Training professionals and solutions providers alike agree that the growing integration of technologies such as artificial intelligence (AI), augmented reality (AR), virtual reality (VR), and extended reality (XR) in various aspects of learning and development (L&D) is making training more personalized, immersive, and data driven, according to findings from Training’s 2025 Training Industry Report survey (the full survey results will be published in the November 2025 issue).
We’re not fully there yet, but we are making progress. The survey results show that while usage of these technologies in L&D is still fairly low, L&D professionals expect to kick it up in the coming year. Some 8 percent of the 200-plus respondents use VR in training and 4 percent use AR, with less than 1 percent of programs delivered via either technology. But 10 percent intend to buy AR/VR technology and another 10 percent indicated they will increase their use of the technologies to deliver training in the next year. And nearly half (48 percent) intend to purchase games and simulations, which often incorporate AR or VR.
Some 37 percent of respondents currently use AI for training purposes—representing 1.5 percent of programs delivered. But a whopping 40 percent believe their company will increase the percentage of training hours delivered via AI in the next year.
And more than half (56 percent) of training solutions providers said their customers’ interest in implementing emerging technologies has increased.
“The future of learning is being shaped by a convergence of intelligent technologies and human-centered design,” believes Apratim Purakayastha, GM, Talent Development Solutions, Skillsoft (see sidebar on p. 26). “We’re entering an era where training programs are no longer static or one-sizefits- all. They’re evolving to be predictive rather than reactive, anticipating learner needs and delivering just-in-time experiences that are both personalized and context-aware.”
TECH TRENDS
When asked what tech trends will continue to strengthen in the next 12 months, both L&D professionals and training solution providers aligned on six key evolutions:
1. AI-powered personalized learning: Adaptive learning platforms use AI to create, tailor, and deliver content based on individual progress, preferences, job roles, and skill gaps. Chatbots and AI tutors provide real-time assistance and microlearning, while predictive analytics recommend courses before skill gaps become critical.
2. Immersive learning (VR/AR/XR): VR simulations are used for high-risk and safety training in fields such as healthcare and manufacturing. AR provides on-the-job support with interactive manuals and just-in-time training. Metaverse-enabled classrooms offer collaborative global learning experiences.
3. Micro-credentials and skills-based learning: Short, stackable certifications such as digital badges and nano-degrees are replacing some traditional degrees. Employer-led academies such as Google Certificates and AWS (Amazon Web Services) training are growing in importance. Skills mapping tools align learning and development with real-time business needs.
4. Learning in the flow of work: Integration with productivity tools such as Slack and Microsoft Teams enables bite-sized learning in the flow of work. AI-curated playlists provide just-in-time learning, such as “5-minute leadership tips before a meeting.”
5. Data-driven learning and development: AIpowered L&D dashboards track engagement, skill progression, and return on investment. Employee sentiment analysis predicts burnout and recommends learning interventions.
6. Using tech to train on soft skills: AI-driven coaching enhances leadership, emotional intelligence, communication, and resilience skills. VR-based empathy training simulates difficult customer interactions; VR also can be used for practicing negotiations or diversity, equity, and inclusion (DEI) scenarios in virtual environments.
TECHNOLOGY IN ACTION
Many of our 2025 Training MVP Awards winners are effectively utilizing training technologies, from AI and AR to game-based simulations. Here’s a look at a few of their programs in action:
• Impact Networking: As part of its Apprentice Program for the Service Delivery Team, Impact Networking used a merged reality platform to train new service technicians to service hardware in the field. The augmented reality software served as a just-in-time learning tool technicians used to receive support and technical guidance from more senior or advanced technicians.
Via a mobile device, a localized technician in the field could place a support call to a technician in a centralized location. The software allowed the field technician to use their camera to visually show the centralized technician the problem. Using the software, the centralized technician could either freeze the screen and use signaling to troubleshoot or insert augmented reality “hands” into the actual environment, showing the on-site technician what to click, remove, etc., to resolve the problem.
