Five phases for the introduction of AI
Do you meet all of the above requirements? The next step is to start implementing one or more AI tools.
For AI integration, you will not only have to manage technical aspects , be aware of the changes in the company and try to create acceptance for the new technologies within the company . Without acceptance from employees, the introduction in the company will fail.
Your AI implementation project will likely go through the following phases:
1. Objective
This aspect was already mentioned in the prerequisites. However, defining the goal can also be the first step in the actual implementation .
Clarify with colleagues and/or their representatives what iran number dataset purpose AI applications should serve in the future . Also explain how these systems work and provide the relevant information in writing. This will break down barriers and create acceptance - employees will realize that they have to learn how to use them.
Based on the goals and objectives, you determine the possible impacts on your organization and its employees .
Ask yourself these questions:
What specific business problems or opportunities should the AI system address?
Which types of AI are best suited to the company's needs ?
What are the potential risks and limitations of the AI system and how can you mitigate them?
Which key performance indicators (KPIs) are used to measure the success of the AI system in achieving its goals?
Your most important steps after setting goals:
Identify suitable use cases. Where could AI create added value for the company?
Engage stakeholders. Talk to key stakeholders such as department heads and IT staff to understand their views on integrating AI.
Establish a foundational understanding. Ensure that the successes and failures of previous AI projects help improve the understanding of AI across the organization.
2. Planning
The focus is on planning the AI system. How should the employees and the system work together in the future? Your goal should be to create interfaces and opportunities that are pleasant for people and make them more productive - comparable to a new colleague with whom everyone gets along well and can work together effectively.
Not only everyone involved in the implementation, but also all employees who will work with the system or tools in the future should understand how they work and how the artificial intelligence arrives at its results . That is why the AI system should be as transparent and easy to explain as possible.
Another important aspect in this phase is data: What data will the AI use? How will it handle it ? The issue of data protection and the security of information should also be considered here.