Making use of artificial intelligence takes more than just buying the technology and flipping the "on" switch. Companies need to understand the goals they want to accomplish -- and ensure that they have the right data to get there. "You can't expect the AI to come up with the solution for you," said Phil Crawford, Chief Technology Officer at Nashville-based CKE Restaurants. "You really have to think about your end goal. Are you trying to achieve speed? CKE operates thousands of Carl's Jr. and Hardee's restaurants around the world and wanted to use artificial intelligence to help with drive-through automation. That goal required the aggregation of different kinds of data from different sources, including drive-through timers, personnel information, sales data, and audio from the drive-through speakers. As a result, the first step the company took was to create a data lake to aggregate the data sources. CKE opted for Snowflake as their platform and began implementing it in the last quarter of 2021. "We couldn't skip it," said Crawford. "There's no other way to do it.

As more organizations deploy AI projects and products, many enterprises are looking beyond surface-level AI. They're looking to take their AI projects to the next step. One way to do that is by pursuing an AI-first data strategy, according to Forrester Research. This means creating machine learning and data models that are designed with an AI mindset instead of trying to use already created data to fit their AI. Phases of an AI-first strategy include delivering and deploying data for scale, testing and training models to create trust, and discovering and sourcing data that represents the business model of the enterprise.