesh architecture, data fabric architecture, data access governance platforms, data catalogs, and process automation solutions are based on sharing information between parties—and make doing so tenable.

The future of KM is not simply AI

Until KM systems can achieve trust in AI, a totally AI-centric workplace will be a fantasy. The future of KM will be based on collaborative work habits, fueled by technology that encourages knowledge sharing, enhances productivity, supports employees to have a healthy work life, and accepts that not every aspect of knowledge management is technology-reliant.

ViewPoints

What you should know about cross-border data transfer laws

Multinational companies are generally aware of data transfer laws, but smaller ones just embarking on looking beyond country borders may not be.

KMWorld 2023 sees a sea change

Most of the papers presented at the 2023 conference did not report on what had changed. Instead, they assumed and predicted that there would be substantial change.

KM and AI: Experts look at what lies ahead for 2024

AI and dreams of its potential rocked this past year as companies moved quickly to embed and offer their own version of chat assistants, predictive and generative AI, and more

Decoding the data deluge; use ECM to navigate the unstructured content labyrinth

Obtaining contextual knowledge about how users create and interact with unstructured data is an essential business practice to plan for data storms effectively. Enterprises need to understand that it's not enough to know these user activities but also must take remediation action when necessary.

Columns

The trust problem with GenAI

2023 has been the year of ultra-hyping GenAI, and who is paying for this deluge of marketing? Technology vendors that want us to buy it. Again, it's impressive stuff, but when we shift from selling to buying and ultimately using it, many tough questions need to be asked.

When is good enough enough?

Our goal should be to improve the quality of knowledge assets and their accuracy and relevance in use. Much of this will come from human expertise and effort, increasingly combined with the power of AI.

Are you data-driven or knowledge-driven?

We no longer need to blindly accept the output of even the most sophisticated AI/ML platforms. In fact, we should not consider any artifact, whether produced by humans or machines, as valid knowledge unless it contains not only supporting data and analyses, including provenance, but also an explanation of the underlying plausibility.

AI technologies upending traditional KM

If we are not careful and proactive about it, the concept and importance of knowledge itself may soon become blurred or lost.

Knowledge Management Whitepapers

Document Viewing Integrations in Enterprise Content Management and Document Management Solutions

Business Impact of Technical Content – The ROI Paradox

Connecting external data sources to CCMS is now a breeze.

Knowledge Graphs Expose Data Connections

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