Big Data in Business: The Lifecycle of an AI Project
Part 4 of my “Big Data in Business Series”
*Before reading this piece, make sure to check out the previous parts of my “Big Data in Business” series:
- Part 1: Data Requirements for AI-Driven Businesses
- Part 2: Data, Revenue Streams, and Valuations
- Part 3: How to Select Your First AI Project
When I teach my AI and business workshop at Stanford, one of the most surprising and insightful topics is the lifecycle of an AI project. Many assume it’s just another software project (far from it!), and they are completely caught off guard when they realize the difference in pace, costs, and data emphasis.
An AI project is a big deal. It marks the high point of an organization’s transition into an AI-driven business, so it should come as no surprise when it impacts all aspects of the company. AI projects are multidisciplinary and often massive undertakings, requiring a competent development team and effective business leaders.
While an AI project never truly “ends” due to the need for adjustments and refinements along the way, there is a point when the product can be launched. This “deployment” stage doesn’t coincide with the end of the project, but rather with the model readiness/maturity stage. This final product…
