AI in Business Conference
Human-in-the-Loop AI: Enabling Responsible and Impactful Human-AI Collaboration
Columbus, OH | October 2-3, 2025
As businesses increasingly adopt artificial intelligence, the need for effective human-AI collaboration becomes essential. The Fisher College of Business announces its inaugural AI in Business Conference examining Human-in-the-Loop (HITL) AI systems featuring human oversight, ethical safeguards, and accountability. HITL AI goes beyond constraining algorithms; it emphasizes augmenting human capabilities and decision-making across different business domains. We aim to spark interdisciplinary dialogue on how these systems drive business value and shape the future of work.
Registration for the 2025 AI in Business Conference has closed.
If your abstract has been accepted, contact Erika Santolalla for registration information.
Conference highlights
- Sessions featuring cutting-edge academic research
- Academic keynotes
- Ample opportunities for networking and collaboration
- Best paper presentation competition
Featured speakers
Anindya Ghose
New York University, Leonard N. Stern School of Business
Anindya Ghose is the Heinz Riehl Chair Professor of Technology and Marketing at at New York University's Leonard N. Stern School of Business, where he holds a joint appointment in the Marketing and Technology, Operations, and Statistics departments. He is also the Director of the Masters of Business Analytics Program and a Leonard Stern Faculty Scholar with an MBA scholarship (the Ghose Scholarship) named after him.
He is the author of TAP: Unlocking The Mobile Economy, a double winner at the 2018 Axiom Business Book Awards, and THRIVE: Maximizing Well-Being in the Age of AI . His rapid promotion from assistant to full professor in 8.5 years is considered one of the fastest in global business school history.
Professor Ghose’s Ph.D. students have gone on to academic and industry leadership roles worldwide. He has published over 125 papers, delivered more than 325 talks globally, and received 29 best paper awards. His research spans digital platforms, mobile commerce, AI, data privacy, and digital marketing.
He is the youngest recipient of the INFORMS ISS Distinguished Fellow Award and has received the AIS Fellow Award, the INFORMS ISS President's Service Award, and the INFORMS ISS President's Service Award. He was named among the Top 40 Professors Under 40 Worldwide by Poets & Quants, a Thinkers50 nominee for Digital Thinking, and is in the top 1% of global researchers by Web of Science.
He has consulted for and collaborated with firms including Alibaba, Apple, Facebook, Google, Microsoft, Samsung, and Verizon. He serves on the board of Delhivery and advises startups and VC firms across the U.S., India, and Asia.
He has served as an expert witness in high-profile litigation involving the DOJ, FTC, Meta, Google, and Amazon. He is affiliated as a Scientific Expert with Compass Lexecon.
Outside academia, he is an avid high-altitude mountaineer, having climbed peaks across five continents.
Mary Strain
Amazon Web Services
Mary Strain leads strategy for artificial intelligence and machine learning in the US public sector at AWS. Mary began her career as a middle school teacher in the Bronx, NY. Since that time, she has held leadership roles in public sector technology organizations as a product lead, and vice president of business development. Mary has advised higher education, technology companies, state and local government on innovative policies and practices leveraging artificial intelligence and machine learning capabilities to advance access and efficiencies. As an advisor to The Education Design Studio at The University of Pennsylvania, The State of NJ AI Task Force and the California State University AI Workforce Acceleration Board. Mary has been on the leading edge of bringing innovative solutions to serve the public interest for two decades. Mary holds a BA from Fordham University and an MPA from The City University of New York
Attending the conference
The AI in Business Conference will take place October 2-3, 2025 in Pfahl Hall at The Ohio State University Fisher College of Business.
