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AI Production Decision Rubric

1. Purpose and Scope of AI Tool

Customization Needed: If a project requires highly tailored features not available in existing tools, then building in-house or partnering might be the better choice.
General vs. Specific: If your needs are generic (like general chatbots), using an existing tool might suffice. But if you need something specific to your industry or business, consider licensing, partnering, or building.

2. Budget

High Budget: Partnering or licensing might be more feasible. Building in-house can also be costly depending on infrastructure and talent acquisition costs.
Moderate Budget: Consider low-code solutions or licensing less expensive tools.
Low Budget: Look for free or open-source tools.

3. Technical Expertise Available

Expert Team Onboard: Building in-house or using low-code solutions might be ideal.
Limited Technical Expertise: Partnering or licensing can provide access to advanced tools without needing in-depth internal expertise.
No Technical Team: Using a free or open-source pre-built tool might be best.

4. Time Constraints

Immediate Need: Using an existing tool, whether free or licensed, can be quickest.
Flexible Timeline: Building in-house, partnering, or using low-code solutions can be considered if time allows for development, testing, and deployment.

5. Control and Data Privacy

High Data Sensitivity: Building in-house can provide the most control over data.
Moderate Concerns: Licensing or partnering can still provide control, but ensure data handling agreements are clear.
Low Concerns: Existing tools, free or paid, might suffice if data handling is transparent and aligns with your requirements.

6. Maintenance and Scalability

Frequent Updates Needed: In-house development or partnerships might offer more flexibility in updating the tool as needed.
Stable Long-term Use: Licensing or using an existing tool might be sufficient if the tool meets current and foreseeable future needs.

7. Integration with Existing Systems

High Integration Needed: Building in-house or partnering can provide better integration capabilities with existing systems.
Moderate Integration: Low-code solutions or licensed tools might offer sufficient API capabilities.
Minimal Integration: Free or existing tools might suffice if standalone functionality is acceptable.

8. Community and Support

Strong Community Support Desired: Using popular free tools or licensed products might offer community support and a plethora of resources.
Dedicated Support Needed: Licensing or partnering might provide dedicated support channels.
Self-support: If you have the capability to handle most challenges in-house, then building or using low-code solutions can work.

Decision Guide:

Partner with a company: When you need a tailored solution, lack the in-house expertise, and have a significant budget.
License an existing AI tool: When there's a tool that meets most of your needs, you desire dedicated support, and have a moderate to high budget.
Develop an AI tool internally: When you need full control, have the technical expertise, and can afford the time and monetary investment.
Build using low-code solutions: When you have some technical expertise, need some customization, and have a moderate budget and timeline.
Use an existing free AI tool: When you have a tight budget, immediate needs, and can work with the features and limitations of the free tool.
This rubric provides a broad overview, and decisions might overlap in some areas. The best choice often depends on a balance of these factors and the specific needs of the organization or project.
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