What are three practical steps a company can take to implement an AI assistant for employees?

Here are three practical steps a company can take to implement an internal AI assistant:

1. Identify specific, high-friction use cases Start small rather than trying to build an assistant that answers everything. Look for repetitive, time-consuming tasks with clear source material—such as:

Answering HR benefits and company policy questions. Searching internal product documentation or knowledge bases. Summarizing meeting notes or drafting standard project updates. Picking one or two well-defined workflows makes it easy to measure success and collect actionable feedback.

2. Establish clear security, privacy, and data boundaries Before rolling out any tool, ensure your data is protected:

Vendor terms: Ensure enterprise agreements prohibit using your company's proprietary data to train third-party public models. Access control: If connecting the assistant to internal repositories (via Retrieval-Augmented Generation / RAG), respect existing permissions so employees can only access documents they are authorized to view.

Usage guidelines: Create a plain-language policy explaining what types of data (e.g., customer PII, confidential financials) should or shouldn't be processed.

3. Run a focused pilot and train for adoption Launch with a single department or an enthusiastic cross-functional pilot group before rolling it out company-wide:

Hands-on training: Show employees real examples of how the tool fits into their daily workflows, including how to ask effective questions and critically verify AI-generated answers. Feedback loop: Provide an easy way for users to report bad answers, hallucinations, or missing documentation.

Refine and expand: Use the pilot insights to improve the assistant’s source knowledge and guardrails before onboarding the rest of the organization.