Executive Summary: Companies worldwide face multiple challenges, including complexity in products and processes, growth in competition, changes in workforce, and immense pressure to be agile. Leaders recognize that having a skilled workforce is a force multiplier. However, traditional training approaches don’t seem effective anymore. Leaders are scrambling for simple, yet powerful solutions to train their workforce. Fortunately, innovations in Artificial Intelligence (AI) might offer the magic toolbox to help them succeed. This blog on AI in training focuses on identifying the challenges faced in training. It then outlines how AI in training can enhance the experience for learners, trainers, and leaders.
Last week, the RapL team met with Ashley, who is the General Manager for training at a large insurance company. As the GM of a 4500-person company, she was concerned about the changing demographics of her customers and employees. She recognized that more millennials are coming into the workforce, and face challenges to sell and support the wide range of products her company offers. She not only has to hire people, but also fully prepare them in the shortest time possible. However, traditional approaches can require anywhere from 4-6 months to train and onboard new employees. So, Ashley realized it might be time to consider new approaches — such as using AI in training.
This week, we spoke to Raja, the Chief Operating Officer at a large retailer. Their outlets stock and sell thousands of products. Not just that, the assortment changes every month. More than 8,000 employees show up daily at one of their 1000+ outlets nationwide. Majority of these employees are high school graduates or pursuing their undergraduate education. They are not experts in the products that the retailer sells. Nor are they well versed in handling the customer base well. The new employees are increasingly mobile-savvy, playful, and short on attention. Raja heard of smarts from using AI in training and was intrigued.
In our further conversations, we see this pattern repeatedly. Raja and Ashley are just two of many corporate leaders who need to train their workforce rapidly. They could send hundreds of trainers to train their employees. However, with the employee churn rate above 50%, these trainers may face serious challenges to scale and be effective. Perhaps something like the neural chip from SpaceX founder Elon Musk might help. Seems very sci-fi and cool! But, definitely, it is NOT a solution now. Neither is it likely to be economical and socially acceptable. Not surprisingly, we need to look at simpler and more economical alternatives, like the use of AI in training.
Existing situation and problems
Challenges without AI in training
Let us take a quick look at the challenges companies face when it comes to training their employees. Whether it’s in retail, customer service, manufacturing, or any other industry, there are many evolving factors to consider. The factors span the spectrum of new products, processes, shifting customer expectations, environment, and more. These challenges broadly fit into the following categories:
- Challenges for Learners: Learners nowadays are distributed and mobile. They have access to new technologies and may not want to use old-style applications. Learners cannot be expected to prioritize their time to handle large volumes of training material, as they have limited time. Cramming knowledge in 1 or 2 weeks of onboarding is inadequate. Such cramming also leads to forgetfulness and retaining issues, as detailed by the Forgetting Curve (see Microlearning and Spaced Repetition). Each individual learner is likely to learn at their own pace, which can lead to differences in their understanding.
- Challenges for Trainers: Trainers have multitudes of people to train. They have limited time to understand and present the training material. Trainers often do not have the time or knowledge to work on creating modern multimedia experiences for their training content. Trainers may not have face-to-face contact, which limits their understanding of learners’ needs. Trainers also do not always get sufficient data to help them prepare and deliver better quality training. Or worse yet, trainers may sometimes get a large volume of data that drowns them. They may not have ready access to adequate analysis and insights from such large amounts of data.
- Challenges for Leaders: Leaders and even first-level managers may have many people working in their team. They do not have enough time to focus on each individual in their team. Hence, they may not have an adequate and timely understanding of the skill levels in the teams. The constant pressure to ship new products and grow business also challenges these leaders to quickly hire and train their workforce. Combined, all these issues can often lead to poor business results, adding more burden to the leaders.
Existing training systems
Ashley and Raja have decades of experience. These leaders instinctively hired and employed Learning and Development (L&D) professionals to create and run training programs. L&D professionals do their personal best to create scores of documents and perhaps a dozen or so assessment tests. They use a traditional Learning Management System (LMS) to load and distribute the content.
Employees get multiple reminders to complete their annual or even quarterly training. Sometimes employees receive 100s of pages of such documents as part of onboarding or annual training programs. Employees rarely engage well and definitely do not benefit much from such mass training programs. There may be a flurry of messages, emails, repetitive warnings, but little happens to move the training forward. Employees lag in training; leaders are challenged further; L&D professionals are under further pressure. Trainers are caught in the middle with poor resources and outcomes. Such traditional use of LMS is not sustainable and valuable. They may have been successful in the last millennia, but are best avoided in the new century. We are already in the 23rd year of new millennia!
