J. Howard Creekmore Professor of Finance and Professor of Economics
Finance Area Coordinator
Ph.D. Area Advisor – Finance
Finance Area Coordinator
Ph.D. Area Advisor – Finance
Making Data-Driven Decisions with Agentic AI
Upcoming Dates and Tuition:
Time: 11:30 am to 1:00 pm (Live Online)
Tuition: $1,950 - Included in the tuition price, you will be given cloud-based access to Claude Code and Python for the duration of the course.
Fall Cohort
Monday, August 3, 2026
Wednesday, August 5, 2026
Monday, August 10, 2026
Wednesday, August 12, 2026
Monday, August 17, 2026
Wednesday, August 19, 2026
Monday, August 24, 2026
Wednesday, August 26, 2026
This program will be delivered synchronously (LIVE) online over Zoom on each date. Each session is 90 minutes and includes instruction, demos, hands-on exercises, and group discussion.
Overview
AI agents that understand plain English, query your data, and deliver answers instantly are transforming how organizations make decisions. This eight-session course gives you hands-on experience building and using these tools — no coding background required.
You’ll use AI to wrangle data, generate charts and reports, solve optimization problems, and automate workflows. You’ll learn how to build custom AI agents that connect to databases and documents, how to secure them for enterprise use, and how to develop an implementation plan for your organization.
The AI Lab provides each participant with cloud-based access to Claude Code so you can work with AI tools without installing software or subscribing to an AI provider.
Interested in Executive Education?
Program Highlights
- Entirely hands-on sessions with exercises with real datasets
- Covers the full stack from ad-hoc analysis to production-ready AI systems
- Includes database skills, API calls, web apps, reporting pipelines and document AI
- Flexible synchronous online structure: enables participation from anywhere
Who Should Attend
- Executives and managers responsible for data-driven decisions
- Finance, operations and strategy professionals
- Business analysts and business intelligence (BI) teams exploring AI transformation
- IT leaders evaluating AI agent deployment
Expected Outcomes
After the program, you will be able to:
- Analyze data and produce reports using AI agents, even with no prior coding experience.
- Connect AI to corporate databases so that anyone can query them in plain English.
- Build automated reporting pipelines from database to finished slide deck.
- Deploy document-based AI that answers questions from company policies and contracts with citations.
- Evaluate reliability, compliance and governance requirements for enterprise AI.
Program Schedule
Session A
Session B
Week 1
The AI Landscape
- The major models, what AI agents can create, and where to trust (or verify) their output
Data Wrangling
- Querying databases, merging and filtering data, generating charts and Excel workbooks
Week 2
Decision Making
- Optimization, resource allocation, and exploring tradeoffs between competing objectives
Automating Workflows
- Building AI skills for repeatable tasks and web apps that produce analysis on demand
Week 3
AI Security
- Enterprise data agreements, prompt injection, and data exfiltration defenses
Agents and Connectors
- Building agents that query databases, search documents, and connect to external services
Week 4
Special Topics
- Teaching AI your company’s documents, predictive modeling, and fine-tuning
Capstone
- Pitch your implementation plan and get peer feedback
Meet Your Professor
Rice Business Wisdom
Rice Business Wisdom is our online ideas magazine that features faculty research.
Investing | Peer-Reviewed Research
How does an IPO affect your community?
Based on research by Alexander Butler
Investing | Peer-Reviewed Research
Can A Few Details Transform Your Earnings Forecast?
Based on research by Professor Brian Rountree
Finance | Peer-Reviewed Research
How A Swath Of Midwestern Cornfields Explains The Effect Of Finance On Economic Growth
Based on research by Professor Alexander Butler
