Program Overview
AI is rapidly evolving from passive tools into autonomous systems capable of independently conducting research, monitoring companies, generating insights, and supporting investment decision-making. These systems — known as Agentic AI — function as AI research assistants that can perform multi-step workflows traditionally done by analysts. This workshop provides investment teams with a practical understanding of how agentic AI works, how leading investment firms are deploying AI research assistants, and how such systems can be applied across investment workflows. Participants will learn how AI agents can autonomously gather information, analyze companies, monitor developments, and generate actionable insights — while also gaining hands-on experience designing and simulating AI research assistants.
Features
- Understand agentic AI and how it works
- Understand how investment firms use AI research assistants
- Identify automation opportunities in research workflows
- Design AI research assistant workflows
- Evaluate implementation opportunities
Target audiences
- Investment Analysts
- Investment Associates
- Fund Managers
- Research Teams
- CIO Office
- Investment Leadership
Curriculum
- 6 Sections
- 33 Lessons
- 1 Day
- Introduction to Agentic AI and Autonomous SystemsBuild conceptual clarity on agentic AI and how autonomous AI differs from prompt-based tools.6
- 1.1Evolution from AI tools to autonomous AI agents
- 1.2What makes AI “agentic” — planning, reasoning, acting, and iterating
- 1.3Difference between chat-based AI vs autonomous agents
- 1.4Core components of AI agents: Memory, Tools, Planning capability, Decision logic, Examples of agentic workflows in investment firms
- 1.5Investment Use Cases: Autonomous company research, Continuous market monitoring and Automated analyst workflows
- 1.6Exercise: Mapping analyst workflows suitable for agent automation
- AI Research Assistants — Architecture and WorkflowUnderstand how AI research assistants operate and how they integrate into investment workflows.6
- 2.1What is an AI research assistant
- 2.2How investment firms are using AI research assistants today
- 2.3Typical research assistant workflow:
- 2.4Types of tasks AI research assistants can perform: Company research, Industry research, Competitor analysis, Earnings analysis and Risk identification
- 2.5Case Study: AI research assistant supporting investment thesis development
- 2.6Exercise: Designing a research assistant for company analysis
- Building Autonomous Monitoring WorkflowsUnderstand how AI agents continuously monitor companies and generate insights.6
- 3.1Continuous monitoring vs one-time research
- 3.2How AI agents track: Earnings releases, News, Industry developments, Competitor actions and Regulatory developments
- 3.3How AI agents detect signals and generate alerts
- 3.4Examples of automated monitoring systems used by funds
- 3.5Case Study: Autonomous monitoring of portfolio companies
- 3.6Exercise: Designing a monitoring agent
- Hands-On Simulation — AI Research Assistant in ActionProvide hands-on exposure to how AI research assistants operate.2
- Designing AI Agents for Investment WorkflowsHelp participants design practical AI assistants aligned with their workflows.6
- Implementation Considerations and Future OutlookHelp participants understand practical deployment considerations7
Instructor
