Begin with one repeatable task.
Imagine a recruiting team that receives many candidate applications. The goal is not to let an AI system decide who gets hired. Start with the narrower task of organizing the information a recruiter already reviews.
Give the AI a bounded job.
With agreed data access and criteria, an assistant could summarize relevant experience, organize screening notes, and point out missing information. The output should show its source and uncertainty so a reviewer can check it. Rules for privacy and access belong in the design before a pilot starts.
You: define requirements and permissions. AI: prepares research and notes. Recruiter: checks the evidence, speaks with the person, evaluates fit, and recommends a shortlist.
Explore AI solutions ↗Name the human owner.
The reviewer needs enough time and authority to correct the output, ask for missing context, and stop a weak result. Customer conversations, candidate assessments, promises, sensitive cases, and final approvals stay with accountable people.
Test it before expanding.
Run a small sample against the existing process. Track time spent, corrections, escalation cases, and whether the result is actually useful. Then improve the instructions or handoff. Only expand after you know what works.
The same pattern can fit sales research, customer care triage, operations updates, or marketing drafts. The exact workflow depends on your tools and rules.