In 2019 Josh Bersin and Marc Zao Sanders ran a survey with Linkedin to find out more about the ‘flow of work’ surrounding knowledge workers, which include people whose jobs involve handling or using information. It turns out there are some common trends amongst them: There are 780 million knowledge workers globally and they spend 19 percent of their time gathering information and searching for data. That’s nearly a full day a week spent searching.
On the plus side, learning at work is undergoing a bit of a revolution, with many corporate learning and knowledge platforms and learning and development departments turning to AI-based ‘knowledge intelligence’ (KI) to get knowledge workers what they need, when they need it. It all starts with using AI to optimise search, and in this article, we’ll look at how KI can help companies save time and boost performance.
Making learning smarter
According to PwC’s key findings on talent research, 80 percent of CEOs say employees need new skills – digital skills in particular – to perform well in today’s business landscape.
Skills have their place, but arguably, it’s knowledge that’s missing. Knowledge workers may only need to upskill or participate in formal training once or twice a year, but they need knowledge daily to complete the tasks that contribute to company performance. However, when the workforce is spending nearly 20 percent of its time searching for the knowledge they need to do their jobs, there’s a big opportunity for improvement to be made.
Even when companies invest in sophisticated learning platforms and third-party content libraries like Udemy, search is often an issue because the results are long courses that take too long and contain more information than the user likely needs to complete a task.
This is where AI can help. Learning and knowledge platforms are beginning to use Google’s AI, Microsoft’s Cognitive Services and Natural Language Processing to build KI into their products.
There are three main ways that companies are tapping AI to help make learning smarter, and all are designed to help provide access to knowledge faster and more efficiently than ever before, giving workers knowledge at the point of need, or as Josh Bersin would say, ‘in the flow of work.’
Companies are now using AI to ‘tag’ knowledge in an extremely granular way. Part of the problem with many modern learning and platforms is that they only tag on a course level, so when users search, they get results that point to whole courses, rather than bite-sized pieces of knowledge that could be helpful as a task is being performed.
AI-driven Knowledge Intelligence builds metadata consisting of the title, description and tags authors give the content to construct all accessible intelligence. This goes beyond course titles. Each piece of knowledge contained within a video, or article can be tagged so that it can be easily found in a search.
Using AI, content can be scanned to build out a transcript, which can be analyzed by services such as Microsoft Cognitive Services (MCS.) MCS can then produce a contextually understood transcript that works in conjunction with tagging to identify people, places, dates and times.
Intelligence search to tap into knowledge at the point of need
There is a lot of room for improvement in search functionality across most enterprise learning systems, but today, enterprises are applying AI to create more consumer-grade search experiences using Natural Language Search.
Building on meta-tagging, intelligent search is helping to guide users to specific sections of videos or articles where they can get the exact knowledge and answers they need when they need them.
AI is also driving faceting, which enables users to augment traditional search techniques with a faceted navigation system, narrowing down search results via the application of multiple filters. This helps to pull out micro details in knowledge, such as specific categories or skills.
Getting more value out of third-party content spend
Chief Learning Officers have been known to have seven-figure budgets for third-party content libraries, but the problem with these libraries is that the search functionality is often poor. The end result is insufficient use of learning libraries, and little or no ROI.
AI and Knowledge Intelligence can be applied to these libraries too to enhance search functionality, running over the third-party content to unlock more value from it. For example, LinkedIn Learning has 8000 courses, which are made up of 300,0000 content assets and videos. Its own search can only return course-level results.
AI-driven search can fetch ‘micro assets’ – these are the content assets and videos – , allowing users to get what they need, rather than an entire course they have to sit through. It’s great news for ROI and music to the ears of any Chief Learning Officer.
This advanced search functionality for third-party libraries is also generating real efficiency gains. Workers no longer have to sit through full courses to get the answer they need. They can go directly to the specific part of the course and get the knowledge at the point of need, in the flow of work.
AI: Accelerating the enterprise
The ultimate benefit? In a business landscape where knowledge workers can spend up to a day a week just searching for knowledge, think about what businesses could do if they gave people back that day and gave them increased access to more knowledge. When people can search for the answers they need and get bite-sized learning at the point of need, they can apply instantly and see the benefit immediately.
Knowledge is the key to everything, and many companies are well on their way to using AI to extract as much value from knowledge as possible. Intelligent tagging and search are just the beginning, and predictive, AI-driven search is on the horizon for many companies. The ability to predict what knowledge workers are going to require, and what micro lessons will be most helpful based on their current activity or task is just around the corner. It’s just another example of how AI is helping businesses to become faster, and more efficient, and there is much more to come.
Steve Dineen, Founder & President, Fuse