As artificial intelligence (AI) continues to reshape how organizations operate, the key to successful adoption lies not just in the technology itself, but in how teams thoughtfully integrate AI into their existing workflows and new products. We had the chance to chat with Emleen Martin, a Manager of Content Operations in Manila to explore her team’s AI journey, from building foundational capabilities to implementing practical solutions that enhance their content acquisition processes.
Q: Can you tell us about your role and how your team fits into Thomson Reuters’ broader mission?
A: I’m a Manager in Content Operations in the Manila office. My team specializes in content acquisition: identifying, validating, and delivering the legal and regulatory materials that keep our products comprehensive and current. While our core expertise is content, we are deliberately building capability in AI. We’re developing effective prompting skills, conducting focused experiments, and integrating practical AI support into day-to-day tasks. This work aligns with Thomson Reuters’ AI strategy by applying responsible, human-centered tools to enhance quality and consistency for our customers.
Q: What enables your team to successfully experiment with AI while maintaining quality standards?
A: Thomson Reuters’ culture is crucial to our progress. Leaders encourage measured experimentation with clear guardrails, fostering learning while maintaining rigorous standards. We benefit from formal training, communities of practice, and mentorship from technology partners who share guidance and lessons learned. This support allows a content-led team to adopt AI in a disciplined manner, without compromising editorial judgment or customer trust.
Q: What specific AI implementations have been most effective in your daily operations?
A: Our most effective changes have been simple and targeted. For example, we’ve piloted prompts that facilitate structured selection of documents that are valid and substantive for acquisition. We’ve also implemented AI solutions that replace manual effort in organizing and preparing content for downstream processes. My responsibilities include defining the problem, setting practical guardrails, and ensuring that human review remains central to decision-making. The focus is on building reliable steps that reduce friction for users and strengthen downstream quality for customers.
Q: How do you measure the success of these AI implementations?
A: The impact appears in operational metrics and feedback from stakeholders. We’ve shortened certain repetitive steps, which aggregates to meaningful time savings. Users report fewer interruptions and more capacity for higher-value tasks. We evaluate success using straightforward indicators—turnaround time, error rates, and partner feedback—and we retain only those approaches that consistently improve these measures.
Q: Can you describe the internal AI Day event you organized for the office?
A: In May, I led the first internal AI Day in our Manila office. The event highlighted internal success stories and live demonstrations, followed by workshops on Responsible AI, Copilot and Power Platform, and meta prompting. We had collaborative sessions such as Team AI Journeys and an hour to focus on our internal AI sandbox. These sessions promoted knowledge sharing and cross-functional engagement. We also included engaging activities like a “Spot the AI” challenge, a word search, an AI ethics wall for perspectives on responsible use, and a Freedom Wall for personal accounts of AI’s impact. We hosted an AI Learning Café as well, offering a quiet venue for TED Talks and curated reading materials. The feedback on the event was overwhelmingly positive, indicating a strong desire to repeat it soon.
Thank you to Emleen for sharing your experience with us. If you are interested in learning more about the Content Operations team or our open roles in Manila, you can learn more here.
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