The transformation of traditional EIM to an AI-driven practice requires an equal part change alo ng three 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 p ractice and must mature at the same rate for a successful transformation. T he overall maturity or AI capability of any EIM practice is limited to the lowest matured of these dimensions. For example, you may have the best GPU architecture running the most sophisticated deep-learning algorithm to auto mate a process, say data ingestion. However, your EIM onboarding practice i s not going to be transformed until the stakeholders involved in this proce ss transition to using the automated solution. The same can be said regardi ng process transformation. The enterprise might have a well-trained and mot ivated set of knowledge workers, armed with the expertise about latest tech niques in data science and analytics. The development team may also have aw esome proof-of-concept tools and applications for EIM. But unless you have the correct infrastructure, it is not possible to scale out to an enterpris e-wide transformation.
\nIn this talk, we present details on how we m easure 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 dimensi ons.
\n DTSTART:20200325T120000 SUMMARY:What Drives a Successful Transformation of EIM Into an AI-Driven Pr actice? DTEND:20200325T125959 LOCATION: See Description END:VEVENT END:VCALENDAR