Webinar: 'Why Enterprise AI Fails to Reach Production - Siemens Expert Talk'

Enterprise AI Investments Are Expanding While large companies are increasingly expanding their AI investments, many cases fail to progress beyond Proof of Concept (PoC) into full production, resulting in inadequate business outcomes. Although expectations for AI are high, challenges remain in making it a standard part of business operations and rolling it out company-wide. Converting these investments into production deployment and tangible management results has become a critical priority for many organizations.

Fragmented Data Makes Business Implementation Difficult One reason AI utilization stalls is that data remains siloed across different departments and systems, preventing the cross-functional use of essential information. Compounded by a risk-averse frontline environment and a lack of trust and AI literacy, it becomes difficult to sustain the use of AI in the field, even if models are successfully developed.

The 3-Layer Foundation for Leveraging AI in Management: 'Data Integration', 'Dev/Ops', and 'App Implementation' This seminar, the first installment of the 'Siemens Expert Talk', is an introductory session that outlines the basic structures necessary to leverage AI for business management. Using Siemens' RapidMiner and Mendix as examples, it explains the comprehensive approach of how to integrate fragmented data, build a sustainable AI development and operations lifecycle, and implement these solutions directly into frontline business processes. To ensure AI moves beyond mere PoC or partial use and connects to real business value in production, we will introduce—alongside case studies—how the three layers of 'Data Integration', 'Dev/Ops', and 'App Implementation' interlock to bridge the gap between AI and daily operations.

Recommended For - Corporate planning and DX department leaders in large enterprises looking to leverage AI for management. - IT department professionals considering the foundational infrastructure needed to support AI production environments, addressing fragmented and unstructured data. - Business unit leaders aiming to move beyond PoC and connect AI to actual business implementation and frontline adoption.

Host / Co-host Siemens K.K.

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