OpenAI Agentic Vision - From AI Pilots to Enterprise Value
Oct 27, 2026 · Time to be announced
Enterprises are rapidly moving from generative AI experimentation to a new phase of transformation: agentic AI systems that can reason, take action, and complete multi-step workflows across business tools, data, and teams. Yet many organizations still struggle to convert AI pilots into measurable business value because of fragmented data, siloed systems, limited production know-how, and insufficient governance. This session will help attendees understand how enterprises can bridge the gap between frontier model capabilities and scalable deployment. We will examine the evolution from conversational AI to reasoning systems and agentic workflows, then explore practical patterns for building agents that operate across enterprise surfaces such as productivity tools, developer environments, browsers, desktops, APIs, and customer-facing products. Attendees will learn how to identify high-value agentic use cases, design single-agent and multi-agent architectures, ground agents in enterprise context, apply evaluations and guardrails, and deploy agents with appropriate permissions, monitoring, and governance. The session will also cover examples across industries including financial services, telecommunications, retail, healthcare, software engineering, and enterprise operations. Practitioners will leave with an understanding for moving beyond isolated AI pilots toward governed, reusable, and scalable agentic systems that improve workforce productivity, automate operations, and power AI-native products.
Session status: scheduled
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Speakers and their event affiliations
- Shikhar Kwatra
Affiliation at this event: OpenAI
Parent event
Hybrid · Hyatt Regency San Francisco Airport, Burlingame, California, United States
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Companies participating in the parent event
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- Daily · Speaker company Source
- Data Driven Intuition · Speaker company Source
- Datasaur · Speaker company Source
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- Daytona · Speaker company Source
- eBay · Speaker company Source
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