This section explains what AI is and how start-up founders can use it to their advantage.
AI is part of the field of computer science and is a term commonly used to describe a specific category of software. This software, unlike traditional computer software, is capable of learning from the data it is fed without constant human intervention. Therefore, it can be used for applications that could not be served by non-AI technologies. Good areas of application for AI are tasks that have changing problems, and thus changing outcomes, that can be solved by processing large amounts of data, creative processes, or the creation of content - such as text.
Not every problem lends itself to the use of AI. Problems that can be solved with traditional software with the same or even better quality should continue to be solved with traditional software. This includes tasks that have consistent starting conditions and predictable end results. An example is payroll accounting. This is done according to a predefined algorithm that must remain comprehensible. It is therefore not suitable for the use of AI tools.
A good example for the usage of AI would be making predictions about user behavior. This would involve using a Machine Learning (ML) model that is fed with historical user data and then makes predictions about future behavior based on the patterns it has found in the historical data.
Another good example of the use of AI is the generation of personalized messages. Large Language Models (LLMs) are able to generate text based on the input they receive, also called prompts. By using chatbot systems that rely on LLMs, a company could create a personalized message for each customer who has purchased something from them, based on their order history.
Before continuing to the model itself, be sure to read and understand the core principles.
Follow them in order to achieve the best results.
At first glance, the following model looks like a traditional software development model - but it is far from that. Once you choose one of the three paths - AIaaS Use, AIaaS Integrate, or Individual Development - the idea is to iterate through the phases in a fast-paced, agile implementation process until you achieve the desired result. As a benefit, the first results are available in a short period of time and can be used to test whether you are on the right track. The deeper you get into technology and software development, the more advisable it is to use an approach like Scrum or Extreme Programming.
As in any traditional project, controlling should take place. The goal is to regularly check the progress of the project and make sure you are still on track. In fast-moving processes, you run the risk of losing track of past, present, and future work steps if you do not check in regularly. Effective controlling ensures that resources are being used in the best possible way and that any changes to the plan are quickly identified and dealt with. This allows you to make adjustments in a timely manner and helps you avoid costly delays or missteps. The sooner you are able to recognize that there is a mismatch between the current approach and the actual goal, the better and more cost-effectively you can re-align.
Unlike traditional software algorithms, AI is not a fixed construct that will always produce the same results for the same input. Unlike non-AI projects where rules and processes are explicitly defined and remain static, AI models adapt based on the data they are fed, making their output more dynamic. This means that the performance of an AI system can degrade or change in unexpected ways due to changes in the data environment or due to biases in the decision-making process. It is therefore necessary to establish monitoring mechanisms that allow you to regularly check the quality, trustworthiness and reliability of the AI. It is also important to ensure that the systems used comply with local legal requirements, such as the EU AI Act.
Plan the integration of AI.
AI as a Service
Use
Select the most suitable AIaaS provider.
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details.
Evaluate the implementation of the AIaaS solution.
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to
read
details.
Utilize the functionality of the AIaaS solution.
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to
read
details.
Integrate
Select the most suitable AIaaS provider.
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details.
Integrate the selected AIaaS solution.
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details.
Evaluate the implementation of the AIaaS solution.
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to
read
details.
Utilize the functionality of the AIaaS solution.
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to
read
details.
Individual
Development
Get the data needed for the model.
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details.
Train the model.
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Evaluate the trained model.
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Deploy and use the AI system in a productive environment.
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to read details.