How Enterprises Scale AI: Data, Governance, and Trust скачать в хорошем качестве

How Enterprises Scale AI: Data, Governance, and Trust

Scaling enterprise AI is hard. This panel breaks down the real bottlenecks and playbooks to deploy AI in production across finance and healthcare. You’ll hear what actually works beyond proofs of concept. Moderator Gabriela de Queiroz (F02 Labs) leads a grounded discussion with David Hefter (BlackRock) and Anand Vallamsetla (Resilience AI) on moving from pilots to production, building trust, and getting governance right. If you’re shipping AI inside a regulated org, this is your shortcut to fewer surprises and better outcomes. 🔥 Key Highlights: 🔹 Adoption hurdle: why chatbots stall and where agents change behavior at work 🔹 The 80/20 trap: models shine in pilots, break on edge cases in production 🔹 Data → information → insight: organizing unstructured text to unlock value 🔹 Synthetic data: when it’s essential, where bias creeps in, and model collapse risks 🔹 Governance that helps, not slows: legal, risk, infosec as a visibility layer 🔹 HIPAA-by-design: de-identification, access controls, continuous monitoring 🔹 Production readiness: evals, guardrails, use-case risk tiers, and ongoing tests 🔹 Trust building: explainability plus human-in-the-loop for clinical safety 👥 Speakers: Gabriela de Queiroz:   / gabrieladequeiroz   David Hefter:   / david-hefter-13530378   Anand Vallamsetla:   / thewhyman   ⏱️ Timestamps 00:00 - Intro: Why most AI pilots fail to scale 01:28 - Intros: Resilience AI and BlackRock use cases 02:53 - Behavior change: chatbots vs agents in the enterprise 03:46 - The 80/20 problem: pilots vs real-world edge cases 04:57 - Data bottlenecks: from siloed data to useful information 06:42 - Synthetic data: where it helps and what to watch 10:28 - Regulated contexts: GDPR, CCPA, HIPAA in practice 11:08 - Governance that accelerates, not blocks 13:14 - HIPAA-by-design and continuous monitoring 15:28 - Deployment readiness: evals, guardrails, risk tiers 18:03 - Building trust: explainability and human-in-the-loop 20:41 - Strategy: align AI with business goals and ROI 23:23 - Buy vs build and staying on the cutting edge 26:20 - How startups stand out: talent, customers, domain expertise 30:03 - DevRel matters: driving adoption with developers 30:23 - Trends to watch: agents, vibe coding, personalized health 32:13 - Closing 🔗 Helpful Resources: – Step SF: https://sf.stepconference.com 👉 If you enjoyed the discussion, be sure to like the video, share your favorite insights in the comments, and subscribe to stay updated on our latest talks and demos! 🔗 Follow us for more: – LinkedIn (Dmytro):   / spodarets   – LinkedIn (Data Phoenix):   / data-phoenix   – YouTube (Events):    / dataphoenixevents   – YouTube (Dmytro):    / @dmytrospodarets   – Twitter/X: https://x.com/Data_Phoenix – Telegram: https://t.me/DataPhoenix – Facebook:   / dataphoenix.info   – Website: https://dataphoenix.info/