Let us understand the emerging new technologies in this millennia. Billions of people worldwide have adopted mobile phones. Many of these phones are smartphones that run rich applications displaying high quality images and text, and play audio and video. Applications easily and securely connect to external systems, and can offer a personalized experience. In the last decade, engineers and entrepreneurs have found ways to build additional value through software running in the cloud systems.
Recently, there have been significant advancements in Artificial Intelligence (AI). Some advancements are:
- Data and Analysis: Collecting, organizing, and analyzing data offers a quick way to solve data issues. AI in training uses modern data and analysis, which will provide real-time feedback and enable richer experiences.
- Presentation: Taking complex concepts and expressing them in simple presentations eases understanding for many users. AI in training solutions includes analyzing complex presentations to identify independent concepts and generate concept specific short presentations or media documents.
- Natural Language Processing (NLP): Computing advancements have enhanced text processing to significantly understand the words, sentences, and intent. AI in training software can benefit from text processing to split, summarize, annotate, and enhance the presentation of information.
- Generative Pre-Trained Transformer (GPT): GPT is a collection of technologies that build on NLP and generate human friendly text outputs from text documents used for training. Novel use of GPT generates images, writes sentences and paragraphs, and even can provide a dialog oriented experience. ChatGPT zoomed in usage, reaching millions of users within days of the launch. High school students used ChatGPT to learn and prepare their school essays.
- Speech: Advancements in AI technology have brought improved algorithms to recognize speech. This allows users to provide voice inputs easily. Modern phones allow recording and transcribing speech into text for further processing, which directly enables AI in training.
- Question and Answers (QnA): For millennia, humans relied on question and answer dialog models to deepen and enhance understanding. QnA systems have grown to provide faster and better ways to generate questions and possible answers. Users can learn from quizzes, tests, and chat experiences powered through QnA systems.
- Recommendations: Consumer experiences, like Netflix movie selections and Amazon shopping finds, use AI for recommendations. Similar AI algorithms can be used to recommend and prioritize areas of training.
- and many more…
Each technology has its own specific value. Together, these are massively valuable! Let us look at how AI in training is applicable for companies.
Using AI in training
Time is a limited resource. Leaders, trainers, and learners are all short on time. They need better solutions. They will benefit from simplified technology solutions. Use of AI in training can bring simplicity, elegance, structure, and power to these stakeholders.
" Any sufficiently advanced technology is indistinguishable from magic."
- Arthur C. Clarke, Science Fiction Author
AI in training for learners
As discussed above, learners are overwhelmed and need simple experiences. Here are a few ways Artificial Intelligence (AI) can help learners.
- Visual Experiences: “A picture is worth a thousand words!” Users prefer simple images and illustrations to ease their training. They do not want black text on white paper ;-). Tools like Sketch, Blender, Canva, HTML5, Adobe, etc. are often used. Creating visual and aesthetically pleasing experiences requires considerable design and implementation efforts. New AI tools like Dall-E, Lensa.ai, etc. are game changers in helping designers create visuals quickly.
- Personalized Learning: AI can act as a coach. It analyzes the user’s needs, skill gaps, content packages, and comes up with a prioritized and organized plan. This may also include customized content and by-the-side coaching inputs for the learners. Since AI driven systems can adapt to the learner’s pace, it helps them immensely.
- Chatbots: Using a question and answer model, the AI driven training experience can help simplify the daunting training tasks. At any time and place, the user can ask questions and get answers. Users can do repeat inquiries to deepen their knowledge.
- Gamification: Learners love challenges and games. They love to earn something even in a virtual sense. AI systems can help craft appropriate points and gaming constructs to encourage learners to engage and learn more. AI in training can also be used to recommend timely use of gamification points and rewards.
These are just the tip of the iceberg. There are several more detailed ways that AI can help, including adoption of virtual reality and augmented reality (VR/AR), gaming, voice control, etc. Using AI, RapL provides personalized, gamified, adaptive, and reinforced learning. Rich visual experiences invite and engage the users easily. We have seen this work well with the millions of scenarios delivered, and mastered by RapL users.
AI in training for trainers
Trainers need to adapt rapidly and scale to handle a wide range of content and growing number of learners. Churn in organizations also adds more burden to tune the content for newcomers. Here are some ways Artificial Intelligence (AI) can help trainers.
