AI tools in the company: development and scaling with Copilot Studio and Foundry
The integration of AI tools into companies is becoming increasingly important in order to optimize processes and support decisions. A current offer from the heise editorial team deals with the development of agents using Microsoft 365 Copilot, Copilot Studio and Foundry. This combination allows companies to create AI-powered assistants that can be used in various business processes. Copilot Studio serves as a platform for developing and adapting AI models, while Foundry serves as a scaling solution to efficiently operate these models in larger organizations. The use of M365 Copilot also enables seamless integration with existing Microsoft tools, greatly simplifying the implementation and use of AI systems.
In addition to developing AI systems, there are also solutions that improve the quality and efficiency of AI responses. A website that helps AI users optimize their responses allows users to improve their communication and make the use of AI tools more effective in everyday life. Such tools are particularly useful for structuring and standardizing AI interactions in teams and projects. They promote better cooperation and ensure that AI tools are not only used technically, but also communicatively.
Another aspect of AI integration in the company concerns data storage and data security. Anthropic plans to move data storage for its myth models to the customer cloud. This allows corporate customers to gain more control over their data while increasing the security and compliance of their AI systems. Moving data storage to the cloud is a step towards more flexible and transparent AI systems that better meet the needs of users.
The introduction of Zero Trust is another important aspect that plays a central role in ensuring IT security in the company. One article describes how companies can implement a minimal approach to zero trust in 90 days. The minimal approach aims to increase security without compromising the flexibility and efficiency of the IT infrastructure. This is particularly relevant because AI systems often process sensitive data and therefore require higher security standards.
Overall, it shows that the integration of AI tools in companies must be implemented not only technically, but also organizationally and security-oriented. Developing AI systems, optimizing AI responses and ensuring data security and compliance are key factors influencing the success of an AI strategy. The combination of different tools and approaches enables companies to make their AI systems efficient, secure and scalable.