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Businesswoman presenting to colleagues at a meeting. Generative AI and knowledge management

Generative AI and knowledge management: the perfect technology marriage

As the buzz around generative AI intensifies, executives and technologists in virtually every industry are scurrying to devise use cases for this powerful new technology and understand its potential impact on business operations, employee productivity, and customer experience.

One technology thought leader believes knowledge management will prove to be the killer application for generative AI.  EY’s global chief technology officer, Nicola Morini Bianzino, wrote recently in Harvard Business Review, “The ability to quickly retrieve, contextualize, and easily interpret knowledge may be the most powerful business application of large-language models. A natural language interface combined with a powerful AI algorithm will help humans in coming up more quickly with a larger number of ideas and solutions that they subsequently can experiment with to eventually reveal more and better creative output.”

Hard evidence for generative AI’s value in the enterprise is only now starting to come in.  For example, a new study conducted by researchers at MIT and Stanford within a Fortune 500 customer support call center suggests that generative AI can bolster employee productivity; in this particular case, among the 5,000+ employees involved in the study, “AI disproportionately improved the work performance of less skilled and less experienced workers.”

While that is compelling, it doesn’t mean customer support is where generative AI’s greatest impact ultimately will be felt in the business world.  Bianzino says in an interview in VentureBeat that as generative AI tools “evolve and improve, and can be trained on an enterprise’s data in a secure way, it will change the way we access and consume information inside the enterprise.

“The generation of text and documentation would also need to be trained and aligned to the proper ontology of the specific enterprise . . . and would need to be securely contained, stored, and controlled within the enterprise.”

Bianzino notes that EY has 360,000 people worldwide doing knowledge-intensive work. “‘But that knowledge is distributed now, you can’t really touch it; it’s the soul of our organization, but it’s immaterial.’ If you could systematize it into an ontology and make it part of a technology solution, you can increase enterprise value significantly.”

This is starting to happen already at some companies, as generative AI is being deployed against inside-the-firewall enterprise content collections for market and competitive intelligence to answer researchers’ direct questions.  Such advanced knowledge management functionality must expand to other business functions and content domains.

In his HBR article, Bianzino and his co-authors write that generative AI may have a real impact in the enterprise within a year, but that will require acclimation on the part of humans.  One piece of advice Bianzino offers to organizations seeking to utilize generative AI is for workers to learn how to interact with the technology effectively.  “As AI becomes a partner in intellectual endeavors, it will increasingly augment the effectiveness and creativity of our human intelligence.  Knowledge workers therefore will need to learn how to best prompt the machine with instructions to perform their work. Get started today, experimenting with generative AI tools to develop skills in ‘prompt engineering’, a prerequisite skill for creative workers in the decade to come.”

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