Useful information about artificial intelligence
You don't need artificial intelligence just because a process is inconvenient. The problem may be simpler
Systems are not interconnected
The same information is duplicated across different systems
The process lacks clear rules
Information is messy and unstructured
Missing standard automation
Employees use too many different tools
Tips
How to understand whether artificial intelligence would suit our process?
It's worth starting not with the question 'where could we use AI?' but with a specific task.
For example:- Where does searching for information take the most time?
- Which documents do specialists constantly review manually?
- Which decisions require evaluating a lot of different information?
- Where are similar responses or proposals constantly being prepared?
- Which changes in data do we notice too late?
- Where does the process get stuck due to lack of expert knowledge?
Where to start an artificial intelligence project?
It's best to start with one clear task and a limited-scope trial.
In the first stage, it's worth:- Define a specific action that the system must perform
- Evaluate available data
- Decide how result quality will be measured
- Test the solution with real examples
- Determine when human confirmation is required
- Only then integrate the function into the actual process
Most common artificial intelligence terms
AI model
A system trained to perform a specific task based on patterns found in data
Language Model
An AI model adapted to understand and generate text
Generative AI
Artificial intelligence that creates new text, images, sound, or other content
RAG
A method that allows a model to respond based on connected documents or other verified sources
Hallucinations
Convincingly presented but incorrect or fabricated information from a model
Agent
An artificial intelligence system that can not only provide answers but also choose actions
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