I had the opportunity to participate in the Microsoft AI Tour, and it was exciting to see firsthand the experiences shared from real-life projects, particularly the Zava demo project.
Here are my key takeaways:
AI will accelerate development and streamline business workflows. It can enhance software quality and security, but it’s crucial to remember that a human must always be involved in the process and make the final quality checks.
Topics such as AI governance, AI security, and data loss prevention (DLP) will be critical in creating productive environments for all organizations, including small and mid-sized companies.
Maintaining high data quality is essential for effective data processing. Data lakes comprise multiple data sources. To transform each data source into data meshes or data products is increasingly important. This encompasses areas such as event streaming and data engineering.
In my experience, every organization or team navigates a learning curve when they begin to adopt new approaches and tools in software development. I’ve noticed that while low-code solutions can lead to impressive early progress, it’s crucial to be aware that a prototype or proof of concept does not meet the criteria for a functional system according to European and German regulations. T-shaped experts will be essential in navigating this AI landscape effectively.