To seamlessly transition from one wave of AI to the next, organizations need an acute understanding of their AI maturity. The main challenges organizations will face as they move along this journey is reducing the cost of building and operating AI projects (while simultaneously generating business value).
This white paper reveals:
- How to move past “low-hanging fruit” projects onto less obvious use cases that may be potentially more costly to implement and deploy
- A multitude of ways that a collaborative data science tool can help reduce costs associated with data projects
- Challenges that persist even after data science tools are implemented (and how data leaders can help their teams move toward pervasive AI)
- How concepts and strategies like reuse, capitalization, and MLOps play a pivotal role in helping organizations accelerate their AI maturity