The new role of educational designers
Traditional teaching designs are built on structured paths: modules, quizzes, and evaluations following linear or branching flows. However, due to AI-powered personalization and the voluntary learning preferences of Gen Alpha and Beta, rigid structures replace the fluid, highly-demanded learning ecosystem.
No trainers or instructor designers
Instead of designing predefined courses, education designers (IDs) should provide curated, real-time contextual learning based on employee roles, past learning behaviors, and trends in emerging industries.
IDs should think about how to integrate intelligent search, dynamic learning recommendations, and adaptive content delivery. AI-powered learning platforms are predicted to soon be fully autonomous and self-curated, eliminating the need for human intervention in content design. [1]
From e-learning courses to learning experiences
Learning is not about taking a structured course. Instead, it becomes a continuous built-in process where learners “fine-tune” the right information at the right time.
McKinsey’s study of Gen Z and young employees emphasizes their preference for self-directed and autonomous learning over traditional training methods. [2]
You go your way, I go to mine
Employees will not follow the set curriculum, but they want a unique, personalized pathway that will adapt to their learning and will eliminate the formal education roadmap. It is important to note that industry experts want new generations of learners to dynamically frame content based on learning behavior and individual performance metrics. [1]
Quiz and end of ratings
The practical application of AI tracking behaviors, interactions, skills, quizzes and tests for artificial intelligence (AI) is no longer necessary to assess knowledge. Instead, it looks like this:
Performance-based evaluation. The ratings are based on performance rather than final quiz scores. When employees successfully apply skills to their work, they themselves become proof of learning. AI-driven observation. AI tools analyze workplace interactions, project contributions, and real-time decision-making to assess capabilities. Self- and peer assessments. Rather than relying on formal quizzes, employees assess their own learning progress and receive feedback from their peers. Josh Bersin emphasizes how an AI-driven corporate training platform evaluates employee’s actual task completion rate and accuracy, rather than the ability to remember information about quizzes. [3]
Learning the flow of work
For Gen Alpha and Beta employees, learning is not a separate event, but a part of the work itself.
Intelligent Search as Learning: AI-powered search tools (such as ChatGPT and company-specific AI models) replace formal training by providing instant, relevant answers whenever employees need them. Learning embedded in digital workflows: Instead of taking e-learning courses on project management, AI assistants guide employees while managing projects in real time. AI-powered mentorship and coaching: AI-driven personalized coaching offers nudges, recommendations, and performance analysis based on real action rather than structured learning modules.
A study by McKinsey suggests that Gen Z employees are highly practical learners and prefer on-demand digital assistance over structured training courses. [2]
Instructor-led community-led learning
General Alpha and Beta employees are peer-driven, rather than hierarchical, and prefer collaborative learning. AI enables distributed learning communities where knowledge is shared organically and socially, rather than being directed by instructors.
Crowd-sourced learning: Employees create and share their own learning resources to reduce their dependency on L&D teams. AI-Enhanced Discussion Forum: AI mitigates and summarises workplace learning discussions and identifies valuable insights across the organization. Peer coaching and knowledge exchange: Learning is done through expert advice in conversation, collaboration and AI curation, rather than a structured training program.
Josh Bersin says that AI-powered tools have promoted a collaborative learning environment, allowing employees to co-create learning content in real time and share it among global teams. [1]
From course creators to learning ecosystem architects
Using AI and self-directed learners in the mix means that L&D experts are no longer content designers, but the curators of the learning experience are:
We will build a learning ecosystem equipped with AI. Integrate intelligent search, adaptive learning, and just-in-time content into your workflow. Cultivates a culture of knowledge sharing. Encourage peer-to-peer learning, coaching networks and AI-supported collaboration. Build a learning journey. Provide employees with AI tools and platforms, allowing them to control their own learning journey.
Images by Commlab India
A new learning paradigm
The future of educational design is not about courses between employees, AI, real-world tasks, and ongoing knowledge, and not about courses. Instead of a rigorous training program, we can see ecosystems that adapt, evolve and integrate seamlessly into our daily work.
The research of HBR, McKinsey, and Bersin consistently points to this transformation and reinforces that AI, peer-driven collaboration, and intelligent automation will be a critical feature of corporate learning over the next decade.
