Lab for AI-Agents in Business and Economics
Mission
Our mission is to pioneer AI-driven solutions for business challenges by developing multi-agent systems and domain-specific AI architectures, while guiding organizations through ethical, scalable, and transformative AI adoption.
Core Objectives
To develop platforms for AI agents and multi-agent architecture for business, management and AI-transformation of organizations
To study and design AI agents for specific business applications with deep domain knowledge
To study and understand the economic impact of AI transformation on economic behavior of human, business and organizations
📚 Major Projects
Econometric AI
We develop an “Econometrics AI Agent” which exhibits outstanding performance in planning econometric tasks strategically, generating and executing code, employing error-based reflection for improved robustness, and allowing iterative refinement through multi-round conversations. It establishes a testbed for exploring AI’s impact on social science research and enables cost-effective integration of domain expertise, making advanced econometric methods accessible to users with minimal coding skills.
A chat based agent for explaining and suggesting econometric method and identification strategy.
An RAG based agent with recommendation ability build on theoretical and applied econometrics papers published at top journals along with datasets.
A latex copilot writer agent that helps thesis writers with citations and references, mathematical formulas, table compiling, etc., in applied econometrics.
LangGraph Agent Rollback System
Explore a live, sandboxed demo of conversation rollback and branching. Create checkpoints, branch timelines, and see how tool calls auto-checkpoint. Use this to understand how AI agents can safely explore alternatives while preserving original state.
Interactive Demo
🌳 Session Branch Tree
⭐️ Key Features
💻 Code Example
from src.agents.rollback_agent import RollbackAgent
from langchain_openai import ChatOpenAI
# Create agent with rollback capabilities
agent = RollbackAgent(
external_session_id=session_id,
model=ChatOpenAI(model="gpt-4"),
tools=[calculate_sum, fetch_data, save_to_db],
auto_checkpoint=True # Auto-save after tools!
)
# Have a conversation
response = agent.run("Calculate 42 + 58")
# Auto-checkpoint created after tool use!
# Create manual checkpoint
checkpoint = agent.create_checkpoint_tool("Important State")
# Continue conversation
response = agent.run("Now multiply by 2")
# Rollback when needed - creates new branch!
new_branch = RollbackAgent.from_checkpoint(checkpoint_id)
# Original timeline preserved, new branch active
response = new_branch.run("Let's try division instead")Research Labs.
Deloitte-HKU Lab for Organizational
Transformation
The success of organizations depends on its ability to attract the right people, motivate effective action, and coordinate efforts. Artificial intelligence is transforming all three of these areas, requiring organizations to adapt their structures for the new challenges and opportunities.
Our lab focuses on guiding this essential transformation. Our work identifies effective organizational response and examine their interaction with markets, norms, and institutions. Through research and collaboration with industry practitioners, we assess the current state of AI adoption in firms, identify common pitfalls, and develop frameworks that help leaders structure and address these critical challenges.
Lab for AI-Agents in Business and Economics
Our mission is to pioneer AI-driven solutions for business challenges by developing multi-agent systems and domain-specific AI architectures, while guiding organizations through ethical, scalable, and transformative AI adoption. We focus on developing platforms for AI agents and multi-agent architecture for business and management, designing AI agents for specific business applications with deep domain knowledge, and studying the economic impact of AI transformation on human behavior, business and organizations.
AI Implementation (AI2) Lab
The AI Implementation (AI2) Lab is dedicated to turning AI and business research into real-world AI adoption. We collaborate with organizations to identify frictions, develop deployment strategies, and measure impact of AI implementation. Our work focuses on helping firms adopt and scale AI, designing business models for the AI era, and incubating AI-related innovations through experimentation and prototyping.
Lab for the Future of Work
and Well-being
Our mission is to advance understanding of how generative AI is transforming labor markets, leisure, and overall wellbeing, with a particular focus on China. We are committed to conducting rigorous, data-driven, and causally robust research to generate actionable insights. Distinctively, our people-centered approach places human wellbeing at the core of our analysis, going beyond productivity and profitability to explore how technological change can foster better jobs and lives.
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