Policy Q&A Agent
A policy q&a agent is an AI agent for employee relations, policy & compliance that answers policy and handbook questions in chat, grounded in the current approved policy documents for the employee's jurisdiction and entity, cites the source clause, and hands off to an HR partner when a question implies a live case rather than a general query.
How does the policy q&a agent work?
What flows in, what the agent does with it, where a person decides, and what comes out.
Reads from
Employee's question · Approved policy library, by jurisdiction · Entity and location · Escalation rules
AI agent · runs when an employee asks a policy question in chat
Policy Q&A Agent
A person sets the rules and can override
HR sets approved sources; HR partner takes any live case
Produces
Cited answer · Warm hand-off to HR · Unanswered-question log
What does the policy q&a agent do?
Answers policy and handbook questions in chat, grounded in the current approved policy documents for the employee's jurisdiction and entity, cites the source clause, and hands off to an HR partner when a question implies a live case rather than a general query.
What does it produce?
A cited answer from the current policy, or a warm hand-off to HR with the question captured; plus a log of unanswered questions to improve the handbook
Who decides?
The HR partner decides anything that requires interpretation or an exception; the agent quotes the policy as written and flags where the answer is not in the documents.
What systems does the policy q&a agent connect to?
Examples of the kind of systems this agent would read from or write to, so you can picture it in your own stack. The actual set is whatever you run.
-
Chat
where questions arrive
-
Policy / document store
current approved policies
-
HR service desk
hand-off tickets
-
HRIS
entity and location
What data does it need?
- approved policy and handbook documents by jurisdiction
- employee entity and location
- escalation routing rules
How would you measure it?
questions answered with citation versus handed off, weekly by topic; HR desk tickets on policy topics, monthly; answer accuracy on sampled review, monthly
What does a first proof look like?
Load the current handbook and policies for one country. Replay three months of real HR-desk questions and have HR partners grade the answers and citations.
You'd call it working when
Answers are correct and cited, anything case-like is handed off, and the log shows the handbook gaps HR already suspected.
What usually goes wrong?
- Answering from a superseded policy version
- Answering a 'general' question that is really a live grievance
- Confident answers when the policy is silent
What are the guardrails?
- Quotes approved policy only; says so when the answer is not in the documents
- Hands off to a person when a question implies a case; never gives case advice
- Never gives medical, legal or immigration advice
- Logs questions without personal details beyond what the employee typed
- Employees told they are talking to an AI and how to reach a person
What leaves your boundary is set per build; the inputs above are the ceiling, and where the model runs, what it retains, and the DPA are agreed with your security team before anything is connected.
Our read
Widely deployed and well understood. Low-risk to build well.
Some ATS, HRIS or LMS suites ship a version of this. Where yours already does the job well, switch it on. The agent earns its place when the native feature is missing, rigid, or does not respect your rules; the strategy month is where that call gets made.
Where it sits in the order
Low sensitivity, policies already exist, and the win shows in weeks
Is a Policy Q&A Agent worth building for your function?
That depends on your numbers, your data, and what else is on the map for you. The strategy month works that out.
Thirty minutes. Bring the number this would move.