This video guides viewers through selecting their initial AI workload. It emphasizes the importance of choosing a project that provides tangible business value and minimizes risk, focusing on generative AI use cases but acknowledging other AI types. The video stresses preparation, including employee skilling and data readiness, before implementing AI.
Prioritize Tangible Business Value: The first AI project must demonstrate measurable impact to justify investment and build confidence. Focus on revenue generation, cost reduction, or improved customer/employee experience, with clear metrics for success.
Ensure Data Readiness: Address data quality, permissions, and access control before implementing AI. Poor data will lead to poor results. Data hygiene is crucial.
Start with Technical Feasibility: Choose a project with manageable complexity, leveraging readily available APIs and pre-built models with built-in safety features and evaluation frameworks to avoid technical pitfalls and ensure a successful first project. Avoid complex fine-tuning for the first project.
Minimize Ethical Implications: The initial AI project should avoid sensitive data and minimize ethical risks. Responsible AI is paramount.
Consider Scalability and ROI: Select a project that can be scaled up if successful, demonstrating a clear return on investment. Focus on repetitive tasks, high-volume processing, and processes spanning multiple systems.
