The advent of generative artificial intelligence (AI) has raised many questions about its use in business enterprises and the impact the technology may have on knowledge workers. According to McKinsey, “The biggest impact for knowledge workers that we can state with certainty is that generative AI is likely to significantly change their mix of work activities.”
Such a broad statement is unlikely to spark much disagreement; the open question is, “How?”
Generative AI will enhance knowledge worker productivity
The general consensus seems to be: By reducing the amount of time spent on rote tasks and increasing the amount of time available for thoughtful engagement. For example, an article in TechTarget notes, “Generative AI can be applied extensively across many areas of the business. It can make it easier to interpret and understand existing content… [by] summarizing complex information into a coherent narrative.”
And McKinsey itself states: “To capture the full benefits of generative AI to make knowledge work more productive… workers would need to see these tools not as job destroyers but as work enhancers.…Researchers could speed up projects by relying on automation tools to sort and synthesize large data sets.”
In a related podcast, a McKinsey consultant observed, “Every knowledge worker has the potential to use these technologies to increase their productivity. If I can have something write the first draft of a document for me or an email, that accelerates my personal productivity.
“What [generative AI does] is automate parts of people’s jobs. You could describe that as creating ‘superpowers’. Because if the machine does ‘X’ and saves me an hour, now I can use that hour more productively.”
A generative AI-enabled knowledge management system that helps improve business decision-making
We have seen that at Northern Light’s clients, who use generative AI capabilities in our knowledge management platform, SinglePoint™, to quickly identify key insights within documents responsive to a specific market and competitive intelligence research query. Generative AI-powered knowledge management is providing them a jump start on their research, so they know which documents to drill down into and what follow-up questions to ask to gain a deeper understanding of their topic of inquiry.
In another recent article, McKinsey writes that generative AI’s “ability to rapidly scan and process huge amounts of certain types of information and synthesize it” is not just a convenience, it can be a driver of an organization’s growth strategy. “Put more simply, [generative AI] can answer questions incredibly quickly. But the quality of the answers depends on both the quality of the question and access to the data that would inform an accurate answer.”
The role of source material in generative AI: Ensuring accuracy
This last caveat cannot be overstated, as reliable source material is a vital prerequisite for the effective and meaningful use of generative AI for knowledge management in the enterprise. Again, Northern Light sees this every day with our clients, each of whom possesses tens of millions of dollars of primary and licensed secondary market research content. This content is the foundation for their market and competitive intelligence research, and SinglePoint’s generative AI-based question-answering feature draws upon it exclusively, along with reliable business news sources and industry and government databases, as well as other scrupulously vetted content collections.
While generative AI as a technology is still in its infancy, it seems clear that innovative organizations that find the best use cases for it soonest will have an advantage over organizations that lag behind, and their workers will reap the benefits of having a tool at their disposal that stands to increase their productivity and job satisfaction.