Academic Journal
Managing AI Software Development.
| Τίτλος: | Managing AI Software Development. |
|---|---|
| Συγγραφείς: | Schulz, Yogi yogischulz@corvelle.com |
| Πηγή: | PM World Journal. May2026, Vol. 15 Issue 5, p1-7. 7p. |
| Θεματικοί όροι: | *Artificial intelligence, *Computer software development, *Cross-functional teams, Data quality, Project management software, Machine learning |
| Περίληψη: | The article focuses on managing AI software development, highlighting its distinct challenges compared to traditional software projects due to AI’s probabilistic behavior, data dependencies, and continuous learning. It emphasizes treating data as a critical asset through governance, quality management, and versioning, and adopting Machine Learning Operations (MLOps) to automate model lifecycle management beyond conventional DevOps practices. The article advocates for iterative delivery of measurable business value, incorporating security and privacy by design, managing AI-specific risks such as bias and explainability, and fostering cross-functional collaboration among data engineers, scientists, and domain experts. Defining clear, statistically grounded evaluation metrics and maintaining robust iterative practices are also presented as essential for successful AI project outcomes. [Extracted from the article] |
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| Βάση Δεδομένων: | Business Source Index |
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