Rethinking workplace learning with AI
Like many medium sized organizations, we faced challenges. A way to modernize your learning infrastructure without digitizing old content. Our legacy learning process was fragmented, difficult to scale and did not support the needs of a rapidly growing international workforce. That’s when you make a bold move. We have rethinked what our Learning Management System (LMS) is. In addition to upgrading software, we also created a learning ecosystem with AI (AI) tailored to our business strategy, empowering our employees and embedding learning directly into our workflow.
We named Initiative Chloe, our internal hub for learning, opportunity and empowerment. In this article, we share our approach, lessons learned, and why this model represents the future of workplace learning.
From LMS to AI-powered learning ecosystems
Traditional LMS platforms often focus on compliance, are difficult to navigate and are disconnected from everyday tasks. We didn’t want that. We imagined the following system:
Support your personalized learning journey. Provides just-in-time knowledge support. It expands across teams and countries. It empowers managers as much as learners. Use AI to increase user experience and relevance.
After evaluating several platforms, we chose a platform that used AI as the core. What stood out was its ability to provide natural language search, personalized recommendations and contextual content delivery within an all-sleek and intuitive interface.
Strategic goals behind an AI-powered learning ecosystem platform
Chloe wasn’t just an IT project. It is designed to directly support three strategic pillars.
International expansion
It required consistent onboarding and training across borders. Innovation enablement
Our team works with ever-evolving technology. You need to learn to keep pace. Scalable, standardized distribution
I wanted to avoid reinventing my training every time a new team or client project was launched.
We also viewed this as a way to shift the role of L&D from content distributors to strategic enablers of culture, capabilities and growth.
Our implementation approach (what worked)
Here’s how Chloe was developed in four intentional stages:
1. A full content audit was performed to identify discovery and plan redundancy and gaps. Success metrics were defined as fronts (e.g., productivity time, course completion, manager feedback, etc.). 2. Pilot and System Configuration Started staff and pilots from newly acquired companies. All onboarding happened within Chloe. There is no external email chain or PDF. Feedback from users and managers shaped the final structure. 3. Content transformations over 50 legacy resources have been rebuilt as interactive modules using the Ai-Enhanced Authoring tool. Multilingual support and accessibility are now incorporated into all assets. Subject experts (SMEs) assembled the content together with educational designers. 4. Essential training in Go-Live and change management on the new internal platform was delivered to all staff. Internal campaigns, leadership videos and peer-led recommendations helped drive recruitment. Usage dashboard provides real-time visualization of completion and engagement.
Important initial results
The platform has quickly demonstrated value beyond expectations.
Onboarding
87% of pilot users completed the onboarding on time, reporting faster integration and clearer expectations. engagement
The course completion rate for the first company-wide rollout is 82%. Manager Enablement
Team Lead used Chloe’s AI assistant to build onboarding plans, coach team members, and answer process questions. Cultural change
Small and medium-sized enterprises have started to actively contribute content, and L&D’s company-wide perception has changed from “optional” to “Essential.”
How AI made a difference
What really sets Chloe apart is the AI. Here are three outstanding features that have inspired you.
Semantic Search
Employees will ask questions such as “How can I complete my travel bill?” and receive relevant curated answers from training materials, policies and tools.
Personalized learning path
Chloe recommends learning based on employee roles, interests, and usage patterns, supporting autonomy and engagement.
Real-time support
The built-in AI assistant supported learners and managers while working as well as training sessions. This helped to embed learning into increased work flow and productivity.
Smart guidance for managers
While many AI features are designed with learners in mind, Chloe’s true strength is her ability to support managers in real time. During the test, I asked the AI a natural language question that included:
Chloe produced a practical and structured onboarding plan that includes:
Tool access and onboarding documentation recommendations. Register for new recruits in platform-specific training modules. We suggest mentoring, shadowing and check-in. Adjust your expectations using a structured one-to-one and feedback prompt.
The response was more than just general advice. Linked to internal guides, suggested specific courses and even provided timelines. This feature allows managers, especially those with limited L&D experiences, to provide consistent, high quality onboarding with minimal support. At this moment, I saw the true potential of AI in learning. It’s not just a possibility for learners personalising, but also for leaders.
Lessons learned (so far)
We are still on this journey, but here is our biggest takeaway:
Not only HR infrastructure, but also learning as a business system
Our platform was built with input from our learning teams as well as operations, IT, sales and leadership. The result is a system that supports large business processes, team performance and culture.
AI is not just a delivery engine, but a decision support partner
AI has helped us scale faster and serve our employees properly, but its real value comes from enhancing human decision-making. Managers generate onboarding plans, answer operational questions, and through AI guidance, the coach team represents the transition from content delivery to strategic realization.
Adopting frictionless drives
Forget the 45 minute module. Employees accepted content that was short, searchable and tailored to their actual needs. Natural Language Search has transformed LMS into a daily tool, not just a training library.
Measure and make it visible
Track your learning impact along with business goals and key outcomes (OKRS), including time to productivity, course completion, certification rate, and manager activation. These metrics help position L&D as a driver of strategic outcomes rather than siloed features.
What’s next for the AI-powered learning ecosystem?
Chloe is just getting started. We are now exploring:
AI Coaching and Mentoring
Features for personalized leadership development. Predictive analysis
To identify skill gaps before impacting performance, expand integration
Use tools for influx learning. Link learning activities with business outcomes
As defined in OKR, client retention, project success, etc.
Our long-term vision is a seamless, data-driven, continuous, fully embedded AI-enabled learning culture.
Final Thoughts
If your organization still relies on traditional LMS, or worse still patchwork of PDFs, SharePoint folders, and manual processes, it may be time to completely rethink the role of learning. It’s not just about building an AI-powered learning ecosystem, but it’s not just about technology upgrades. It is about rethinking how we support strategy, culture and performance in a rapidly moving world of learning.
We don’t claim to have all the answers. But with Chloe, we built a learning system that evolved with us. Want to explore how you can build Chloe and how AI can support an organization’s learning strategy? I want to connect.
Let’s connect
If you are investigating AI-powered learning strategies or building your own learning ecosystem, we would like to connect and share ideas. Reach out!
