Spend 15 minutes with four diagnostic questions to find your first AI agent: target frequent, patterned, and measurable problems. Build an agent that handles the repetitive work while people keep judgment and accountability.
Answer-first: Your first AI agent should solve one frequent, explainable, measurable problem that wastes time or money — not be the latest shiny tool. Use four targeted questions to find that problem and deploy an agent that supports people, keeps human judgment, and returns clear value quickly.
TL;DR: Spend 15 minutes answering four diagnostic questions: Where is your biggest labor cost? Where is your biggest revenue leak? Where does delay cost you most? Where are you overly dependent on one person? Circle one weekly problem that shows a pattern and delivers a measurable win when automated, then build an agent to handle the repetitive parts while people retain decision authority.
It’s tempting to pick the flashiest AI tool first. That’s the wrong approach. The fastest route to real value is identifying where your business already leaks time, money, or opportunity, and then building a focused agent to plug that hole. The goal is repeatable improvement in a single process, not an all-at-once transformation.
Set a timer for 15 minutes and answer these four questions honestly. Use the examples below to help you recognize where an agent can add practical value.
Look for work you pay good people to do that is repetitive, rule-based, and time-consuming. These tasks are candidates for an agent because they follow clear rules and recur often.
Track where potential revenue slips away because nobody has time to follow up, notice a pattern, or act quickly enough. An agent won’t close deals for you, but it can make sure the right human sees the right opportunity before it disappears.
Find the gaps between events and action. If a delay harms deals, relationships, or trust, that delay is a target for automation.
Ask what happens if a key person is unavailable tomorrow. I am not suggesting AI replaces that person. Instead, ensure the repetitive parts of their role are documented and automated so the knowledge does not live only in one head, inbox, or spreadsheet.
Automating routine tasks preserves continuity — the person still owns judgment calls, but their time is freed for higher-value work.
After answering the four questions, circle ONE problem that meets all three of these conditions. This keeps your first agent focused and achievable.
Example A: Sales prospect research
If your sellers spend an hour building prospect briefs for every outreach, that task likely happens weekly, follows a pattern (what to look up, where to record it), and would save measurable time. An agent that compiles a standardized prospect summary for review meets the three tests.
Example B: Proposal follow-up
If proposals sit for days waiting on follow-up, and you can identify the trigger and timing for nudge messages, an agent that recommends or drafts follow-up messages and flags overdue proposals fits the criteria.
An agent’s role is to handle repetitive work and surface the right things for human attention. It should produce drafts, summaries, alerts, or checklists that a person reviews and owns. Human accountability and judgment remain essential for consequential decisions.
Sandy Waggett, an AI integrator at MSW Interactive Designs, recommends starting with a tightly scoped agent that frees people to focus on judgment and relationships while the agent does the routine lifting.
Not every problem requires an AI agent. Some issues are better solved with simpler automations, better training, or a change in process. If the task is infrequent, lacks a clear pattern, or the “win” cannot be measured, pause and consider a non-AI approach first.
If you want a practical list of agent ideas, download the 101 AI Agents report to see concrete examples. When you’ve circled one problem that meets the three tests, consider a short review — request a process review and we’ll help you determine whether an agent, a simpler automation, or a people-first fix is best.
Spend 15 minutes with these four questions. Pick one repeatable problem. Build an agent that does the routine work and leaves judgment to your team. That approach creates real, repeatable value without sacrificing human accountability.
— Sandy Waggett, MSW Interactive Designs