- Program and Learning Paths: Through AI driven data analysis, trainers can build learning paths composed of a sequence of microlearning topics. Generating and selecting appealing names for programs and topics also engages users. Audio and visual elements with composition of documents, quizzes, surveys, and tests also create a well-rounded program authoring experience.
- Assessment and Grading: With an increased number of trainees, trainers need a faster and easier way to assess and grade tests or assignments. AI can automate the grading and assessment of assignments, quizzes, and tests. This can save time and improve consistency with explanations.
- Intelligent Analytics: Trainers need to operate with data and insights. Too much data, and they drown in unwanted details. AI can analyze data from training systems, discover patterns, and surface actionable insights. Trainers can quickly spot difficulties and skill gaps to address them rapidly.
- Enhanced Content Quality: Providing good quality content is essential to boost learner engagement and excitement. AI driven tools can quickly spot language issues or visual inconsistencies, allowing content authors to address issues. Automated analysis and generation can further enhance the quality of the content generated.
We are just scratching the surface of what is possible. RapL has consistently used AI to simplify the life of trainers and content authors. Use of AI has improved the quality and speed for 1000s of authored training materials. Trainers have found extra time to focus on their main mission to help their learners and organization achieve better outcomes.
AI in training for leaders
We already observed that leaders have insufficient data, insights, and time. Having run teams and businesses for a long time, most leaders appreciate the value of trying to boost outcomes. The leaders also rely on their trainers and team leaders to ensure that employees are well trained. Artificial Intelligence (AI) can help them in the following ways.
- Simplicity and Scale: AI can simplify the way training content is generated, how training is run, and how to get data from training programs. Leaders can record audio or video casts and work with their trainers to mix it up with other regular content. This can be easily distributed to all their employees.
- Deep Insights: Data from various training modules are easily analyzed and prioritized by AI systems. Unlike traditional systems, AI sharpens the insight and makes it precise and actionable. For example, 43 users out of 1732 have not completed customer service etiquette training, because they are stuck on question 8.
- Smart Targeting: AI can also enable precision targeting of training topics, nudges, and appreciation to relevant learners. Leaders can instantly contact the individual, manager, or appropriate trainer to ensure that any skill gaps are addressed. For example, 21 users who are behind on question 8 belong to store A573, where there is a high manager churn.
- Better Outcomes: Leaders can use AI to bring together training and business outcomes data to better understand the situation. Using such analysis, leaders can employ AI driven training to impart the right training, leading to better outcomes.
Often leaders engage quickly with smart, simple, and data driven systems. AI in training enhances the generation, capture, use, and analysis of data. RapL has seen this in action, with 1000s of leaders and managers using RapL. They feel empowered and equipped with data and the ease of tools to change the course and impart training that generates outcomes quickly.
In conclusion: Apply AI in training
Companies across the world face triple challenges: a) changing demographics of employees and customers, b) growing complexity in products, processes, and competition, and c) significant need to be agile. Recent innovations in Artificial Intelligence (AI) offer promise for better ways to create training programs, engage employees, and derive insights to guide the programs further. In this blog, we reviewed the challenges first. We learned how traditional approaches do not function well for the new challenges. We then looked at how AI in training provides immense value for learners, trainers, and leaders.
Some AI in training solutions are already in place within the RapL platform. 1000s of experienced corporate leaders, managers, and training professionals have used RapL to solve their training problems.
At RapL, we are committed to creating training experiences that lead to better outcomes. Our deployments combine modern AI in training approaches with personalized content and experiences. Log on to getrapl.com to learn more about successful use of AI in training.
Mr. Murali Krishnan
CPO of RapL Inc
Murali Krishnan is the co-founder and Chief Product Officer (CPO) of RapL Inc. Murali is passionate about using technology to accelerate human skills development at scale. In the past two decades, he has led global software teams at Microsoft Corp., Starbucks Coffee Company, and start-ups across the consumer and enterprise sectors.
As VP of the Starbucks Digital Platform, Murali enabled millions of mobile orders and over $10 billion in payments from customers of the world’s largest coffeehouse chain. At Microsoft, Murali was a Director, leading the development of e-commerce platforms, app stores, subscriptions, payments, big data, AI, and anti-fraud systems.
Murali holds an MS in Computer Science from the University of Wisconsin, USA. He has a BE in Computer Science & Engineering from College of Engineering, Chennai, India. He is passionate about running marathons and is currently preparing for a Grand Canyon hike.