Instructor-led training (ILT) has long been a cornerstone of effective learning experiences, but in today’s digital age, the integration of technology can take ILT to new heights.
One such technology is generative artificial intelligence (AI), which has the potential to transform ILT by creating engaging and interactive learning experiences.
In this article, we’ll explore the top ways to enhance instructor-led training using generative AI.
From content creation to learner engagement and assessment, we will uncover practical strategies and actionable steps that ILT providers and trainers can implement now to elevate their training programs.
Using Generative Artificial Intelligence in Instructor-Led Training
Generative AI is software that can produce everything from walls of text to compiled images. Powered by natural language processing (NLP), it’s a machine learning model that’s capable of creating just about anything for your training program.
AI is a key tool that most training and development specialists in charge of ILT operations should consider incorporating into their training programs.
Gen AI in this context acts as a digital training partner that can help continually innovate and evolve training materials for instructors and subject matter experts (SMEs).
When properly utilized, it allows an expert back-office training team to create better learning experiences without putting more effort than what’s needed, providing massive benefits in measuring the success of learning retention and success.
What is Instructor-Led Training (ILT)?
Instructor-led training (ILT) is guided learning delivery provided to learners in a classroom or facility by a qualified instructor or trainer.
Consider ILT to be the most common learning delivery method available to learners as it is most similar to traditional classroom learning in an academic sense.
ILT can take many forms including:
- Seminars: in-person learning events held in large auditoriums catering to an pre-planned audience at once.
- Workshops: hands-on learning sessions, usually to learn a new skill or craft.
- Apprenticeships & On the Job Training: learners develop new skills while on the job using the learning by doing model.
- Upskilling & reskilling: professionals learn new skills by facilitators on new developments in their field and refine current ones.
When the learners and instructor(s) don’t meet in real-time and in-person but instead through online scheduled training, it is considered virtual instructor-led training (vILT).
Real-time instructor-led training is the gold standard for providing any type of training and development for learners as it allows for direct interaction between the instructor and learners and provides instant guidance and discussion to clarify training topics, on top of involving the learners in every phase of the training course.
Because of these advantages, instructor-led training and its virtual counterpart make it a critical part of any training program’s success.
Dive Deeper: Your Complete Guide to Instructor-Led Training for Skills Development
How can AI Improve Instructor-Led Training?
Generative AI is advantageous for ILT operations because it can assist L&D teams in quickly generating learning material and other educational assets.
In addition, it can significantly improve how training and development specialists plan and execute training courses and enhance the quality of training for ILT.
Below are some of the advantages AI has in improving ILT-based learning programs.
Dynamic and Interactive Content Creation
Generative AI can enhance instructor-led training experience by creating content that captivates and engages learners in the instructional material. How can it be utilized?
Automated Content Generation
Creating learning content is consistently seen as a challenge for training specialists focused on ILT due to the volume and specificity of what’s needed for the learner.
In addition, training teams must also focus on how it should be delivered.
Through text and video?
Or perhaps in a lesson plan utilized by the subject-matter expert?
The benefit:
With generative AI, the creative roadblocks and production timelines from concept to consumption are reduced dramatically so that the back-office and SMEs can focus on the execution of instruction.
Interactive Training Content
Interactive video for training has always had its benefits in learning but, with Gen AI, its utility increases. Before, training teams had to resort to using virtual reality (VR) or simulation models to help bring an interactive, hands-on training experience to the learners.
With AI-generated training content, learners can engage with video content produced with or without the guidance of an instructor to get a visual idea of concepts being taught on.
The benefit:
Interactive training scenarios using Gen AI can simulate real-life situations and encourage learners to apply their knowledge practically and in some cases, more safely compared to a live training scenario. In addition to providing simulated on-the-job training, it can provide learners with a deeper understanding of what their roles will entail, currently or in the future, and how they can adapt their critical thinking skills.
Gamification Elements
Turning learning into a game has long been a staple of the blended learning strategy.
With AI, the production of engaging and thoughtful learning games and puzzles increases interest due to the incentivizing of competition with leaderboards and rewards and teamwork-based initiatives.
What’s even better is that with a game element, training specialists can gather more data than they were previously able to use other learning methods.
The benefit:
Generative AI helps create smart recommendations for how a particular learning plan should be created into a game and what the best methods to use in parallel with the instructor’s guidance.
Personalization for Learner Preferences and Objectives
Using data collected from past training programs, Generative AI allows team members to personalize ILT to the benefit of both the instructor’s teaching methodologies and the learner’s preferences and objectives. Consider the following when opting for a Gen AI personalized training plan:
Learner-Centered Approach
The learner-centered approach has long been touted by instructors for helping guide the plasticity of the training material.
According to Harvard Business School, using the learner-centered approach allows instructors in all environments the greatest capacity for skill-building.
