Gagan Preet Singh
Principal AI Architect at HP | AI Agents & Enterprise Financial Systems
Houston, Texas, United States
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Gagan Preet Singh is a Principal AI Architect at HP Inc., specializing in the engineering of automated AI workflows and agent-based systems for enterprise finance. With over 12 years of experience at the intersection of Data Science, Finance, and Computational Physics, Gagan designs and deploys autonomous decision-support engines that integrate large-scale data processing with specialized AI agents.
Previously, Gagan led global initiatives to standardize machine learning development, modular architecture, and deployment hygiene across international data science teams. His work focuses on transforming unstructured or noisy financial data into structured, actionable insights through the development of robust, auditable AI frameworks. An active member of the IEEE Computational Intelligence Society, Gagan holds an MS in Physics from IISER Mohali, with a research background in computational simulation and N-body modeling.
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From Data to Decisions: AI for the Backoffice
This session focuses on practical finance applications: turning messy data into AI-ready formats, building analysis tools for problems previously 'too expensive to explore,' and automating the manual work that finance teams have normalized.
Outcome: Identification of high-ROI AI opportunities in back-office operations
Takeaway: Two or three specific back-office AI applications to evaluate for your organization
Key Discussion Points:
• Why back-office AI delivers better ROI than front-office investments
• The hidden cost of manual work finance teams have normalized
• Data readiness: turning messy data into AI-ready formats
• Use case: automating data extraction and categorization
• Use case: exception-based processing and anomaly detection
• Use case: analysis tools for previously unexplored problems
• Building vs. buying: when to use off-the-shelf vs. custom solutions
• Change management: helping teams adopt AI-assisted workflows
• Measuring success: KPIs for back-office AI initiatives
• Case study: real-world back-office transformation results
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