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79: “Good enough to start, governed enough to scale," says Rehan Shah, AWS

Data: Heaven or Hell? (Adastra Podcast)

Listen to Adastra’s podcast dedicated to the latest trends in data management, AI, and analytics.

This engaging podcast series showcases the visionaries reshaping the tech landscape. Featuring strategic leaders and boardroom heroes who persuade decision-makers to back new technologies, each episode dives into stories of ambition, innovation, and collaboration.

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<div><p>Rehan Shah, General Manager and Head of Channel and Partner Sales for US Greenfield at AWS, explains how the right mix of AI tools, trustworthy data, and strong controls turns early AI trials into real business results. He shows how AWS provides access to top models, better value, responsible AI practices, and secure ways to connect your systems. Examples include instant insights from manufacturing data and Breakthru Beverage moving hundreds of servers, plus quick AI helpers like a Sales Coach and a Legal Assistant. He also shares how to keep costs in check and set up a company-wide AI program with clear budgets and accountability. </p></div><ul>
<li>What does it take to move from quick wins with Amazon Q to custom agents on Bedrock that scale across the enterprise?  </li>
<li>When is “good enough” data enough to start, and how can AI assistants surface gaps while improving data quality over time?  </li>
<li>Which operating model and risk-based guardrails help leaders control cost and compliance while accelerating adoption? </li>
</ul>

<p></p><p>Rehan Shah, General Manager and Head of Channel and Partner Sales for US Greenfield at AWS, explains how the right mix of AI tools, trustworthy data, and strong controls turns early AI trials into real business results. He shows how AWS provides access to top models, better value, responsible AI practices, and secure ways to connect your systems. Examples include instant insights from manufacturing data and Breakthru Beverage moving hundreds of servers, plus quick AI helpers like a Sales Coach and a Legal Assistant. He also shares how to keep costs in check and set up a company-wide AI program with clear budgets and accountability. </p><ul>
<li>What does it take to move from quick wins with Amazon Q to custom agents on Bedrock that scale across the enterprise?  </li>
<li>When is “good enough” data enough to start, and how can AI assistants surface gaps while improving data quality over time?  </li>
<li>Which operating model and risk-based guardrails help leaders control cost and compliance while accelerating adoption? </li>
</ul>

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79: “Good enough to start, governed enough to scale," says Rehan Shah, AWS

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