Knowledge workers are somewhat beleaguered; they spend 30 percent of their working life looking for information.
Dave Schubmehl of IDC says that we can help and empower knowledge workers through the next generation of search, which uses artificial intelligence (AI) by speeding up and improving search. You can do this not just through efficient and powerful processing but by returning information to them – not just documents.
Schubmehl used a little history as background. In 1986, search didn’t exist as a commercial entity, he said. Companies such as Dialog and LexisNexis were just getting started. People used file cabinets and looked up memos by hand. But in the last 35 years, things have changed tremendously – and Schubmehl thinks that those 35 years are just the beginning of search.
I don’t tend to think of search as being in its infancy, but Schubmehl raises an interesting point — changes in search based on AI have already altered the way we shop, work, and treat illness. Yet everyone at this conference is looking for ways to continue improving search – and using new tools and approaches to do it.
Schubmehl went on to say that the amount of unstructured data is dropping because we see more and more video and audio – but at the end of the day the video and audio turns into text that we need to understand.
Other panelists at Activate may dispute this claim, but we can use AI for functions such as speech to text, image analytics, natural language processing, natural language generation, and computer visions.
All approaches to find and serve up information are important because not only is more than a third of a knowledge worker’s day is spent finding information, but “even with all the work we’ve done with search, workers can find information only about half the time,” Schubmehl said.
The usual suspects are at play – too much data in too many data stores and too many formats.
AI is helping to overcome those issues and is popping up in areas we don’t usually think of in the workplace. Conversational AI – also known as chatbots – can ask workers questions and return documents and information. To do that, they’ll need to continue to move from script-based processes to adaptive ones.
We’ll also see more work and process automation – so that the knowledge worker can do more and think more – and labor augmentation – so that computers can perform tasks that need to look over huge amounts of data — we’re starting to see it come into the enterprise.
Schubmehl’s research suggests that this will lead to more personalized information for knowledge workers. For example, AI will unify knowledge and information so that it makes sense to the user – instead of the user having to sift through data and documents for and distill it into insights.
And all of this has to happen fast. Because nobody has time to wait on the future.
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