Artificial Intelligence (AI) is often portrayed by Hollywood, either as friendly robots or evil super villains, however, it doesn’t seem like we are quite there yet. In the meantime, AI is rapidly transforming global businesses across industries and verticals.
But first, What is Artificial Intelligence or AI?
Minsky and McCarthy, who can be described as founding fathers of Artificial Intelligence define “AI”,” as any task performed by a program or a machine that, if a human carried out the same activity, we would say the human had to apply intelligence to accomplish the task”.
AI broadly comprises Machine Learning & Deep Learning.
In Machine Learning, a computer program is trained to recognize patterns such as identifying a human face or answers to particular questions. Training the system requires it to be exposed to as many variables for completing a task as possible, using different types of input data. These computer
programs build their own algorithms from the data they collect and use it to make correct “decisions”.
Deep learning is a subset of machine learning where artificial neural networks, algorithms inspired by the human brain, learn from large amounts of data. Similarly just like we learn from experience, the deep learning algorithm would perform a task repeatedly, each time tweaking it a little to improve the outcome. We refer to ‘deep learning’ because the neural networks have various (deep) layers that enable learning.
AI eventually leads to process automation and the reduction of error. AI thus enables enterprises to economize on operational costs and increase revenue.
In the 2019 CIO survey conducted by Gartner, 37% of organizations have implemented AI in some form. That’s a 270% increase over the last four years. (Source: Gartner).
For instance, Customer Support has benefited greatly through the use of AI Chatbots which nowadays offer personalized customer service round the clock with immense efficiency. The Marketing department has been able to harness the power of AI to generate and nurture leads.
The power of intuition and prediction makes AI a powerful ally that can be used by Learning and Development teams.
Let us take a brief look at how AI can improve Learning and Development.
Nowadays most LMS providers have vast learning libraries that comprise content across different types (video, text, pdf, slides, charts) and from a multitude of author.
One of the main functions of an L&D Administrator is to be a content curator. Content curation is a painstaking process of continually finding, filtering, and sharing the most relevant content to the right audience.
Fortunately, AI can curate relevant content after taking into account the unique skill level, timeline, course, and group that the individual belongs to. For example, Machine Learning can analyze factors such as how many shares the articles received, and more specifically the algorithms can look at how many participants of a network or a team shared the articles, review how many upvoted the article, or commented on the article. These algorithms can also look at the author of an article and the domain the article was published. In this way, algorithms can help determine if the content is more likely to be relevant and of interest to learners.
The L&D administrator can use AI to automate repetitive tasks in content filtering and aggregation and instead focus on more impactful activity.
A modern LMS that is personalized for an organisation not only builds the company’s brand identity but also gives the employees an effective learning experience according to their role, skill, and experience level. LMS customization will improve training outcomes and hence employee productivity.
A personalized LMS platform along with a user-friendly UI, that has an AI-powered recommendation engine, closely resembles platforms like Netflix and YouTube. User skills are mapped to job roles which are in turn linked to relevant content. The AI crawls and understands the required content thereby suggesting relevant learning paths, modules, courses and creates suitable assessments.
The more data the system processes, the more Deep Learning analyses and understands an individual learner’s needs, turning the LMS platform into a continuous improvement engine that grows alongside the learners.
The AI algorithm also personalizes the formats that each individual learner prefers (from YouTube videos to games) and curates the style of the course to mirror the learner’s past experience and completion level. These features coupled with gamification and social learning truly make for an immersive employee training experience.
AI-assisted programs like Chatbots are not passive sources of information but can be potentially active assistants.
The modern employee is mostly constrained for time and hence finds it hard to meet his or her training goals. These bots act like “digital coaches” and help employees stay on track with timely and personalized reminders.
For example, LMS platforms can use Chatbots, during onboarding, which can be used by new hires to ask questions about their team, their role within the team, and how that role is changing.
To ensure the onboarding process is smooth, these bots can reach out to new hires and take their individual feedback. If there are some challenges, then bots can also assist with suitable solutions to address the same.
For current employees, the AI bots can provide refreshers on different pieces of training including Safety, Compliance, Human Resources, and Operations. This ensures a high level of workforce engagement and satisfaction.
Furthermore, these LMS bots also serve as a single point for all learner needs. They can diagnose weaknesses in the learner’s understanding and help bridge any knowledge gaps in real-time.
In the past, personal assistants and career coaches were reserved only for senior management. But now with the exponential growth of AI, we could see these learning Chatbots being used across the organization to democratize the training process.
Analytics & Reporting
Erik Duval’s Weblog, 30 January 2012 defines learning analytics as follows, “Learning analytics is about collecting traces that learners leave behind and using those traces to improve learning.”
While most enterprise training programs have some element of knowledge acquisition, the specific program can vary quite widely. For example, a Company’s training program could be attempting to
● Increase the success rate of outbound sales calls
● Reduce the average time spent on customer support calls
● Maximize productivity in a manufacturing facility
To achieve the above training goals Big Data analytics using AI can maximize the returns of an L&D program.AI achieves incredible accuracy though deep neural networks which can assist with micro-level Reporting like Learners Activity Report (using data analysis), Problem Report (using diagnostic analysis), Progress Funnel report( using descriptive analysis), Cluster Report (using Cluster Analysis) showing low and high performers in a training program.
The biggest use of Descriptive Analysis in AI-powered LMS is to track Time and Engagement Metrics, for example, the average number of actions of the learners, the progression of users through the training, learner Retention Metrics, etc.
Additionally, AI-based data analysis can align LMS training to Employee assessments/appraisals and changing regulations.
Predictive Analytics is another way of using Learning data to create predictions about future learner progress, using techniques such as data mining, machine learning, and predictive modelling. It enables L&D Managers to study KPI’s such as content consumed, learner progress and course completion to optimize the budget and thereby maximize ROI.
Amazon uses machine learning to recommend products to you based on a user’s purchase history. Apple’s Siri and Microsoft’s Alexa use Artificial Intelligence heavily in natural language generation and Big Data processing. Similarly, AI is not just an add-on in a modern-day LMS. It is the primary engine for an enterprise’s learning strategy, while data acts like the fuel which drives it.
In summary, AI has numerous benefits for an LMS platform ranging from the way content is customized, consumed, assessed, and then analysed.