Educational note: This page is general educational content, not legal, tax, investment, or Sharia advice. Formal structures should be reviewed by qualified professionals.
AI cost categories
| Cost | What it includes | How to control it |
|---|---|---|
| Discovery | Process mapping, data audit, use-case selection. | Use fixed diagnostic packages. |
| Development | Engineering, model integration, UI, APIs, automation. | Start with a narrow pilot. |
| Data | Cleaning, labeling, storage, permissions. | Reuse existing data and label only what matters. |
| Compute / API | Model calls, hosting, vector database, cloud services. | Track cost per task and cache where safe. |
| Maintenance | Monitoring, updates, retraining, support. | Design simple systems and clear ownership. |
How to estimate ROI
Start with operational value. Estimate baseline time or cost, then compare expected improvement after automation.
- Identify the workflow.
- Measure monthly volume.
- Measure time per task.
- Estimate hourly cost or opportunity cost.
- Estimate reduction after AI support.
- Subtract development and running cost.
Example: if a process takes 300 hours per month and AI reduces it by 40%, the gross time saving is 120 hours per month. The financial value depends on labor cost, quality improvement, and what the team does with saved time.
Pricing AI services
- Fixed pilot: clear scope, deadline, and deliverables.
- Monthly retainer: continuous improvement, monitoring, and support.
- Subscription product: repeated value for many users.
- Revenue share: possible when measurement, ownership, and risk are clear.
- Success fee: should be used carefully and never presented as guaranteed profit.
Balanced value sharing
AI7Sky.org should encourage contribution-based agreements. Define who brings capital, who builds, who sells, who manages, who owns IP, who carries risk, and how revenue is calculated. Avoid vague promises.
Venture readiness
Before seeking capital, an AI project should clarify problem, customer, prototype, data access, competitive edge, technical risk, cost model, governance, and ethical boundaries.