 AI Operating ModelRohan Sharma Chapter Chapter 7 in AI and the Boardroom, 2024, pp 77-94 from Springer Abstract: Abstract Creating an effective operating model for integrating data and AI is a foundational step for achieving sustained business outcomes. The journey begins by aligning data and AI capabilities with prioritized business use cases, ensuring the right focus on impactful, low-risk initiatives. To do this, leadership must establish an AI steering group and ensure cross-functional collaboration across data, IT, and business teams. A successful AI operating model involves agile delivery, clear accountability, and close cooperation between data and business functions. This allows teams to adapt quickly, address real business needs, and experiment effectively. Establishing a robust governance structure is also critical to ensure ethical, secure, and compliant AI deployment. This chapter explores how an AI operating model framework can organize AI activities across an enterprise, from data providers to service delivery management. With welldefined roles and responsibilities, ongoing collaboration, and a focus on ethical AI practices, organizations can build a solid foundation for leveraging AI as a strategic differentiator. Are you ready to elevate your AI initiatives from mere experiments to driving substantial business value? Date: 2024 There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:979-8-8688-0796-1_7 Ordering information: This item can be ordered from DOI: 10.1007/979-8-8688-0796-1_7 Access Statistics for this chapter More chapters in Springer Books from Springer |
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