The Training Question Every Employee Has (And Generic AI Gets Wrong)
At some point, every employee asks some version of the same question: what should I be working on to grow in my role and career here?
It sounds simple. In practice, it sits at the intersection of role expectations, compliance requirements, available resources, prerequisite sequences, and strategic priorities. Generic AI can answer the surface version of that question. A context-engineered Learning Path Advisor can answer the real one.
RAG #4 in the Kendall Project's 100 Essential Enterprise AI Assistants is the Learning Path Advisor, an AI assistant designed to give employees and managers specific, accurate guidance on training and development. This post walks through what one looks like and what you need to build it.
What a Learning Path Advisor Does
The Learning Path Advisor is a context-engineered AI assistant built on a RAG model, that provides personalized training guidance based on who is asking, what role they are in, and what they are trying to accomplish.
At its most useful, it handles questions like:
- What training is required for my role, and what are the deadlines?
- What is the recommended path to a specific certification?
- Are there prerequisites I need to complete before enrolling in a course?
- What development options are available for someone in my career stage and location?
- When does my certification expire, and how do I renew it?
The difference between a generic AI assistant and a context-engineered one shows up in the specificity of the answers. A general-purpose AI can describe what project management training looks like. A Learning Path Advisor built on your organization's context can tell a specific employee which courses apply to their role, which are overdue, and what the enrollment process looks like.
The Five Context Blocks That Make It Work
The Kendall Framework identifies five critical context blocks for the Learning Path Advisor. Getting these structured is what separates a useful AI assistant from a sophisticated search function.
1. Roles
Training recommendations only land when they are anchored to a specific role. The Roles block captures what a person in a given position actually needs both the required training attached to that function and the development paths available for growth from it.
When building this block, it helps to think about three questions: What does someone need to do this job effectively? What does advancement from this role require? And what compliance obligations come with this position?
2. Assets
The Assets block is the course catalog, but structured in a way the AI can reason with. That means mapping which courses serve which roles, which are required versus optional, which have prerequisites, and which contribute toward a certification or credential.
Building this block often surfaces useful questions about the catalog itself: which courses are current, which map to actual role outcomes, and where there are gaps between what is available and what is needed.
3. Processes
Knowing what training to take is only part of the answer. The Processes block covers the operational side: how to enroll, how to request approval for external programs, how to submit for reimbursement, and how to document completion.
This is what turns the Learning Path Advisor from an information source into something actionable. An employee should be able to walk away from the conversation knowing exactly what to do next.
4. Objectives
The Objectives block connects individual development to organizational priorities. If the organization is building toward specific capabilities over the next year or two, the Learning Path Advisor can surface that context alongside role-specific recommendations, helping employees understand not just what applies to them, but what the organization is investing in.
This block also helps when an employee is evaluating development options. Knowing that a skill set is strategically prioritized changes how they think about allocating their time.
5. Rules
Some training is not optional. The Rules block captures compliance requirements, deadlines, reimbursement policies, and certification standards, the non-negotiable that needs to show up in the AI's responses with appropriate weight.
Without this block, a Learning Path Advisor might treat a mandatory compliance course with a 30-day deadline the same way it treats an elective development course. Rules context is what makes the distinction explicit.
Where to Start
If you are thinking about building a Learning Path Advisor for your organization, the most useful first step is auditing those five context blocks, not to evaluate the AI, but to understand what structured information you actually have available.
For most organizations, the Roles and Assets blocks are where the most work sits. Role-to-training mappings often exist in informal documentation or institutional knowledge rather than in a structured form the AI can use. Course catalogs may need some work to map clearly to outcomes and roles.
That work is valuable independent of the AI project. The Learning Path Advisor is a delivery mechanism for clarity that should exist anyway. Getting the context right is what makes the AI genuinely useful and what gets answers past the generic and into the specific.