Vaishnavi
Gudur
Senior Software Engineer at Microsoft
"AI for Visibility: How Women in Tech Can Leverage AI to Accelerate Recognition and Global Leadership"
"AI for Visibility: How Women in Tech Can Leverage AI to Accelerate Recognition and Global Leadership"
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Session: AI for Visibility: How Women in Tech Can Leverage AI to Accelerate Recognition and Global Leadership
In an era where AI is reshaping industries and redefining leadership, standing out requires more than technical expertise—it requires strategic visibility and influence. In this TED-style talk, I share how women leaders can harness AI not just as a tool for automation, but as a powerful accelerator for recognition, leadership, and global impact.Drawing on my own journey of achieving extraordinary recognition during one of the most competitive times in history, I’ll reveal a 3-part framework—Visibility, Validation, and Value—that blends AI-driven insights with proven leadership strategies. From using AI to amplify thought leadership, to leveraging intelligent tools for storytelling and decision-making, I will show how to transform AI into an ally for building credibility in the C-Suite and beyond.
Attendees will walk away with actionable strategies to elevate their presence, position themselves as innovators, and lead with confidence in a future where AI is not just shaping technology—it is shaping who gets recognized as extraordinary
Key Takeaways
- Learn how to apply a 3-part framework (Visibility, Validation, Value) powered by AI to accelerate leadership recognition.
- Discover practical ways AI can amplify thought leadership, storytelling, and executive presence.
- Gain insights into how AI can help leaders make data-backed decisions while enhancing credibility.
- Understand how to leverage AI tools to stand out in stricter, more competitive environments.
- Walk away with actionable strategies to transform AI from a technical tool into a leadership accelerator.
Bio
Vaishnavi Gudur is a Senior Software Engineer at Microsoft specializing in AI-first systems, security, and compliance. She builds secure-by-default platforms that let teams ship AI quickly while staying audit-ready—spanning policy-as-code guardrails, data protection, model/prompt risk controls, and telemetry for real-time detection across cloud and edge. Her thought leadership and research on ethical AI and governance appear in IEEE and Springer venues; she also contributes as a reviewer and judge in the AI ecosystem. Current interests include Explainable AI and next-gen performance tooling that turns opaque pipelines into transparent, measurable workflows. On stage, she shares practical patterns—checklists, reference architectures, and developer-friendly workflows—for secure AI integration and developer velocity. Outside work, she’s a photographer, nutrition and travel enthusiast, and mindfulness practitioner, bringing a human-centric lens to safety and design.