# Two Key Elements of AI

Go back to the [[Main AI Page]]
See the [[Week 1 - Introduction]] AI contents page

#AIBusinessCase 

## Componentry

- A unified, modern data fabric. 
	- Data must be prepared for the AI to use. 
	- Logical representation of all data assets.
- A development environment and engine.
	- A place to build, train, and run AI models.
	- End-to-end, input-to-output.
	- models help find patterns and strctures in data that are inferred rather than explicit.
- Human features
	- HUman features.
		- UI/UX attached to the AI's IO with features like voice, language, vision, and reasoning.
- AI management and exploitation.
	- Enables you to insert AI into any application or business process.
	- Make sure you can test, bench-test, improve, check what has changed, and measure variance.
	- This is how you manage AI lifecycle, proof, and explain-ability of decisions. 

## Process

- Identify the Right Business Opportunities for AI.
	- Customer service (chatbots)
	- Employee/company productivity << Reference for Proposal
	- Manufacturing defects
	- supply chain spending
	- If it can be described >> It can be programmed >> Ai can make it better
- Prepare the Organization for AI.
	- [[The AI Job Replacement Axiom]]
	- All technology is useless without the talent to put it to use
	- Repetitive and manual tasks will be automated
- Select Technology & Partners.
	- Corporate culure should drive the choice of AI technology mix.
	- Adopt many technologies and learn which ones work and which ones don't.
	- Pick and handful of partners that have the skills and tech to get the job done.
- Accept Failures.
	- [[AI's Ratchet effect]]
	- If you try 100 AI projects, 50 will probably fail. 
	- But, the 50 that work will be more than compensate for the failures. 
	- The culture you create must be ready and willing accept failures, learn from them, and move onto the next. 
	- Fail-fast, as they say.