Agentic AI doesn't have an Intelligence problem, it has a Governance problem !!

Hybrid event: In-person, Zoom and YouTube If you want to join remotely, you can submit questions via Zoom Q&A. The Zoom link: https://acm-org.zoom.us/j/93780208499?pwd=5DTkBAYvaPehTCh7CTcfmKL415IVhF.1 Join via YouTube: https://youtube.com/live/sVNwIuKDNF8 AGENDA 6:30 Door opens, food and networking (we invite honor system contributions) 7:00 SFBayACM upcoming events, introduce the speaker 7:15 speaker presentation starts 8:15 - 8:30 finish, depending on Q&A Join SF Bay ACM Chapter for an insightful discussion on: Talk Description: As enterprises race to deploy autonomous AI agents, much of the industry conversation remains focused on model capabilities: reasoning, planning, tool use, and autonomy. Yet the greatest barrier to successful adoption may not be intelligence at all. It is governance. Unlike traditional AI systems that primarily generate recommendations, agentic systems execute actions across interconnected business processes, data platforms, and operational workflows. In such environments, failures rarely originate from model limitations alone. They emerge from hidden dependencies, inconsistent data, unclear ownership, inadequate observability, and the absence of effective operational controls. Speaker bio: Sayantan Ghosh is a Senior Engineering Manager at LinkedIn, where he runs the feed data platform serving billion+ members on LinkedIn Feed. He has previously built data and AI platforms at Meta, Uber, and eBay. He is an IEEE Senior Member, holds a granted U.S. patent (US 9,870,355 B2), and is an invited speaker at various international venues like Big Data Europe, Big Data Canada, DataCon LA. He is a manuscript reviewer in leading Q1 journals IEEE TNNLS, ACM TKDD, IEEE TCDS, Elsevier Neural Networks, etc. Sayantan has mentored and grown several tech professionals across his decade long career at the most cutting edge companies in Silicon valley. LinkedIn:…