AI powered learning ecosystem
Evolving learning from compliance to a true learning experience for 4M+ learners. Transforming traditional, destination driven learning portal into learning ecosystem that supports learners in the flow of work.
Customers + Impact
Learning management system serving 4M+ Amazon employees
Role:
Leadership interfacing, Concepts and Visual design, Interaction design, Prototyping
Timeframe
6 months
Preview of solution
AI assistant teaching mode provides on demand, custom learning with conversational sessions, editable plans and interactive check points
Learning progress tracking, nudge reminders and badges within employee’s own profile
View in depth training history, grades, learning with AI and popular courses on My learning dashboard
Before
Cumbersome discovery
Learners had a hard time finding learning as it was buried in the menu on their work portal. Some learners could not find their way into the tool.
No motivation to learn independently
Learners visit their learning portal through notifications about mandatory and compliance trainings and do not expect much in terms of active learning.
Outdated page with minimal experience
As the main priority of the product previously was moving compliance trainings over from a third party platform to in house LMS, minimal investment was made on the learner experience.
🕵🏻♀️ Understanding the problem
Traditional training approaches, scattered across multiple platforms with static content, fail to provide the personalized, just-in-time instruction that modern professionals require to remain competitive and confident in their role. With 39% of core skills expected to change by 2031 and AI accelerating industry disruption, employees need seamless, personalized learning integrated into their workflow.
57% of employees reported difficulty finding due to fragmented systems and poor discoverability
Only 2% of training was self-initiated by employees in 2025
70% of employees lack time to balance learning with daily responsibilities
72% of employees want more career-aligned development
Vision
Transform employee learning through AI and deliver personal experience that allows seamless and continuous learning to support individual growth. This customization will be based on data such as trainings completed, searches performed, role, goals, and insights from the skills graphing engine, which maps the user’s skills to those required for various roles across the company.
🛠️ Solving the problem
The initial exploration and design was aimed at introducing micro-learning and learning ingresses into users’ news feed and redesigning outdated page. Additionally, we designed an initial AI built custom learning paths.
Serve micro-learning content designed to keep development engaging and accessible.
Deliver smart recommendations and tailored skill development
Provide AI assisted custom course creation based on Ai skills assessment
Introduce social proof and goals tracking, to increase motivation
AI Powered custom learning path creation
Request a topic from AI assistant
Skills chart powered customized path
Insight into training set selection
Phase 1 design
Learn home redesign into a full feature hub
Relevant recommendations
Goals section
Curated learning paths
Assigned training, Managing and filtering mandatory training
🧭 Leadership feedback
We showcased our new design vision at a yearly Amazon Leadership summit. The designs were overwhelmingly well received and earned a Most Innovative award from shareholders. We also had the opportunity to gather reactions to the tools and direction of the vision from stakeholders and customers. We received some actionable feedback for iteration.
Learning hub is still too destination driven and does not promote organic discovery enough
AI assistant needs to be more advanced and not only create collection of existing trainings but rather offer a full interactive learning experience
We need to push the designs further to solve customer painpoints
Next steps
After rollout of our designs at a leadership summit and gathering feedback, we advanced the solution to integrate learning across employee experiences vs maintaining one destination. Additionally, we advanced the AI assistant from just building courses to offering direct lessons.
Surface learning via multiple touchpoints vs via one destination
Deliver hyper-personalized learning in the flow of work
Offer interactive formats like AI Teaching, podcasts, microlearning
Transform development into an integrated, seamless part of daily work, supporting continuous skill growth without disrupting productivity
Phase 2 design
The next design phase was aimed at analyzing how we could introduce learning across most frequented employee touch points and offer fully interactive AI assistant learning experience. To get more holistic perspective, we collaborated across multiple teams and held a design workshop to get inputs on ideal employee touch points.
Meeting learners across multiple touchpoints. Whether it’s an employee hub news feed, AI assistant, or their personal Profile, they”ll find easy to access learning opportunities.
Closer look: AI Assistant teaching mode
On demand, custom learning
Conversational session and editable plans
Quizzes and progress badges
Different learning formats like podcasts
Closer look: Employee hub news feed
Digest reminders for due soon and overdue trainings
Microlearning modules and videos in feed informed by team interests, personal interests, and smart engine recommendations
Social proof and public recognition of learning achievements
Ready made AI assistant lessons
Knowledge tests that allow user to test out from some trainings
Learning from within employee’s own profile
Progress tracking, nudge reminders and badges
Shortcuts to required and recommended trainings
and recommendations based on their role, goals and interests directly into employee’s profile via Learn widget.
In depth learning dashboard
View all learning in depth including training history, grades and certificates
Information chips highlight due dates, learning with AI and popular courses
Easy ingress to learning with AI
All relevant recommendations
🕵🏻♀️ User research and feedback
We tested the new experience for personalized learning and AI assistant teaching mode with our customers.
Biggest takeaway
To make personalized and AI assisted learning truly impactful, we must build learning that adapts, not intrudes. Give users tools to shape their path, see their progress, and connect learning to outcomes, while making the experience feel lightweight, contextual, and safe.
Learning recommendations need clarity and restraint
Users liked seeing learning in their news feed if it was visually distinct, well-placed, and not overwhelming. Too many or too generic recommendations reduce perceived relevance. Social proof helps but only when it’s personal (e.g. “trending in your job family”).
AI assistant teaching mode
Users saw clear value in the AI teaching mode. The biggest wins were:
Bite-sized, easy to accomplish learning
Quizzes with real-time feedback were viewed as the most valuable part of the experience not just for validation, but for actual learning.
Visible progress felt focused and motivating, especially when compared to longer static courses.
Suggested learning works, when recommendations are transparent
Users preferred proactive course recommendations, but trust hinges on transparency: users want to know why something is recommended and how it benefits them. Opt-in models and light customization were favored over full automation.
Users want personalization, but on their terms
Participants favored customization (choosing duration, depth, style of AI learning session) over aggressive AI-driven personalization and are cautious about deeper personalization using sensitive data (like their performance or manager feedback).