View the full conference schedule
Thursday, October 2, 2025
1 7:00 - 8:00
2 8:00 - 8:15
Provost of The Ohio State University
3 8:15 - 9:00
4 9:00 - 9:10
4 9:10 - 10:30
5 10:30 - 10:40
6 10:40 - 12:00
7 12:00 - 1:00
8 1:00 - 2:40
9 2:40 - 3:00
10 3:00 - 4:40
11 4:40 - 5:30
12
13 5:30 - 8:30
Friday, October 3, 2025
1 7:00 - 8:00
2 8:00 - 8:50
3 8:50 - 9:00
4 9:00 - 9:50
Speakers:
Will Burrus, Chief Product Officer at Expeed
Steve Bartos, Vice President at Worthington Steel
Susan White, Chief Data and Analytics Officer at OSU Wexner Medical Center
Moderator:
Michael Leiblein, Professor of Management, Fisher College of Business
9:50 - 10:00
6 10:00 - 11:00
7 11:00 - 11:10
8 11:10 - 12:10
12:10 - 1:00
Program Coordinators
- Christina Dressel is a third Public Policy and Management PhD student at the John Glenn College of Public Affairs. She is interested in integrating AI into qualitative methods for analyzing organizational language.
- Rang (Rae) Gong is a forth year Logistics PhD student who is studying AI-driven transformations in logistics and supply chains.
- Sunny Hasija is a 2025 graduate from Fisher College's Logistics PhD Program. His interest in AI is Algorithm Aversion in Supply Chain Management.
- Hanho Lee is a fifth year PhD student studying Organizational Behavior. He is interested in AI and psychological processes.
- Mohamed Megahed is a fourth-year PhD student in Operations Management at the Fisher College of Business. His research focuses on AI and human collaboration in operations, particularly systems design in healthcare and industrial contexts.
- Kris Shen is currently a fourth year Finance PhD student. His AI interest revolves around AI and asset pricing.
- Max (Chengzhao) Tu is a fourth year Quantitative Marketing PhD student. He interests in AI are in information extraction and the integration of LLM with traditional ML algorithms.
Search for conference presentations
9:10 AM – 10:30 AM
- A Human-in-the-Loop AI Agent for Meta-Analysis Coding
Hanyi Min* (University of Illinois UrbanaChampaign), Sohee Kim (University of Illinois Urbana-Champaign), Feng Guo (University of Tennessee at Chattanooga)
- Qualitative Coding with Hybrid AI and Human-in-the-Loop
Christina Dressel* (John Glenn College of Public Affairs, The Ohio State University), Megan LePere-Schloop (The Ohio State University), Lucia Gomez Teijeiro (Bern University of Applied Sciences and University of Geneva)
- AI-Assisted Triage of Patient Messages: A Clinically Calibrated Human–AI Framework for Healthcare Operations
Mohamed Megahed* (The Ohio State University), Nathan Craig (The Ohio State University), Aravind Chandrasekaran (The Ohio State University)
- Dual Applications of Large Language Models: Specialty Triage and Patient-Friendly Discharge Summaries,
Xiguang Liu* (University of Florida), Haocheng Ren (University of Michigan), Tianrun Pan (Hackensack Meridian School of Medicine), Tianhe Zhang (University of Wisconsin-Madison), Liangfei Qiu (University of Florida)
- From Copy-Paste to Cognitive Lift: A Design Theory for AI-Assisted Mastery
Lori Kendall* (The Ohio State University)
- Improving Student Engagement and Personalized Learning In Business Analytics with AI
John Draper* (The Ohio State University), Ismael Talke (The Ohio State University)
- Does Machine Learning Help Flights Depart on Time? The Value of Machine Learning Tools on Airlines’ Operational Performance
Rang Gong* (The Ohio State University), Xiang (Sean) Wan (The Ohio State University)
- Does Objective Service Quality Guarantee Subjective Service Quality? An AI Application of Facial Recognition on Flight On-Time Performance and Passenger Sentiment
Xiang (Sean) Wan* (Fisher College of Business), Hongshuang (Alice) Li (Fisher College of Business), Zenan Zhou (W. P. Carey School of Business)
- Information-Seeking from AI Chatbots: Tradeoff between Judgment and Misinformation Concerns under Stigma
Aravinda Garimella* (University of Illinois Urbana-Champaign), Behnaz Bojd (University of California, Irvine), Haonan Yin (University of California, Irvine)
