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73 I L T A N E T . O R G content, and have a strong track record of data privacy, security, and responsible AI practices. • Employing comprehensive data handling processes, such as data acquisition and preprocessing, data augmentation to enrich and expand datasets, end-to-end data tracking and monitoring, data security and privacy by design, and adherence to responsible AI principles, ensuring data quality, integrity, and ethical practices. • Utilizing cloud computing platforms to democratize everyone's access to Gen AI technologies. For instance, AWS Bedrock provides a secure and streamlined environment to leverage rapidly evolving LLMs, facilitating quick adoption and saving operational management efforts, enabling the data scientist teams to focus on innovation experiments and delivery. Organizations planning to train or ground Gen AI models on internal data must have robust, mature data governance policies to implement Gen AI more quickly, leverage it more effectively, mitigate any possible risks, and maximize the return on their investment. The transformation of Gen AI has genuinely raised the bar for building a robust data platform and infrastructure to an unprecedented level. The investments made in strengthening data governance – including ensuring data quality, privacy, security, transparency, and explainability; leveraging data stewards as humans-in-the-loop; and using internal policies to guide responsible AI use – will enhance an organization's ability to successfully tap into AI's transformative capabilities and achieve their business objectives. ILTA MIN CHEN As VP and CTO of LexisNexis Global Platforms, Asia, Pacific, Min Chen is responsible for driving and delivering customer-centric legal innovations across the globe through artificial intelligence, data analytics, visualization, big data processing, cloud native solutions and other advanced tech- nologies. She leads 600+ engineers and product people in Asia, Pacific and US, with core teams in Shanghai, Raleigh and Gurgaon. FEATURES

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