The role of education designers in corporate L&D is experiencing earthquake changes. As AI-driven learning models, intelligent search, and personalized learning pathways become standard, traditional paradigms of education design (structured courses, rigorous assessments, LMS-driven training) quickly become obsolete.
To stay relevant, IDs need to learn an outdated approach, acquire new capabilities, and redefine how L&D adds value to business performance.
What you need to ID to get Linear Course Design Thinking: A traditional approach to splitting content into modules followed by quizzes and ratings, which disagrees with employees’ learning methods today. Learning is now continuous, personalized and embedded in the work. [4]
LMS-First Thinking: LMSS still plays a role, but is not a central figure in corporate learning. Learning is moving towards a Learning Experience Platform (LXPS), AI-powered content curation, and workplace learning strategies. [5]
One-Size-Fits-All Training: Historically, training has been standardized for efficiency. However, AI can enable personalized learning journeys and make general courses effective. [3]
Completion rate as a success metric: Measurement of training effectiveness by completion rate and seating time is outdated. Instead, your ID should focus on performance metrics, behavioral change, and business impact. Instructor-led learning: Employees no longer rely solely on trainers to learn. They look forward to an on-demand, AI-driven, peer-to-peer learning experience. [6]
IDs needed to learn AI-driven learning models: IDs should understand how AI dynamically curates content, provide personalized learning recommendations, and predict skill gaps based on performance data. [7]
Data and Learning Analysis: The ability to analyse learning data, user interaction and performance outcomes is important for designing an effective learning ecosystem. Being familiar with XAPI, AI-driven analytics and performance dashboards is essential. Adjust your AI-powered learning experience: IDs should integrate AI chatbots, intelligent search, adaptive learning, and nudges wrapped in workflows to create a seamless learning experience. [3]
Workflow Learning: Instead of designing a standalone course, IDs should embed learning into daily tasks using microlearning, AI-generated nudges, and just-in-time content delivery. AI-Driven Platform: IDs must acquire expertise in platforms that support AI-powered, user-driven learning ecosystems, such as Degreed, Edcast, Cornerstone, and LinkedIn Learning Hub. [5]
Social and peer-driven learning: Designing collaborative learning, discussion forums, crowdsourced content, and peer coaching opportunities is important. Agile Learning Design: Traditional models such as ADDIE have replaced a more agile and iterative approach where learning interventions are continuously refined based on feedback and analysis. What you need to do to shift from content creation to content curation: IDs take less time to develop content from scratch, curate AI-recommended resources, improve machine-generated content, and ensure quality and relevance. [6]
From delivering training to realizing learning: Instead of pushing courses, IDs allow employees to access knowledge at the right time through AI-driven content recommendations, intelligent search and real-time performance support tools. Measuring learning through business impact: Rather than focusing on completion rates and test scores, IDs should track how learning interventions improve productivity, reduce errors, increase sales, and enhance employee retention. Blending of unstructured and unstructured learning: IDs should blend informal, community-driven, AI reinforcement learning opportunities and formal learning experiences.
Images by Commlab India
Learning Ecosystem Architect: The Future of Educational Designers
Enterprise L&D instructional designers should embrace an AI-driven, experience-based, performance-focused learning approach to maintain relevance. Shifting from a rigorous teaching framework to a dynamic, learner-driven ecosystem, they can design learning journeys that truly reinforce the capabilities of the workforce.
This transformation is not an option. It is necessary for IDs to flourish in the future of AI-driven, voluntary, business-aligned corporate learning.
We begin by investigating AI-powered learning tools, integrating analytics into design, and promoting a culture of continuous, peer-driven learning. The future of L&D belongs to people in the architect experience, not just building courses.
References:
[1] Autonomous Educational Designer Arrit Creator
[2] “True Gen”: Generation Z and its impact on companies
[3] AI is transforming corporate learning faster than I expected
[4] 10 ways artificial intelligence can transform educational designs
[5] Ecosystem Mapping: Secret Secret to Optimize L&D
[6] Empowering instruction designers to build immersive learning experiences with AI
[7] How Educational Designers Use AI to Optimize Workflows and Learning Experiences
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