Feathercap Blog

Employees have no time to learn new skills and search for the answers to do their jobs. AI to the rescue?

Jan 30, 2020 10:08:26 PM / by The Feathercap staff

no time


Over the past years in the learning industry and when discussing the future of work, we talked a lot about building “engaging” content and developing “bite” size" and micro learning because as we all knew, regardless of industry few of us had time to learn the skills we needed to do our jobs. Micro learning in the form of individual documents, SOPs (Standard Operating Procedures) or videos had become a favorite approach because making any job skills content more granular with an easier path to update was definitely an advantage. It’s been mentioned that the millennial generation was the main driver to this trend but all industries and employee age ranges are having this experience. The issue facing all employees face is they have in recent years had as little as 24 minutes a week or 1% of their typical workweek available to learn new skills or the skills they need.


Google was the answer for the internet, AI and cognitive analytics is the answer for the enterprise.


We all know Google; we type in a question, a word or a phrase and it typically gives us the answer, video or web site we are looking for in the first few results.  Additional household demographic data and personalization  has even further improved its success in delivering the most relevant results to us. It's not hard to imagine having these at work and instead of the internet as the data source have a connection to our corporate content silos such as documents and videos. Such work based AI driven appliances could deliver the right document or answer to performing a specific job skill based on any question asked. What has stopped us doing this in the enterprise is that Google and internet search search tools rely on the way web pages link to each other, known as "page rank. According to wikipedia "PageRank works by counting the number and quality of links to a page to determine a rough estimate of how important the website is. The underlying assumption is that more important websites are likely to receive more links from other websites." 

Until recently, we had no effective way to easily index and organize the content typically found in the enterprise; word documents, powerpoints, text, pdfs or videos. This was usually done manually or using existing enterprise content repository search based on keywords, titles or manually tags associated to the content. The results were usually horrible. Because we generally don't have links or data connections between our enterprise content approaches like page rank can't be used. But we’ve come a long way in the last few years. NLU or natural language understanding has evolved from taking many minutes to analyze a sentence to where we are today enabling millions of documents getting processed with the ability to index and develop relationships between every sentence and video segment in enterprise content processed in seconds. These AI approaches are not new, but they are now practical with the advent of low cost cloud computing. 

This is where cognitive analytics comes in; it starts with applying NLU as above to understand the meaning of all indexed text - down to the sentence and word level and then feeding those descriptions back into the curated content to further analyze the relationships with all other available content. Based on what an employee searches for, who they are in the company (similar to Google's household demographic data) and how an employee interacts with any found content to help gauge how valuable they found the search result. From there all content is actively curated, re-indexed and classified based in real time to improve future search results - becoming a self reinforcing feedback loop improving with each iteration. 

What does this mean for employees? Now the bottleneck can be removed between the existing “right” answer, document, course or email to keep employees moving by answering their question.  Instead of asking their colleague or searching through Sharepoint, Box or their company Gdrive, the right answer is instantly delivered. Imagine the time saved as employees do their jobs, especially while on their own for the first time after on boarding or anytime when a pressing question needs to be answered.

Products like what we offer at Feathercap along with others provides the means of enabling employees learning a new skill or trying to get an answer to their job question can come as easily as asking Google a question and getting the exact right web page or answer. 

See our primer on the employee answer platform for more on how this works. 

Feathercap is an AI driven answer platform that lets employees look up answers to their job related questions from all their existing learning content, documents and videos located anywhere. Feel free to contact us for more. 


Topics: Blog, NLP, AI curation, NLU

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