By using this tool, the Service Delivery Team was able to increase their ability to resolve issues without a repeat visit, which incurs additional time and travel costs. That said, Impact Networking did note one downside: some challenges with signal/connection when working with rural or extremely urban/downtown clients.
Nevertheless, this approach to learning helped field service apprentices quickly become proficient. With little turnover and no backfilling, Impact Networking did not need to continue using the technology once its new technicians achieved full competency, but the company does see potential use cases in the future to bring it back for larger adoption among its Tier 1 engineers touching physical IT hardware.
• Cardinal Health: Cardinal Health’s L&D Center of Excellence piloted Synthesia AI software, using it to develop more than 100 deliverables and create six global trade training modules for 6,000 employees in 10 languages.
The AI-powered software utilizes realistic-looking avatars with diverse and customizable appearances and voices, enabling efficient translation and delivery of training content in multiple languages. Synthesia’s AI translated scripts, on-screen text, and captions in minutes, significantly reducing development time. As a result, Cardinal Health completed the project 40 percent faster than with using traditional methods.
• HD Supply: As part of its Product Knowledge University (PKU) initiative, HD Supply partnered with Bosch and game-based learning provider Attensi to launch a Web-based training experience designed to deepen product knowledge among its customer-facing teams. Focused on Bosch appliances, the program replaced static eLearning with a competitive, points-based game where repetition, real-time feedback, and leaderboards reinforced learning. Associates advanced through gameplay designed to motivate through score progression and peer rankings.
Rooted in behavioral science, specifically the COM B model, the gameplay fostered capability, opportunity, and motivation through continuous practice and feedback. Training was delivered via desktop and included certification for associates who achieved a minimum score of 80 percent. HD Supply issued Credly digital badges to those who met this threshold, adding layers of motivation, public recognition, and support for career advancement.
Prior to launch, the company conducted a controlled study comparing outcomes between two groups. One completed prework through an Articulate Rise course, while the other entered gameplay directly. The prework group outperformed the game-only group by approximately 25 percent, showing the value of a scaffolded approach.
HD Supply measures behavior change through gameplay analytics, including completion rates, replay frequency, and leaderboard activity. Business outcomes are evaluated through metrics such as Net Promoter Score and Voice of the Customer. Agent product knowledge now is a tracked element within these feedback loops, linking training directly to service quality.
Lessons learned: Begin with structured prework, build repetition into gameplay, and recognize success. Cross-functional collaboration and data tracking are key to driving behavior change and business impact.
• Dexian: Dexian incorporated an AI role-play bot into its Introduction to Recruiting (ITR) program. The purpose of the “RoleplAI” bot was to help new recruiters role-play 25-plus additional candidate scenarios outside of their scheduled oneon- one role-plays with their mentors and managers. ITR program managers worked with the Technology and Innovation team to create different recruiting scenarios that vary in level of difficulty and provide new recruiters with the opportunity to practice real-life on-the-job situations. Through the RoleplAI bot, recruiters are scored and receive constructive feedback highlighting areas of improvement and encouragement to learn and grow their professional and conversation skills.
This tool was designed to help new hires overcome role-play anxiety, practice role-plays on demand without relying on others’ schedules, and receive scenario feedback and scoring. More than 40 people are now using the RoleplAI bot to role-play various scenarios, which has improved productivity across all lines of the organization. The bot allows mentors and salespeople to spend more time going over detailed, scenario-based feedback instead of conducting the role-play themselves. This allows more time to focus on improvement and secon-dlevel conversations. By integrating this technology, Dexian is creating a faster, more confident, and better-prepared recruiting team.
FUTURE OF TRAINING: FRICTIONLESS
By Apratim Purakayastha, GM, Talent Development Solutions, Skillsoft
Artificial intelligence (AI) will play a central role in the future of learning, not just in tailoring content, but in shaping entire learning journeys based on role, skill needs, and career aspirations. We’re moving toward systems that can dynamically adapt to business priorities and individual performance, making learning a strategic lever for growth.
