Explore the possibilities of agent learning with a pioneer elearning
Dr. Allen Partridge is the director of the evangelization of Adobe's digital learning, celebrated for his speaking in dynamic public and his insightful writing on immersive learning, gamification and education improved by AI. His doctorate in interdisciplinary studies uniquely integrates art, music, theater, philosophy and computer science, reflecting the rare intersection of creativity, technological mastery and deep critical thinking. The rich academic and professional journey of DR Parridge perfectly positions it with the link of specialized knowledge and AI technology, embodying the skills of unicorn sought essential to stimulate innovation and effective collaboration on labor evolving today. Today, he talks to us about the role of AI in content creation and conservation, agent learning, and what emerging technological features should look in their next LMS.
Depending on your experience, how can L&D teams use AI to stimulate efficiency at each stage of creation, conservation and delivery?
The greatest force of AI in L&D today is an accelerator – not a disruptor. Rather than upsetting established workflows, AI can improve them: to accelerate content creation, refine research and discovery and optimization of delivery between groups of learners. A global company used The AI recommendations of the Adobe Learning learning manager To train more than 36,000 employees with more than 20% of the general administration costs, without modifying its basic strategy. Another scale certification at scale of more than 900 locations by personalizing delivery via AI, increasing the scope while reducing operational friction. You will find below a hypothetical health care company, Ops Labs, which sells a health computer solution to specialized doctors. AI recommendations can help recommend courses according to the area of interest, popularity of course, etc.
This type of improvement can affect each step of the learning cycle. The AI can help in writing, to create learning paths dynamically depending on the user's behavior and information on surface data to support administrators. The result is faster delivery, more relevant learning and better decisions without reinventing the wheel.
Can you tell us a little more about agent learning and how can it help organizations stimulate productivity and empower Pros L&D?
Agent learning Referring to an emerging AI model where autonomous agents act in the name of the learner, adjusting the experience in real time according to objectives, behavior and context. It is a static learning trips to something more dynamic and responsive. Imagine a forest of small specialized assistants – a timely surfing on resources, another pushing one user to mastery, another suggesting the following steps based on the progress observed.
Although always on the horizon for many, the potential is convincing. These agents could reduce the need for constant manual conservation and give learners more autonomy, which both help the L&D teams to evolve without sacrificing relevance. We see the first explorations of this concept in adaptive recommendations and the learning paths aware of the role, and platforms like Adobe Learning Manager evolve to support this type of intelligent experience and centered on the learner.
One of the features we deploy in beta is an AI administration assistant to raise the self-service experience of the L&D administrator. The assistant powered by AI is designed to provide instant and precise responses to your common requests and your troubleshooting problems on the platform without referring to long documentation or dependence on our assistance teams.
What is one of your customer success stories that highlight the power of AI and human collaboration?
Two examples come to my mind: very different organizations, but they emphasize how AI can extend human capacity without replacing it.
A global airline, operating through a vast model of franchise, had to train tens of thousands of staff in dispersed regions. Their L&D team used Adobe Learning Manager to integrate content recommendations fueled by AI in its platform, surfacing the most relevant materials for each learner according to the role, activity and geography. The strategy was always managed by humans: the educational designers have set themselves and chose resources. But the AI has helped to transport this content more intelligently, reducing the administrative costs by 20% while increasing the commitment through the network.
In the health care sector, a main manufacturer of prostheses has been confronted on the scale of clinicians and large -scale patients. By consolidating several platforms in Adobe Learning Manager, they were able to deliver personalized certification paths fueled by AI – corresponding to the content of the role and needs of each learner. With the design of the human surveillance program, AI played a support role: final research, personalization of delivery and the overhaul of good learning at the right time in more than 900 clinics.
In both cases, history did not aim to replace people – it was a question of empowering them. The AI has helped to extend the scope, speed up delivery and personalize on a large scale while allowing human experts to focus on quality, context and care.
What are some of the AI features that organizations should have on their unmissable list when looking for a new learning management system? How can these features personalize learning and increase engagement?
It is tempting to chase a list of control of the functionalities of the AI, but the real opportunity lies in the way in which AI is integrated throughout the learning experience, not only in a tool or a workflow. The best LMS platforms do not bolt AI on the side; They use it to accelerate content creation, personalize learning paths, support skills growth and rationalize operations, everything without disturbing confidence processes.
Organizations should look for solutions that smoothed the transition from recruitment to integration, helping new hires to quickly gain speed through automated and conscious travel. AI can help learners identify skills gaps, plan their career and follow progress with a minimum of friction. Tools such as headless delivery and open APIs support transparent integration with business systems while allowing brand experiences deeply.
Improved research and recommendation features help to surface the relevant content, while the conversation tools (such as a friend or an AI coach) offer moments of microlearning and a contextual support. Peer -based recommendation models, updated catalogs and dynamic learning paths help maintain relevance over time.
Let's use the same hypothetical health care customer, OPS Labs. They implemented the research fueled by AI for doctors. As you will see in the image below, if a user type of “health computer science foundation”, the system includes the term “health computer science” as the most important keywords, and research results show all the relevant courses that include the basics or fundamentals of “health IT”.
Commitment is more motivated by gamification, social recognition and the content generated by users, creating a culture of bidirectional learning. And for administrators, integrations with SHRM, performance systems and powerful data visualization tools allow real -time preview of learning and commercial impact.
In the end, the value of AI in an LMS is not in its novelty – it is in the way it quietly and effectively supports people, learners to L&D leaders, at each turn.
How do you think that the role of generative AI in learning will develop or evolve in the years to come?
In the near future, the generative AI will not only help create content – it will maintain it and evolve it, becoming a kind of co -author and silent editor in residence. Imagine an AI that knows each course you have launched, reviews your old equipment and quietly suggests updates according to emerging skills frames, changes in commercial strategy or even news from the last time. Your learning library remains up to date without you raising a finger.
We are also at the dawn of more proactive learning agents – tools that monitor the context (your calendar, a title, a product reminder) and a training just in time before a critical meeting. Combine this with a forest of intelligent assistants integrated into your ecosystem, and L&D pass from reagent to anticipation.
Over time, the generator will evolve in a reflective design partner – which helps learners to develop, helps designers stay lively and helps organizations building learning ecosystems which are as alive and adaptive as the people they serve.
Packaging
We would like to thank Dr. Allen Parridge for highlighting the potential of agency AI in learning and how good LMS can transform L&D experiences. If you want to know more about Adobe's capabilities, consult their Ultimate features list.
At Learnopoly, Finn has championed a mission to deliver unbiased, in-depth reviews of online courses that empower learners to make well-informed decisions. With over a decade of experience in financial services, he has honed his expertise in strategic partnerships and business development, cultivating both a sharp analytical perspective and a collaborative spirit. A lifelong learner, Finn’s commitment to creating a trusted guide for online education was ignited by a frustrating encounter with biased course reviews.