It’s official: AI has become mainstream. A recent report, IBM’s 2021 Global AI Adoption Index, confirms this. Based on a survey of 5,501 businesses globally, the report shows that one-third of companies are currently using AI in some way, while 43% are exploring it.
While everyone’s familiar with popular uses of AI – including AI-driven recommendation engines, maps, and ride-hailing apps, we’re often less familiar with the applied use of enterprise AI. Most people realize that banks and the military are using it, but did you know that AI is driving enterprise learning in a big way?
We’re talking about the learning platforms implemented by your HR team, or your Chief Learning Officer, or your Head of Learning and Development. These platforms may feature courses, or, in the case of a platform like the Fuse learning and knowledge platform, they may provide access to both courses and bite-sized knowledge to help you learn in the flow of work. What many of them have in common is an increasing use of AI and machine learning functions.
In L&D, AI is driving translation and transcription engines, hyper-personalized micro and macro learning recommendations, and unrivalled search.
If all this is new to you, it may be helpful to increase your understanding of AI in enterprise learning by dividing it up categorically into ‘buckets.’ Read on to hear more about the L&D bucket list for enterprise learning.
The Three AI Buckets
In Fuse, we break down our AI intelligence into three ‘buckets:’ knowledge intelligence, search intelligence and language intelligence.
The knowledge intelligence bucket encapsulates all the AI-driven activities designed to help a platform better understand the context of content so that they can begin to create what we like to call a ‘corporate brain.’ A corporate brain is different for each company: it consists of all the knowledge required to help your workforce do its job better. It may be made up of both formal courses, and more informal training such as videos and short articles.
AI is about making the knowledge contained within the corporate brain more accessible than ever before. AI can capture content’s metadata, which is the title, description and tags the authors give the content. It can then scan the content and build out a transcript which it can process contextually by looking at the intelligent tagging applied: tags can identify people, places, dates, and times.
What’s the point?
Well, it means that when you have a job-related question as you are working on a task, you can do any sort of very granular search you want, and come back with really relevant results rather than generic material that may not answer the question.
AI classifies knowledge in a way that allows workers to get really specific answers to their questions. You could ask the system to show you all content contributed by a specific user, or all content created during a certain time period. You could ask a question about one step of a process, and get the specific answer rather than having to watch all of a video that explains every step. As knowledge intelligence builds up over time, individuals can effectively build their own knowledge bases that can be referenced time and time again.
AI-Driven Search Gets Savvy
We’ve become so accustomed to Google and Amazon-grade AI-driven search in our consumer lives, that it’s easy to forget that AI hasn’t filtered down to many enterprise applications – until now of course. This is where the second bucket, search intelligence, comes in.
Today, AI-powered search means that learning platforms are ‘understanding’ our queries better than ever before.
AI can begin to learn our intent behind search, and use this search intelligence to create hyper-relevant search results and personalized feeds of knowledge. Again, AI is helping companies to move on from very generic searches and content, to very niche searches and search results that can help workers right at that very crucial moment of need.
It’s happening with technologies like Natural Language Processing (NLP) which can break down a query into intricate blocks to understand it more closely and more contextually. And with the knowledge intelligence generated by these platforms, AI can extract granular answers directly from content transcripts, searching these transcripts and breaking the query down into sort, content type, topic and author. NLP then works to dynamically filter searches to produce intelligent results that are highly accurate and relevant to a specific user.
It makes the generic ‘list’ search results based on keywords in learning platforms a thing of the past.
The Third Bucket: Language Intelligence
English may be the most popular language on the Internet (25% of all websites are written in English) but there is a whole world of other languages out there that represent the other 75% of searches.
Search needs to work equally regardless of what language you speak. In order to remove language as a barrier to accessing knowledge, we are getting creative with easy-to-use translation services that enable the transcripts generated during knowledge intelligence to be available across 49 languages. This means that when the user searches for content in their native language, we can access the translated transcript to find what is needed.
It’s also important to note that great knowledge isn’t just contained within content. Socially-focused platforms, such as Fuse, can also allow clients to enable conversations to take place in multiple languages. The user experiences the conversation in their native language, despite other comments being in different languages.
With AI doing the heavy-lifting, you can unlock access to global expertise and break down the language barrier.
The Ultimate Benefit of AI for Learning
If you ask most businesses why they use AI, they’ll tell you that it’s to increase productivity and to introduce new efficiencies that will ultimately help better the bottom line.
AI for learning is no exception. In making knowledge more personalized and searching better and faster, workers can find new answers faster, and improve their performance. For L&D, AI is a new opportunity to drive enterprise-wide revenue and profitability, and our AI bucket list is just the beginning.
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