One of the most exciting developments is the rise of integrated authoring environments that empower subject matter experts to create high-impact content without needing to be instructional designers. These platforms leverage AI to accelerate content creation, reduce production cycles, and respond quickly to emerging skill needs. Equally transformative is the integration of learning into everyday workflows. Whether it’s surfacing coaching moments inside a customer relationship management (CRM) system or embedding simulations within productivity platforms, the future of training is near frictionless. This creates an environment where development becomes a natural part of the workday, not a separate task.
Looking ahead, the pace of innovation will only accelerate. As AI, immersive media, and skills intelligence mature, we’ll see entirely new formats and delivery models emerge—ones we haven’t yet imagined.
Agentic AI will be the catalyst for many of these new models. AI agents increasingly will take on tasks alongside human employees, which means L&D teams will need to evolve their strategies. They won’t just be training people anymore. Teams will need to onboard, assess, and continuously upskill AI agents, as well. Understanding how these agents learn, adapt, and align with business goals will become a core competency for modern learning organizations.
Ultimately, the most powerful training programs will be those that combine cutting-edge technology with a deep understanding of people—and those that use innovation to unlock the potential of every learner and business.
CONVERSATIONAL LEARNING WITH AI AGENTS
By Ankur Edkie, Co-Founder and CEO, Murf AI
Over the past decade, learning went digital— becoming more accessible, flexible, and available on demand. It helped organizations scale training to wider audiences, anytime, anywhere. Today, most enterprise digital learning sits inside screens: clickthrough videos, learning management system (LMS) libraries, and slide decks.
But in making it scalable, we sometimes made it solitary. Digital learning brought many benefits but was lower on interaction. It’s no surprise, then, that a 2024 study by Murf AI found nearly 1 in 3 enterprise Learning and Development (L&D) leaders cited learner engagement as their biggest challenge when deploying digital training content. Real learning isn’t always a broadcast. It’s often a conversation. We learn by asking questions, testing ideas, and getting real-time feedback. And seasoned instructional designers have always emphasized interaction over passive content.
In the next three years, digital training will take a new leap—it will go conversational. Powered by AI voice agents, these speech-enabled systems understand natural language; respond in real time with lifelike voices; and hold contextual, back-and-forth conversations. They don’t just deliver content. They engage learners like a coach would.
Here are three scenarios that show what this shift might look like in practice:
1. From LMS to real-time conversation. Learning won’t live in dashboards. It will live in dialogue. A sales rep could ask a live AI coach trained on company data, “How do I pitch this to a healthcare client?” and hear a tailored answer that is relevant to their role, region, and context. No slide decks. No searching. Just timely contextual guidance.
2. Training through role-playing and practice. Imagine practicing a performance review with an AI voice agent that challenges you, reacts to your tone, and gives feedback in real time. This creates a safe, dynamic space to build leadership muscle. It is no longer a workshop exercise. It’s personalized, on-demand practice.
3. Voice that builds belonging. AI voice agents go beyond translation. They speak the learner’s language with the right tone, rhythm, and cultural nuance, making training feel personal and relevant. Subtitles can convey information, but voice builds connection. When people hear content that sounds like it was made for them, it fosters inclusion and interest.
What Powers All of This?
Behind the scenes, the voice agents enabling this new kind of learning will be built on:
- A speech recognition module that converts the learner’s spoken input into text
- A fine-tuned large language model (LLM) trained on internal policies, training materials, and domain-specific scenarios, which generates the right response in context
- A low-latency multilingual text-to-speech engine such as Murf AI that instantly turns that response into speech, enabling real-time conversation
The real power of voice lies in interaction and connection. People engage with it. They trust it. They learn from it. That’s why the next breakthrough in L&D will go beyond digital content. It will be driven by richer context, real conversations, and AI voice agents as the interface that makes it possible.
