Start Lesson
Your operations lead drops a spreadsheet on your desk: 47 tasks the team wants to "automate with AI." Your CEO wants a prioritized list by Friday. Half of those tasks are terrible AI candidates, and the other half range from quick wins to six-figure projects. You need a scoring system that separates signal from noise in 30 minutes.
This lesson gives you that system. By the end, you will have a completed scorecard ranking every process in your business by AI readiness -- with numbers, not gut feelings.
A filled-in AI Opportunity Scorecard that ranks your top business processes by three criteria: repetitiveness, data richness, and error tolerance. The scorecard produces a single score (3-15) for each process, so you can sort by priority and know exactly where to start.
Not every task is a good AI candidate. The best ones score high on three dimensions:
| Filter | What It Measures | Score 1 (Low) | Score 3 (Medium) | Score 5 (High) | |--------|-----------------|----------------|-------------------|-----------------| | Repetitive | How often the task occurs | Quarterly or less | Weekly | Daily or multiple times per day | | Data-Rich | How much text/data the AI can work with | Requires physical action or real-time sensory input | Mixed -- some text, some judgment calls | Pure text, data, or pattern-based (writing, classification, extraction) | | Error-Tolerant | What happens when the AI gets it wrong | Single mistake causes legal, financial, or safety harm | Errors are costly but catchable with review | Human reviews output; 85% accuracy is a net win |
Scoring: Rate each process 1-5 on all three filters. Add the scores. Maximum possible: 15.
| Total Score | Interpretation | |-------------|---------------| | 12-15 | Strong candidate -- start here | | 8-11 | Worth exploring -- plan for Phase 2 or 3 | | 5-7 | Marginal -- only if easy to implement | | 3-4 | Not a candidate -- keep human |
The agency CEO wants to know where AI will have the most impact. Here is the audit:
| Process | Repetitive (1-5) | Data-Rich (1-5) | Error-Tolerant (1-5) | Total | Verdict | |---------|-------------------|------------------|----------------------|-------|---------| | First-draft blog posts (20/week) | 5 | 5 | 4 | 14 | Strong candidate | | Social media captions (50/week) | 5 | 5 | 5 | 15 | Strong candidate | | Client meeting note summaries (15/week) | 4 | 5 | 4 | 13 | Strong candidate | | Competitive research briefs (8/week) | 4 | 4 | 3 | 11 | Worth exploring | | Client proposal pricing (4/month) | 2 | 3 | 1 | 6 | Marginal | | Vendor contract negotiation (quarterly) | 1 | 2 | 1 | 4 | Not a candidate |
Fifteen minutes with this table and the priority order is obvious. Social captions and blog drafts go first. Vendor contracts stay human.
Once you have scores, plot your top candidates on two axes to decide sequencing:
Impact = Total Score multiplied by Monthly Volume. A process scoring 14 that happens 80 times per month has more impact than one scoring 14 that happens 4 times per month.
Difficulty = How hard is it to set up? Consider: Do you have the data the AI needs? Does it require integration with other systems? Does it need custom prompts or just a generic tool?
| | Low Difficulty | High Difficulty | |---|---|---| | High Impact | Start here. Quick wins. Prompt-based, no integration needed. | Plan for these. Worth the investment, but not first. | | Low Impact | Nice to have. Do after quick wins if easy. | Skip entirely. Cost exceeds benefit. |
For the marketing agency, social media captions are high impact and low difficulty (just prompting). A competitive research brief that requires CRM integration is high impact but high difficulty -- plan it for later.
Some tasks should stay human even if they score well on paper. Apply these overrides:
The question is not "can AI do this?" It is "what happens when AI does this wrong, and can we afford that?"
Open a spreadsheet or copy this table. List every process your team touches in a typical week. Score each one.
| Process | Repetitive (1-5) | Data-Rich (1-5) | Error-Tolerant (1-5) | Total | Monthly Volume | Priority (H/M/L) | |---------|-------------------|------------------|----------------------|-------|----------------|-------------------| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Your target: List at least 8 processes. Score them honestly. Sort by total score. Circle your top 3. Those are your AI pilot candidates.
If your highest-scoring process is below 8, you may not have strong AI candidates right now -- and that is a valid finding. Better to know now than after spending $50,000 on a platform.
You now have a ranked list of AI opportunities. The next question: for each of your top 3 candidates, should you solve it by prompting an existing AI tool, buying a vertical product, or building something custom? That is exactly what the Build vs Buy vs Prompt decision matrix in Lesson 2 will answer. Bring your top 3 candidates with you.
