> Markdown version of [/events/world-congress-2026-north-america/sessions/1400-ai-decision](https://www.wearedevelopers.com/events/world-congress-2026-north-america/sessions/1400-ai-decision). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Decision Observability: Enabling Transparency and Trust in Intelligent Systems - **Event:** World Congress 2026 North America ## Description Artificial Intelligence (AI) now drives decisions across enterprise operations, for autonomous systems—yet much of this decision-making remains a “black box.” AI Decision Observability is an emerging paradigm that transforms opaque model behavior into traceable, explainable, and auditable decision pathways. This session introduces a unified framework that combines AI Decision Observability with Decision Intelligence—linking how decisions are made, measured, and improved across human-AI systems. Building on our AI Decision Automation Framework, we explore the technical and organizational capabilities required to move from decision outputs to decision systems: continuous, observable pipelines where every inference, rule, and outcome can be traced back to its origin. We discuss key methodologies—comprehensive logging, data and model lineage tracing, model introspection, counterfactual and causal analysis—and how these integrate into enterprise observability stacks. The session also showcases tools and architectures that operationalize observability, alongside real-world case studies from regulated domains like finance, healthcare, and autonomous mobility. We’ll conclude with a forward-looking view on how Decision Observability fuels Decision Intelligence—enabling enterprises to build trusted, adaptive, and compliant AI ecosystems where decisions are not just made but understood, improved, and governed. Key Takeaways: How to architect AI systems for full decision traceability and governance Integrating Decision Intelligence with AI Decision Observability for continuous learning Practical frameworks for scaling decision transparency and automation across the enterprise ## Speakers ### [Amjad Shaikh](https://www.wearedevelopers.com/@amjad-shaikh) VP, Platform & AI ### [Soumil Mandal](https://www.wearedevelopers.com/@soumil-mandal) Sr. Machine Learning Engineer, ServiceNow ## Related talks at this congress - [Closing the Visibility Gap: Lessons from Safety Critical Agentic Systems](https://www.wearedevelopers.com/events/world-congress-2026-north-america/sessions/1408-closing-the) — Vivek Pandit - [Beyond the Code: Human-AI Synergies in Product Development](https://www.wearedevelopers.com/events/world-congress-2026-north-america/sessions/1734-beyond-the-code) — Ajita Kanchivakam Ananth - [Who Tests the AI? Building Trustworthy AI Systems at Enterprise Scale](https://www.wearedevelopers.com/events/world-congress-2026-north-america/sessions/1693-who-tests-the-ai) — Him Raj Singh - [Reinventing Testing Practices in the AI Era](https://www.wearedevelopers.com/events/world-congress-2026-north-america/sessions/1724-reinventing-testing) — Eric Deandrea ## Watch remotely Can’t make it to San José? Watch this session live with Pro. You also get: - All full videos, bookmarks, and playlists - World Congress livestreams [See pricing](https://www.wearedevelopers.com/pricing) ## Links - [Get tickets](https://www.wearedevelopers.com/world-congress-north-america/tickets)