With more focus on the learner’s past experiences to act as a compass in guiding them through the training they’re in.
When ILT is focused first and foremost with the learner as the main focal point, instructors and training team members will focus on providing a positive and reinforcing learning experience.
How can the learner-centered approach be utilized?
When using Gen AI, learner data is gathered from previous programs and even the learner’s answers on a survey to understand preferences, strengths, and weaknesses, allowing trainers to provide individualized support and tailored instruction during ILT sessions.
Adaptive Learning Paths
Learners like technology, are adaptable. The benefits of adaptive learning are something not easily ignored by L&D teams. When properly managed with the learner in mind, adaptive learning produces better outcomes. Utilizing generative AI algorithms to analyze learner data, can customize content delivery, pace, and difficulty levels that cater to each learner’s needs as they progress throughout the course.
Intelligent Recommendations
Leverage generative AI to provide intelligent recommendations for additional resources, exercises, or supplementary materials based on learners’ interests and progress, offering a tailored learning experience.
AI can be utilized to look into the learner’s preferred learning style or perhaps modify the delivery of the training material based on performance factors.
Training Case Studies and Work Simulations
Developing work case scenarios and case studies can be limiting especially if the L&D team doesn’t have much information to provide for instructors. With Gen AI, training specialists can give new and modified workplace scenarios that may be encountered post-training. Consider using AI for the following:
Situation Development
Gen AI can be used to modify a challenge or real workplace scenario that they may face.
Gen AI can go beyond standard textbook situational training examples and provide new variables that may have not been used before, incentivizing learners to apply their knowledge and practice concepts taught by the course.
Customized Case Studies
There are only so many case studies to be used in a particular industry to draw upon for training purposes.
With Gen AI, role and industry-specific case studies can be developed that are tailored to the department or company in training and even the current role of the learner.
Enhanced case studies, although fabricated, can engage learners to apply their newly learned skills to the test before using them in the actual real world.
Continuous Improvement for Instructor-Led Training Operations
After the coursework has been completed and learners have passed or received certification, training doesn’t end yet for the instructors or the training and development team. AI doesn’t stop at producing learner-centered content or content to be used by instructors.
Generative AI can integrate itself as a important tool within training operations helping perfect back-office processes associated with learning administration. In fact, many chief learning analysts including Josh Bersin, project that AI-powered training operations and management will be in the norm in 2026 and beyond as more learning software suites utilize AI with the most complex items tasks possible.
Continuous improvements using generative AI ask training teams to look at the following areas for their cohort of learners:
Training Program Components
Instructor-led training-based programs should have methodically placed modules and courses to ensure that learners are comfortable with the pace and timeline of the training.
Depending on the type of training program being implemented for an organization, components will vary.
For example, some instructors will provide extensive blocks of in-person and virtual instruction for compliance training but offer no recap assignments for the same course.
With GenAI, learning specialists can look at learner objectives and data and see where they can fill in the gaps within the program to ensure all learning objectives are met with full understanding within the training course time frame.
Thoughtful Program Design
Training specialists need to look at their learner data and instructor evaluations and determine where areas of improvement can be brought into the course.
GenAI can compile the data and provide a robust overview of specific metrics that instructors and specialists can look over to ensure learner objectives are being met at the expense of no one.
Making Data Useful for L&D Teams
Between dozens of training programs and hundreds of different training sessions scheduled throughout the year, learning professionals can deal with terabytes of data. So much data that’s there’s a 100% chance even the best chief learning officers won’t know what to do with it.
With AI, learning teams will be able to optimize their learning analytics capabilities to develop new strategies, make informed decisions, and optimize resources properly without the need of an in-house statistician.
The result can mean millions of dollars saved by avoiding training budget mistakes, reduced administrative hours, and more streamlined processes for training managers.
AI is Only a Piece to Optimizing Your ILT Management
The integration of generative AI into instructor-led training represents a paradigm shift in education and corporate learning. When learning and development specialists use generative AI as an additional tool for creating engaging and robust learning experiences, they’re drawing from mountains of quality data to empower their instructors and subject-matter experts with the content they need.
The future of training is exciting with AI in the training tool belt of L&D teams. By reducing the amount of time needed for planning and providing ILT-based training experiences, we will expect training team members to roll out more course sessions and training programs of all types.
The same goes for training companies as well.
With the volume of training set to increase for both internal and outsourced training providers, we also expect the managing of such large training programs to increase as well.
Expansion calls for improved efficiency.
How can L&D teams better manage hundreds of courses without the headache? Implementing a training management system into your learning tech stack can drastically improve how your training team delivers ILT learning experiences.
What happens when you combine the power of AI, the compatibility of an LMS, and the scheduling efficiency of the best training management software available