- Leadership in the Loop: Business Roles in Responsible AI Innovation
Shixian Xie* (Carnegie Mellon University), John Zimmerman (Carnegie Mellon University), Motahhare Eslami (Carnegie Mellon University)
10:40 AM – 12:00 PM
- Generative Agent-Based Modeling for Logistics and Supply Chain Management Research
Vince Castillo* (The Ohio State University)
- Human-AI Congruence in Supplier Selection from Public Procurement Bids
Finnegan McKinley* (University of Arkansas), Anne Dohmen (Michigan State University), Vince Castillo (The Ohio State University)
- The Impact of Industrial AI Agent on B2B Procurement: Evidence from a Field Experiment
Ricky Tan* (China Europe International Business School), Shichen Zhang (Tianjin University), Ruyu Chen (Stanford University), Xiande Zhao (China Europe International Business School)
- Teaching Algorithms the Art of the Deal: Lessons from Reverse Auction Blunders
Piyush Shah* (Florida Gulf Coast University), Irita Mishra (University of Wisconsin-River Falls), Senali Amarasuriya (Middle Tennessee State University)
- Between Awe and Shame: The Emotional and Interpersonal Consequences of Workplace AI Use
Justin Woodall* (University of Georgia), Yihao Liu (University of Georgia), Szu-Han (Joanna) Lin (University of Georgia), Jack Ting-Ju Chiang (Peking University), Zheng Wang (Zhejiang University)
- Can an AI Be Sorry? Ameliorating the Human-AI Gap in Customer Service Apologies
Rasam Dorri* (University of California, Riverside), Rami Zwick (University of California, Riverside), Ye Li (University of California, Riverside)
- Emotional Agents: Human-AI Interaction and Emotional Diversity in Adversarial Prompt Engineering
Guohou Shan* (Northeastern University), Kofi Arhin (Lehigh University), Yi Tong (University of Florida), Michael Rivera (Lehigh University), Liangfei Qiu (University of Florida)
- If It's Easier, Why Do I Feel Worse? Impostor Thoughts Triggered By Generative AI Assistance
Hanho Lee* (The Ohio State University), Zixu Zhang (University of Arizona), Hun Whee Lee (The Ohio State University), Sarah P. Doyle (University of Arizona), Robert B. Lount, Jr. (The Ohio State University)
- Does Machine Learning Shift Job Requirements? Impacts on Entry-Level Opportunities
Yuanyang Liu* (University of Tennessee, Knoxville), Chuanren Liu (University of Tennessee), Tingliang Huang (University of Tennessee)
- Modeling the Interviewer: Leveraging LLMs to Uncover Personality Mismatch Effects in Interview Assessment
Rachit Kamdar* (University of Maryland), Balaji Padmanabhan (University of Maryland), Siva Viswanathan (University of Maryland)
- What Do Early-Stage Investors Ask? An LLM Analysis of Expert Calls
Victor Lyonnet (University of Michigan), Amin Shams* (The Ohio State University), Shaojun Zhang (The Ohio State University)
- A Framework for Interventions in Human-AI Collaboration
Paul Wynns* (UC San Diego), On Amir (UC San Diego)
1:00 PM – 2:40 PM
- The AI Management Paradox: How Algorithmic Performance Systems Drive Efficiency but Erode Consumer Trust
Qiaowen Guo* (Washington University in St. Louis), Xiang Hui (Washington University in St. Louis), Fuqiang Zhang (Washington University in St. Louis), Tianjuan Feng (Fudan University)
- Algorithm Aversion in Supplier Selection - The Role of Cognitive Style and Interface Design
Abhinav Hasija* (The Ohio State University), Aravind Chandrasekaran (Ohio State University), Terry Esper (Ohio State University), Thomas Goldsby (University of Tennessee), Walter Zinn (Ohio State University)
- Why Students Reject AI for Human Counselors in College Applications: A Field Experiment
Hemanshu Das* (Yale School of Management), Sofoklis Goulas, (Yale School of Management), Faidra Monachou (Yale School of Management)
- Breaking the Sound Barrier: Asymmetric Impacts of AI Dubbing on Multilingual Engagement on YouTube
Minjie Han* (University of Rochester), Mikhail Lysyakov (University of Rochester), Yang Gao (University of Illinois Urbana-Champaign)
- AI Self-preferencing in Algorithmic Hiring: Empirical Evidence and Insights
