Organizations can face many challenges in operationalizing D&A and AI strategies. In this session, we discuss how to capitalize on value-based opportunities, engage with stakeholders and get to what matters.
talk-data.com
Speaker
Donna Medeiros
3
talks
Donna Medeiros is a Senior Director with Gartner's Chief Data Officer Research Team. She covers C-suite leadership and utilization of data and analytics needed for digital transformation and the strategies, policies and processes to empower organizations and agencies to be successful in driving change. She helps organizations become data-driven by providing advice on establishing data and analytics strategy, data and AI literacy and change management practices. She has led global research, publications and large-scale implementations on data management and analytics, stood up emergency operating centers for disease outbreaks and advised organizations on best practices and innovation in data and analytics technologies.
Ms. Medeiros has consulted to governments, multilaterals and companies in the application of innovative and advanced technologies to transform systems including Integrated Architectures, Interoperability, Data Science including Advanced Analytics and Artificial Intelligence.
Ms. Medeiros' career spans 35 years with extensive international experience and is a recognized Data Strategists, Architect and Health Data and Analytics expert for clients in North America, Asia, the Pacific, Latin and South America, Africa and the Middle East. For the past decade, she has focused on working with governments and private sector partners to establish national, state and organizational digital investments in data and IT, primarily in health, e-government and at universities. She has spent extended periods of time living in countries co-creating data architectures, policies and advising on the application of innovative technologies by using an agile high impact strategic approach.
Bio from: gartner-data-analytics-apac-2025
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Implement your target AI governance operating model by mapping governance pillars to key AI components and differentiating AI capabilities. This model should connect with other governance bodies and extend existing governance models to AI-specific considerations of trust, transparency and diversity.
Implementing AI governance can be challenging, navigating this in the public sector is particularly so with risk focus often overshadowing value and benefits. This roundtable will explore practices in overcoming challenges to achieve success in AI Governance with specific focus on public sector aspects including data, regulations and workforce.