Matthew Brown's Analyst Perspectives

It has been a predominant buzzword for several years across all areas of human resources (HR), but artificial intelligence (AI) and learning and development (L&D) are finally beginning to integrate at scale, and it is one of the most transformative evolutions for the function of learning and development in the last 15 years. For a few years, we have been learning more about how AI will impact our daily personal lives, and more recently we have seen widespread evidence of how AI will impact our work lives. AI is not new by any means, but we find ourselves in the preliminary stages of exploring how it will affect business operations, especially in the scope of HR functions such as compensation, benefits, payroll, recruiting, onboarding, performance management and learning.  

The impact of AI on learning and development often results in hyper-personalized learning journeys. A personalized learning experience yields tremendous gains in knowledge transfer, employee confidence and competence. The advances of AI for learning and learning technology have afforded learning and development teams the ability to maximize the personalization of the experience for learners without requiring the same horsepower as necessitated without the use of AI.  

The inclusion of generative AI (GenAI)-based tools in learning platforms, such as chatbots, can foster productive open dialogue between employees and learning teams. As humans, we may be inclined to avoid confrontation or sharing constructive feedback with the learning professionals. In some instances, this behavior is reinforced by workplace environments that do not feel psychologically safe. In both virtual and in-person classroom-based learning experiences, learners are required to be more vulnerable at times, which can be challenging when there is a high fear of judgement. Having the option to interact with a conversational bot can expand the inclusivity factor tenfold, resulting in a willingness to engage and be forthcoming with questions, feedback, challenges, and other interactions that strengthen the learning impact. 

The use of GenAI tools can also support interactive knowledge assessments to check for understanding while allowing learners  to go deeper and explore additional insights on the topics. Learning teams can take advantage of GenAI tools to provide just-in-time content availability to the workforce at scale, allowing the information to be readily available to all employees on their terms. When employees can get what they need at the time they need it, it results in accelerated productivity, proficiency, and competency. 

We assert that by 2028, one-quarter of enterprises will require that learning is experienced through GenAI that can provide intelligent guidance on the skills that should be improved for a worker to be effective. The use of AI is advancing the maturation and scalability of the learning function by performing more of the heavy lift frequently incurred in activities that are often labor-intensive and overwhelming to tackle including: 

• Skills mapping. Organizations are progressing on the path to a skills-centric talent strategy; however, the most common barrier is creating a comprehensive skills ontology that is informed by organizational needs, job descriptions, competency models and talent proficiency. AI has made this a much easier lift, permitting teams to shift their effort from collection and creation to review and approval, dramatically reducing the amount of time involved.  
• Designing learning simulations. Simulations are an effective tool for facilitating maximum comprehension and application on complex learning topics. AI enables teams to provide more simulation-based experiences to the learning population. Not all learners will engage with simulations, but the ones who need this experience most are usually not speaking up and/or do not have access. The barrier has often been resource availability for the design and creation of simulations. Traditional methods involve a learning and development professional collecting input from subject matter experts, synthesizing the inputs to align with learning program objectives and language, and soliciting feedback and review from the business before moving into production. The simulations can often go stale, as the appetite and availability for ongoing maintenance can be a nuisance. AI affords learning teams assistance in simulation development, dramatically reducing the amount of time involved to deliver a simulation experience. 
• Real-time coaching support. There will always be a need for a live human to participate in coaching experiences; however, it is impossible for an organization to support all employees with coaching needs at scale. The incorporation of AI provides for conversational exchanges with an expertise-focused chatbot and closes the gap, enabling all employees access to just-in-time coaching support. 
• Elevated and comprehensive learning analytics. The use of GenAI facilitates continuous learning progress and the integration of performance data into overall learning analytics, resulting in a near-real-time view of activity and potential actions needed. The expansion of data collected through AI algorithms enables organizations to gain deep and meaningful insights into the learning behaviors and patterns within the organization. This enhances the ability for learning and development teams to respond in near-real-time to the changing needs of learners. Leveraging AI to support the collection and analysis of extensive datasets tied to learning interactions can enable teams to optimize the learning function, leading to a deeper integration within the business strategies. 

 The use of AI in learning and development has proven to yield higher productivity in the design and implementation of learning activities and maintain pace with the speed of change affecting businesses. Its impact is significant across many learning processes and activities, including:  

• Content creation. AI has dramatically accelerated the training design and development processes. Ideating or brainstorming a new learning program, outlining learning objectives, developing course frameworks and even the design aesthetics relative to images, videos, branding, themes, and learner interactions are some of the tactical ways AI has impacted the design and development process. 
• Testing for knowledge transfer and application. I have found this to be one of the best gateways into adoption of GenAI in the L&D function. Often, testing for knowledge is an arbitrary function of the learning process in which organizations have become relaxed or complacent with “checking the box”. It takes an inordinate amount of time to develop an extensive question pool for every program or learning activity, so L&D may settle for the “good enough” approach. This can result in false confidence in our training impact and efficacy. Recycling the same questions through three attempts and changing up the order of questions and answers is not a viable strategy to yield ideal levels of knowledge transfer and application. Consider the benefits of using GenAI to assess your training outline along with key learning objectives, leveraging the technology to generate mass question pools designed to measure what really matters.  
• Translations. For many years, translation was one of the more challenging aspects of learning and development. Depending on internal employees or external translation agencies to deliver all the translations for learning content and programs has always been expensive and time-consuming. Enter the use of GenAI to assist with this function and enable teams to provide more inclusive training content to meet the workforce's needs. As with all GenAI output, it is still necessary for human review to ensure accuracy and appropriateness of content. 

Additional benefits for L&D with the usage of AI can be found at the intersection of employee well-being and training. Employees expect to be seen and heard, and to feel valued by their employers. One way to support this is by connecting workers to learning opportunities and content in service of physical, mental, and emotional health and well-being. The nature and timing of employee needs and workplace challenges are often unpredictable; they do not adhere to strict working hours and can go unreported and unsupported. Enabling real-time access for employees to the content they seek can help them cope with burnout and stress. By 2027, digital learning software providers will need to embed AI and provide GenAI capabilities to support required employee experiences. 

 The transformative power of AI in the learning sector is undeniable and stands as a critical partner for both employees and learning and development teams. Its prowess in customizing learning experiences and boosting efficiency is nothing short of remarkable. HR and learning leaders, it’s time to take action and lead the charge in embracing learning technologies. Recognize the groundbreaking progress enabled by AI and seize the abundant opportunities for development and exploration in the learning domain. The journey of AI in learning is accelerating, heralding an era brimming with possibilities and progress. Don’t just watch the future unfold — be a part of shaping it. Invest in AI-driven learning solutions today, and propel your organization towards a smarter, more capable tomorrow. 

Regards,

Matthew Brown