As public and private sector leaders develop data, cloud, and Artificial Intelligence (AI) / Machine Learning (ML) strategies, the need for a unified framework has never been more apparent. These strategies naturally overlap, presenting challenges spanning strategy development, implementation, continuous delivery, and operations.
Curated, tracked, and governed data served through cloud native infrastructure fuels impactful and high value AI/ML solutions. Organizations and their respective data, cloud, and AI divisions need to coalesce around a unified vision, strategy, and execution plan. Additionally, they must bring to bear rigorous engineering practices, coupled with a scientific approach to continuously deliver solutions that shorten the time to customer value (TTCV) and build a sustained competitive advantage.
This white paper explores some of the challenges and necessary considerations when developing, governing, and releasing AI solutions. While setting an AI strategy is essential to any AI journey, it is also crucial to consider the full-stack AI ecosystem; integrated strategy enables AI teams to develop an Ultimate Lab where data is discoverable and computational resources are scalable and secure. Accordingly, this series also includes the Cloud Strategy for the Ultimate AI Lab, Data Strategy for the Ultimate AI Lab, and Foundations for the Ultimate AI Lab white papers, which explore the implementation of each respective strategy, along with a culminating business case for strategy integration: The Ultimate AI Lab.