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Determining AI Maturity for Your Organization

In: AI and the Boardroom

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  • Rohan Sharma

Abstract

AI maturity refers to an organization’s progress in effectively deploying AI, measured through increased capabilities and ROI. This chapter introduces a maturity model that defines seven levels of AI sophistication—from foundational data preparation to advanced multiagent systems. Each level builds upon the previous, enhancing AI’s impact and aligning it with strategic business goals. At the core of AI maturity is responsible AI practice, emphasizing ethical deployment, data privacy, and compliance. Achieving higher maturity levels requires investments in data infrastructure, fostering crossfunctional collaboration, and adopting a phased approach that balances innovation with responsibility. Key takeaway: Advancing through the AI maturity levels can drive significant business value, but it requires deliberate investments, responsible practices, and strategic leadership to succeed. Is your organization prepared to navigate and lead in this journey of AI maturity?

Suggested Citation

  • Rohan Sharma, 2024. "Determining AI Maturity for Your Organization," Springer Books, in: AI and the Boardroom, chapter 0, pages 95-104, Springer.
    • Handle: RePEc:spr:sprchp:979-8-8688-0796-1_8
    DOI: 10.1007/979-8-8688-0796-1_8
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