AI is plagued by inflated and unrealistic expectations due to a lack of broad understanding of this wide-ranging space by software vendors and customers. Software tools can be extremely powerful, however the services, infrastructure, data quality, architecture, talent and methodologies to fully deploy in the enterprise are frequently lacking. This four-part series by Earley Information Science and Pandata will explore a number of issues that continue to afflict AI projects and reduce the likelihood of success. The sessions will provide actionable steps using proven processes to improve AI program outcomes.
Part 1: Why AI Projects Fail – 3 Key Ingredients to Success
The series begins with a discussion of mistaken beliefs regarding AI and what it takes to be successful. During this session we cover why AI projects fail and 3 key ingredients of a successful AI project.
Part 2: Organizational Readiness
This session covers ways of identifying key stakeholders and the factors that influence how well an AI pilot can be operationalized and scaled.
Part 3: Why You Need Ontology and Information Architecture for Artificial Intelligence to Succeed
In this sessions you learn what an ontology is, the critical role ontologies play in AI programs, and an introduction to how ontologies are developed and applied.
Part 4: What's next – how and where do you focus your resources?
In this session we discuss how to take your program to the next level by learning how to identify and eliminate roadblocks to success.