Jiannan Xu* (University of Maryland), Gujie Li (National University of Singapore), Jane Yi Jiang (Ohio State University)
- AI and the Extended Workday: Productivity, Contracting Efficiency, and Distribution of Rents
Junyoung Park* (Auburn University), Wei Jiang (Emory University), Rachel Xiao (Fordham University), Shen Zhang (Fordham University)
- Large Language Models in the Workplace: The Role of Social Class Background
Yao Yao* (University of Houston), Meng Li (University of Houston), Lai Wei (Boston College)
- When Age Helps or Hinders AI Use: A Goal Orientation and Appraisal Perspective
Hun Whee Lee* (The Ohio State University), Christopher Dishop (Auburn University), Nai-Wen Chi (National Sun Yat-Sen University), Yonghwan Lee (University of Seoul), Wu Wei (Wuhan University), Ke Michael Mai (China Europe International Business School)
- Work Design for AI Agents: Tool and Socio-Technical System Design for AI Performance
Cory Eisenhard* (Michigan State University), Frederick P. Morgeson (Michigan State University), Dhruv K. Toprani (Michigan State University)
- When Told by a Machine: Human Perception and Responses to AI-Generated Information and Misinformation
Lan Wu* (California State University, East Bay), Richard R. Klink (Loyola University Maryland), Jing-Wen Yang (California State University, East Bay)
- Artificial Intelligence, Opportunity, and Regulatory Uncertainty: Implications for Asset Pricing
Kris Shen* (The Ohio State University)
- Auditing in the Age of AI: Private Equity vs. the Public Interest
Rajib Doogar* (University of Washington Bothell), Sri Ramamoorti (University of Dayton), Cory A. Campbell (Indiana State University)
- Developing a Better Mousetrap: An Advanced Machine Learning Approach for Detecting Corporate Accounting Fraud in the Presence of Noisily Labeled Training Data
Waleed Muhanna* (Ohio State University)
- The Intelligence May Be Artificial, but the Story Must Be Human: Rethinking Audit Value, Ethical Pricing, and Client Perceptions in AI-Enhanced Professional Services
Kristina Harrison* (Indiana University), Sri Ramamoorti (University of Dayton), Cory Campbell (Indiana State University)
3:00 PM - 4:40 PM
- Improving Recycling Quality through AI & GreenNudges: Evidence from a Field Experiment
Erin McKie* (The Ohio State University), Nikhil Sharma (The Ohio State University), Sanghoon Cho (Texas Christian University), Aravind Chandrasekaran (The Ohio State University)
- Strategic Algorithmic Advice Taking
Tobias Rebholz* (Duke University), Maxwell Uphoff (University of Minnesota Twin Cities), Christian H. R. Bernges (University of Tübingen), Florian Scholten (University of Tübingen)
- When Influencers Delegate Replies: How Social AI Agents Shape User Engagement
Maggie Zhang* (University of Virginia, McIntire School of Commerce), Yang Gao (University of Illinois at Urbana-Champaign), Jingjing Li (University of Virginia), Steven L. Johnson (University of Virginia)
- The Adoption and Efficacy of Large Language Models: Evidence From Consumer Complaints in the Financial Industry
Minkyu Shin* (City University of Hong Kong), Jin Kim (Northeastern University), Jiwoong Shin (Yale School of Management)
- The Impact of AI in Operations and Supply Chain on Firm Productivity
Jafar Namdar (Michigan State University), Yuanyang Liu (The University of Tennessee, Knoxville), Nima Safaei* (The Ohio State University), Sachin Modi (University of Cincinnati)
- Accuracy Obsession: Humans Prioritize Immaterial AI Accuracy Over Their Own Compensation — Unless We Educate Them
Matthew DosSantos DiSorbo* (Harvard Business School), Kris Johnson Ferreira (Harvard Business School)
- Addressing Consumers’ Sensitive Attributes in Product Recommendations: An Explainable AI Recommendations System Approach
Piyush Anand* (Rice University)
- Backpropagating from Customer Value
Midam Kim* (ServiceNow), Fabio Casati (ServiceNow), Darrell Penta (ServiceNow), Delaney Kipple (ServiceNow), Catherine Martin (ServiceNow), Minyoung Kim (The Ohio State University), Di Yan (TU Delft)
