Choose AI Support and Human Decision Boundaries
Decide whether the bottleneck needs inbound qualification support, outbound AI SDR capacity or a simpler process repair.
What you will complete
Complete a responsibility map for capture, matching, research, scoring, review, response and policy ownership.
Diagnose the bottleneck before choosing the category
An AI SDR usually supports outbound prospecting: account discovery, research, outreach preparation, sequencing or reply classification. An inbound qualification system starts with a request the business already receives. It captures, matches, enriches, scores and routes a brief for review.
If worthwhile enquiries already wait for research or ownership, adding outbound volume does not repair the constraint. If inbound works well and the business needs prospecting against a tested ICP, AI-assisted outbound may be relevant. A broken form, unclear ICP or unowned queue may need process repair before either system.
Write the job first. Product names and autonomy claims vary. The team needs a boundary it can test regardless of platform.
Assign the least risky capable mechanism
| Work | Possible mechanism | Human responsibility |
|---|---|---|
| Capture and normalize fields | Deterministic integration and validation | Approve required fields and handling rules |
| Match accounts and duplicates | Rules plus review for uncertain matches | Resolve ambiguous relationships |
| Summarize approved evidence | AI assistance with source pointers | Inspect evidence before consequential action |
| Apply scoring rubric | Rules or AI-assisted interpretation | Own criteria, thresholds and overrides |
| Accept SQL and respond | Human decision and action | Own relationship and commercial judgment |
AI confidence does not replace evidence quality. Show the source, missing fields and conflicts to the reviewer. A recommendation that cannot explain itself belongs in review.
Worked example: Harborline responsibility map
Fictional example: Harborline uses ordinary rules to capture forms and detect exact duplicates. An AI step summarizes approved website content against the written rubric and cites the pages it used. The scoring layer recommends a review band and shows unknown fields.
Revenue operations owns source policy and matching exceptions. A salesperson accepts SQLs, chooses whether and how to contact the person, and runs discovery. The revenue leader approves changes to the ICP, thresholds and response policy. No model may create a promise about price, timing or service eligibility.
Harborline does not need an autonomous outbound agent for this course. Its current bottleneck is inconsistent inbound review and assignment.
Complete section 4 of the workbook
- State the actual bottleneck: inbound review, outbound capacity or process clarity.
- List each system step and assign rules, AI assistance, human action or process repair.
- Name the evidence shown at every human gate.
- Name the person who can change policy, correct a result and pause the system.
Stop conditions
Pause automation when the team cannot define fit, lawful and approved evidence sources, ownership or allowed actions. Keep sensitive or conflicting requests in review. Do not use qualification automation to make hidden eligibility decisions or to send messages a responsible employee has not authorized.
A smaller deterministic workflow may solve the problem. Automated capture, duplicate matching and queue alerts can create value before any AI interpretation is added.
Check your decision
1. Inbound enquiries wait because nobody assembles context or assigns an owner. Which category fits that bottleneck?
2. Which decision should remain with sales?
3. What should an AI-generated lead summary include?
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