Accelerating AI in Your Enterprise
Artificial Intelligence (AI) is generating excitement across a range of industries. But there are many barriers to implementing AI in a company. The first barrier is in identifying the use case to be addressed with AI and the success in moving that forward is highly dependent on answering the questions that can be applied to any technology project – does it cut costs or increase revenue, does it address a key product or service, and how much are the key stakeholders invested? Once the use case is identified, there are a range of AI approaches that can be used, some utilizing a combination of techniques – machine learning, deep learning, cognitive analytics, etc. Success here is dependent both on choosing the right technique appropriate to the particulars of the use case and the data that is available. But solving an AI problem only represents 15-30% of a workflow. There are many steps both before and after the AI model development that need to be addressed while also determining how the AI infrastructure is to be integrated into an analytics infrastructure. Other dependencies include addressing how the present non-AI workflow can be modified for AI either as a drop in replacement or by altering it. This presentation will address the different steps above through discussion of one to two use cases, the barriers to realize AI, and options to address these barriers.
AAPG Datapages/Search and Discovery Article #90327 © 2018 AAPG Middle East Region GTW, Digital Subsurface Transformation, Dubai, UAE, May 7-8, 2018