- Cultural Differences in Receptivity to AI Branding
Archer Yue Pan* (Wayne State University), Manoj Thomas (Cornell University)
- Consumer Strategizing as Human-in-the-Loop: Gaming the Pricing Algorithm
Joshua Gerlick* (Case Western Reserve University)
- Deepfakes for Good: Empirical Analysis and AI Agentic Framework for Bias Mitigation
Yizhi Liu* (University of Maryland, College Park), Balaji Padmanabhan (University of Maryland, College Park), Siva Viswanathan (University of Maryland, College Park)
- From Slip to Spiral: Behavioral Implications of Boundary-Pushing AI-Generated Content for Platform Governance
Lei Wang* (Indiana University), Lu Huang (Penn State University), Ram Gopal (University of Warwick)
- Stress-Energy-Trust (SET): Constraints and Affordances for Ethical Artificial Intelligence Transformation in Management
Huan (Harry) Wang* (Siena University), Michael D. Johnson (University of Washington)
- AI-Powered Virtual Stress-Testing: A Data-Driven Framework for Strategic Resilience Investment in Power Grids
Mazin Al-Mahrouqi* (The Ohio State University), Abdollah Shafieezadeh (The Ohio State University), Jieun Hur (The Ohio State University)
Search for conference presentations
10:00 AM – 11:00 AM
- Scaling Human Capital with Artificial Intelligence: Codified Selves and Value Creation and Appropriation
Natarajan Balasubramanian* (Syracuse University), Prithwiraj Choudhury (London School of Economics), Mingtao Xu (Tsinghua University)
- Scalable Virtual Influencer Creation Using LLMs, VAEs, and Stable Diffusion Models: A Human-in-the-Loop Generative Framework
Yuan Lu* (The Ohio State University), Alice Li (The Ohio State University), Greg Allenby (The Ohio State University)
- Why the Best Machine May Not Be the Best: Incentivizing Human–Machine Collaboration
Xiaotong Guan* (The University of Texas at Dallas), Anyan Qi (The University of Texas at Dallas), Shouqiang Wang (The University of Texas at Dallas)
- LLM-Assisted Formalization Enables Deterministic Detection of Statutory Inconsistency in the Internal Revenue Code Steven Keith Platt* (Loyola University Chicago), Borchuluun Yadamsuren (Loyola University Chicago), Miguel Diaz (Loyola University Chicago)
- Reuniting Forcibly Separated Families Through Shared Memories
Huifeng Su* (Yale University), Lesley Meng (Yale School of Management), Edieal J. Pinker (Yale School of Management)
- The Impact of Responsible AI Management (RAIM) on Organizational and Market Performance
Christopher Yaluma* (The Ohio State University), Aravind Chandrasekaran (The Ohio State University), Dennis Hirsch (The Ohio State University), Rakesh Mallipeddi (The Ohio State University)
- Generative AI as an Equalizer: Enabling Entrepreneurs in Underrepresented Regions
Faisal Altalhi* (Kent State University) - Roundtable Discussion
- Rethinking Professional Ethics in Accounting for the Age of Agentic AI
Sridhar Ramamoorti* (University of Dayton), George Botic, Mark DeLong, William Miller, Michael Voinovich - Roundtable Discussion
- Can Generative AI Acquire Tacit Knowledge? Revisiting Strategic Assumptions in the Age of Large Language Models
Ezekiel Leo* (Grand Valley State University) - Roundtable Discussion
11:10 AM - 12:10 PM
- Collaborative Intelligence: Reconstructing the Invisible Consumer from Fragmented Survey Data
Alice Li* (The Ohio State University), Jiyeon Hong (Seoul National University), Qing Liu (Northeastern University)
- AI in the Pen: How Real-Time AI Writing Guidance Shapes Online Reviews
Zaiyan Wei* (Purdue University), Fangyan Wang (Purdue University), Sai Liang (Purdue University)
- It's Not Just What You Say, But When You Say It
Max Tu* (The Ohio State University), Alice Li (The Ohio State University), Greg Allenby (The Ohio State University)
- Designing Human-Automation Redundancy: Overreliance, Automation Shirking, and the Operator's Dilemma
Doron Cohen* (Carnegie Mellon University), Yefim Roth (University of Basel), Joerg Rieskamp (University of Basel), Markus Schöbel (Carnegie Mellon University)
