MIT CISR Annual Research Forum 2026

Developing Expertise for Human-AI Collaboration
Nick van der Meulen

MIT CISR research has shown that success with AI depends on people knowing when to trust its output—and when to override it. Yet that judgment comes from experience, and the work that once built it is increasingly conducted by AI. In this session, we'll examine the three types of skills that human-AI collaboration demands of your workforce, why most organizations are investing in the wrong ones, and what leaders can do about it.

Fifty-two Years of MIT CISR Research: Enduring Challenges and Lessons Learned
A conversation with Peter Weill, Jeanne Ross, and Stephanie Woerner

Peter, Jeanne, and Stephanie will discuss the challenges of doing relevant research for executives plus the enduring lessons that they have learned over MIT CISR's history. Following their conversation, they will open up the discussion to the audience who will share their own experiences and lessons learned.

Towards an AI Operating Model
Alan Thorogood

During this session, Alan will examine how large companies capture AI value across the enterprise and we’ll discuss how intelligence architectures support agility, cost management, and risk mitigation. Effective practices for innovation, workforce development, platforms, and supplier ecosystems identified in our research will be highlighted.

Context Is Key: Building Contextual Empathy into AI Offerings for Rapid Delivery
Gayan Benedict

Building on MIT CISR's Business Models in the AI Era framework, this case study session will explore how PwC operationalized the Modular Curator model through Regulatory Pathfinder. This agentic AI platform develops contextual empathy for each client's regulatory environment by learning from historical failures, corrective actions, and success guidance—compressing service delivery from weeks to days and lifting early-stage compliance efficacy from 80% to 95%. Gayan will conduct a brief technical demonstration and then facilitate a discussion.

The AI Decision Matrix: Designing Decision Rights for Humans and AI
Ina Sebastian and Peter Weill

Companies are beginning to use AI to conduct enterprise work like hiring employees, approving loans, optimizing pricing, and running marketing campaigns. In this session, we will explore a practical framework based on two dimensions, ambiguity and risk, to map decision rights between humans and AI. Using examples from case studies and participants, we'll examine different approaches to human-AI decision making and implications for accountability, governance, and organizational design.

Managing Your Digital Colleagues
Stephanie Woerner

Enterprises are grappling with how to work effectively with AI as it is becoming more embedded in the enterprise, as a role, team member, and tool. This session will examine digital colleagues, which we define as AI that has a role in and performs work, makes decisions and recommendations and interacts with people. Stephanie will present current survey findings and case studies and what it takes to get value from these colleagues.