Ready Set Do

Got it. Let me draft this properly then.Landed at 3,019 characters. Here's the description:

Picture this: it's 2023, ChatGPT just dropped, every Fortune 500 suddenly needs an "AI strategy," and the job postings want 5 years of experience in a technology that's barely 18 months old. How does anyone actually get hired in that mess?

Sowmya Podila figured it out. She's now a Senior Data Scientist on Target's centralized Generative AI team — basically the internal startup that decides which AI use cases get built, killed, or scaled across the entire company. Before Target, she was deep in the chaos: interviewing at Google and other Fortune 500s during the wildest hiring wave applied AI has ever seen.

We pull back the curtain on what enterprise AI actually looks like from the inside. Not the LinkedIn version. The real one.

She walks through how she prepped for GenAI interviews when nobody on Earth had three years of GenAI experience, why she picked Target over Google (the answer is more interesting than you'd think), and what Fortune 500 hiring managers are actually screening for in 2026 once the hype settled.

Here's the part nobody tells you: knowing when NOT to use AI is the most valuable skill on her team right now. Every PM wants an LLM in their product. Most of those ideas should be a SQL query and a dashboard. Sowmya breaks down how her team plays gatekeeper — and why that judgment call is what gets you hired, promoted, and trusted with bigger budgets.

We also get into the agentic AI question everyone's dancing around. Can AI agents actually run a Fortune 500 company? (Spoiler: no, and the reasons are way less sexy than Twitter would have you believe — it's data plumbing, not model capability.) She talks through building a multi-agent simulator at Target, why company size completely changes the AI adoption playbook, and the messy reality of getting clean data out of systems built in 2008.

Then we go big picture. Utopian future vs. dystopian future. Will AI take your job? Sowmya gives an honest answer that doesn't pander in either direction, which is rare these days.

If you're trying to break into applied AI, data science, or ML engineering at a large company — or you're already in and trying to figure out what to bet your career on next — this one's for you. We cut through the noise so you know what actually matters vs. what's just LinkedIn theater.

Connect with Sowmya:LinkedIn: https://www.linkedin.com/in/sowmyapodila/

Podcast site: www.readysetdopodcast.com

Timestamps

00:00 - AI Implementation Landscape in Fortune 500 Companies04:21 - The Evolution of AI Strategies in Enterprises07:20 - Interview Insights: Navigating the AI Job Market10:19 - The Current Landscape of AI in Enterprises13:28 - Understanding the Role of AI in Business Decisions16:24 - The Future of AI Agents in Enterprises28:01 - Building a Multi-Agent Simulator31:15 - Challenges in AI Data Utilization33:33 - The Impact of Company Size on AI Adoption40:02 - The Future of AI: Utopian vs. Dystopian Views45:45 - The Importance of Content Creation in AI Awareness