- When Peers and Chatbots Disagree: How Conflicting Advice Shapes Auditor Voice
Dongsheng Li* (University of Wisconsin–Madison), Emily Griffith (University of Wisconsin–Madison), Dan Zhou (University of Wisconsin–Madison)
- The AI Echo Chamber: AI-Generated Summaries in Prediction Markets
Yi Tong* (University of Florida), Kaiyu Zhang (University of Florida), Qili Wang (Penn State University), Liangfei Qiu (University of Florida)
Hotel accommodations
Preferred accommodations
Conveniently located on Ohio State's campus:
The Blackwell Inn and Pfahl Conference Center
2110 Tuttle Park Place
Columbus, OH 43210
A preferred group rate has been arranged for conference attendees. Early reservations are encouraged, as availability is limited. Contact the hotel at 614-247-4000 if you need any additional information or help with booking.
Other hotels around the campus area
- Marriott Columbus OSU
- Fairfield Inn & Suites Columbus OSU
- Holiday Inn Express & Suites Columbus OSU-Medical Center by IHG
- Staybridge Suites Columbus OSU
Parking
Conference attendees may park in the Lane Avenue Garage. For parking validation, bring your garage entrance ticket to the conference registration table.
Lane Avenue Garage
2105 Neil Avenue
Columbus, OH 43210
Call for submissions
We invite scholars from all business management disciplines conducting research in the broad domain of effective human-AI collaboration to submit an abstract (maximum 500 words, excluding references, tables, and figures) in PDF format. The abstract should summarize the research project and articulate its intended contribution to the conference.
Submission deadline: July 31, 2025
Call for submissions for the 2025 AI in Business Conference has closed.
Researchers in all business fields are invited to submit. We welcome abstract submissions from all areas of business, including Accounting, Information Systems, Finance, Marketing, Operations, Supply Chain, Logistics, Management, Entrepreneurship, Organizational Behavior, and Human Resources. Submissions may be interdisciplinary or rooted within a single business discipline. Examples include (but are not limited to):
- Human-AI collaboration in business processes
- Explainable AI, accountability, and governance
- AI ethics, bias mitigation, and fairness in business
- Mitigating Bias and Ensuring Fairness in AI Algorithm Design
- Generative AI for creativity, ideation, and marketing
- AI in operations, supply chain, and logistics
- Large language models and their business applications
- Psychological and behavioral responses to AI in the workplace
- Organizational change and the future of work in the AI era
- AI regulation, privacy, and security
- AI tools for strategic decision-making and innovation
- Individual and group differences in AI usage patterns
We welcome abstracts that propose contributions in any of the following forms:
Empirical, analytical, or theoretical research projects
Investigations that deepen our understanding of Human-in-the-Loop AI systems and human-AI collaboration across business functions.
Roundtable discussions
Facilitated discussions on emerging questions or challenges related to human-AI collaboration, designed to foster connection and idea exchange among scholars and practitioners.
Pedagogical approaches or teaching innovations
Novel teaching methods, curriculum designs, or classroom applications that explore AI’s role in business education.
All abstracts will undergo review by a multidisciplinary planning committee. Our goal is to create an engaging, community-based conference experience that highlights rigorous and diverse scholarship while also fostering collaboration, dialogue, and innovation across disciplines and sectors.
Best paper awards
- Best Student Paper Presentation Award ($1,000)
- Best Junior Faculty Paper Presentation Award ($1,000)
To qualify, the first author and presenter must be a PhD student, postdoctoral fellow, or junior faculty at the time of submission.
We look forward to seeing you at the inaugural AI in Business Conference at The Ohio State University!