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DESCRIPTION:Click for Latest Location Information: http://edw2020chicago.da
 taversity.net/sessionPop.cfm?confid=143&proposalid=12324\nTraditional EIM p
 ractices have relied heavily on manual processes requiring tremendous effor
 t and costs. A transformation to an AI-driven EIM practice is critical for 
 delivering actionable insights in a fast and consistent manner. Such a tran
 sformation requires an equal part change along 3 dimensions:\n\n
 Automated implementation of AI solutions for existing processes\n
 Scaling of infrastructure to account for new solutions and number of users\
 n
 Engaging stakeholders to enable a cultural change to adopt new solutions\n\
 nThese three dimensions provide a primitive maturity model for the EIM prac
 tice and must mature at the same rate for a successful transformation. The 
 overall maturity or AI capability of any EIM practice is limited to the low
 est matured of these dimensions. For example, you may have the best GPU arc
 hitecture running the most sophisticated deep-learning algorithm to automat
 e a process, say data ingestion. However, your EIM onboarding practice is n
 ot going to be transformed until the stakeholders involved in this process 
 transition to using the automated solution. The same can be said regarding 
 process transformation. The enterprise might have a well-trained and motiva
 ted set of knowledge workers, armed with expertise about the latest techniq
 ues in data science and analytics. But unless you have the correct infrastr
 ucture it is not possible to scale out to an enterprise-wide transformation
 .\nIn this talk, we present details on how we measure these dimensions and 
 apply it towards the transformation of our EIM practice at IBM. We will be 
 sharing our thoughts and experiences regarding specific initiatives to help
  drive the maturity along each of these dimensions.\n
DTSTART:20201022T083000
SUMMARY:What Drives a Successful Transformation of EIM Into an AI-driven Pr
 actice?
DTEND:20201022T091959
LOCATION: See Description
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