Artificial Intelligence: an Enterprise Level Set

Authors

Gary Rowe – CEO/Principal Consulting Analyst

Jeff Nichols – Principal Consulting Analyst

Contributors

Barbara Starr – Principal Consulting Analyst

Abstract

Artificial Intelligence (AI) is one of the more heavily hyped and widely misunderstood technology topics of the past 30 years—it is right up there with blockchain. This report looks to demystify AI by defining, categorizing and describing the three distinct waves of AI including the capabilities, limitations, use cases and future state expectations of each category.

This is the first of a series of reports designed to provide TechVision Research clients with practical information to assist in developing plans and allocating investments in this complex and disruptive area. This report offers a high-level AI foundation and an enterprise reality check for Line-of-Business leaders and IT executives.

We believe that the starting point for any major enterprise program is for key stakeholders to get on the same page with consistent definitions and context. This can be a challenge in AI since there are so many widely divergent categories and so much marketing hype. We seek to address this by breaking AI into three distinct waves or categories. The first wave (symbolic reasoning/directed AI) works best in supporting well-defined, static applications, but has major limitations in broader use cases. The second wave (statistical/machine learning) provides a self-learning capability by applying real-world data to statistical models to improve results over time. The third wave (contextual adaptation) blends the abilities of the previous two waves to understand and explain how a decision was made. Each wave is adept in solving distinct types of problems and are at a different maturity level.

This foundational document will help enterprises understand, categorize, prioritize and ultimately, develop strategies leveraging the various types of AI. We provide high-level recommendations and an action plan for enterprises developing strategies, architectures, governance models and plans in AI and related areas.