AI DECISION-MAKING, PROCESS TRANSFORMATION, AND STRATEGIC LEADERSHIP
You’ve sat through AI demos. You’ve approved pilots. Your team is experimenting (or resisting working) with AI. And yet the AI conversation in your organization still feels disconnected from the business decisions that matter:
- Which problems to tackle first
- How to redesign workflows that can scale
- How to invest wisely when the technology is still evolving
- How to lead a team that’s either anxious or overconfident about what AI can do
This seminar was built to turn AI ambition into results. Taught by Foster School of Business faculty who work at the intersection of technology, operations, and strategy, it gives you an end-to-end framework for understanding what AI can and cannot do, operationalizing it through real process transformation, and leading your organization through the strategic uncertainty that comes with it.
You’ll leave with concrete takeaways you can use immediately: an AI use case brief for a real problem in your business, a redesigned workflow with built-in guardrails and a pilot charter that can scale, and a strategic roadmap that connects AI investment to competitive positioning.
UPCOMING SEMINAR DATES
June 2-4, 2026 | UW Seattle Campus | Registration Deadline May 19, 2026
Benefits of attending
- Evaluate AI opportunities with a rigorous, value-based framework
- Redesign workflows that your team and AI can execute together
- Make disciplined AI investment decisions, including when to wait
- Stop approving AI pilots that don’t scale and start building ones that do
- Lead the organizational dynamics of AI adoption including trust, role changes, and psychological safety for your team
The seminar is structured as three sequential modules, each built around a leadership challenge, core frameworks, hands-on application, and a concrete takeaway. By the end of the three days, you’ll leave with a set of working assets you built during the seminar which can be applied to a real business context. You’ll be learning alongside operational and functional leaders from other organizations who are all navigating the same terrain.
The modules are designed to build on each other. The technology foundation in Module 1 enables the process work in Module 2, which informs the strategic decisions in Module 3.
MODULE 1: AI FUNDAMENTALS FOR BUSINESS LEADERS
Leadership challenge: AI initiatives often fail at the front end. Leaders either overgeneralize what AI can do and end up approving solutions that aren’t feasible or they stay out of the conversation because it feels too technical. Both lead to poor problem selection and mis-scoped efforts.
In this module, you’ll build a working mental model of how modern AI systems actually work — not at an engineering level, but at the level you need to scope problems correctly, evaluate proposals credibly, and ask better questions of your technical teams. Topics include:
- Core AI concepts, explained through use cases: machine learning, prediction, large language models (LLMs), embeddings, context windows, and retrieval-augmented generation (RAG).
- How to work backward from a business problem to a narrow, feasible AI use case and how to recognize when a problem isn’t solvable with AI.
- Organizational data readiness: what AI-ready data looks like, why most AI projects fail here, and what leaders need to do before approving a build.
- Illustrative examples spanning industries and business functions.
Concrete Takeaway: An AI use case brief that connects a real business problem to a feasible AI approach and data requirements.
This is the operational core of the seminar. You’ll learn a practical system for transforming business processes with AI, reliably and at scale, with emphasis not on “doing AI” but on building a repeatable engine for turning AI capability into improved flow, quality, service, and risk outcomes. Topics include:
- How to diagnose where process friction truly lives.
- A rubric for prioritizing AI-enabled opportunities that is designed to remove hype and novelty as decision criteria.
- Reusable process patterns for AI-enabled workflows.
- How to select the right level of human oversight for each part of a workflow and define the minimum viable guardrails.
- Writing a pilot charter with the scope, success metrics, monitoring plan, audit protocol, and fallback design that allows a pilot to move to scale rather than remain a one-off experiment.
Concrete Takeaway: A process transformation package: redesigned workflow + oversight and guardrails design + scalable pilot charter.
This module focuses on competitive strategy examining how AI changes what is possible in your industry, how value is created and captured, and what capabilities your organization needs to build for lasting advantage. Topics include:
- Developing an AI strategic vision: How AI may create new competitive advantages or threaten existing ones in your specific industry, business model, and organizational context.
- Building AI investment strategy around foundational capabilities, broad exploration, disciplined timing of growth, and integrated organizational learning.
- Designing an AI capability-building approach that weaves together talent development, technology infrastructure, and organizational culture.
- Assess make vs. buy decisions through a strategic lens: long-term competitive positioning, organizational learning, and ecosystem dynamics.
- Leading through uncertainty by managing organizational dynamics of AI adoption, including role disruption and fostering psychological safety for experimentation and learning.
Concrete Takeaway: A strategic AI roadmap linking your firm’s current advantages, industry dynamics, capability-building priorities, and investment choices.
Registration and Fees
June 2-4, 2026 | UW Seattle Campus | $3,600
Registration deadline: May 19, 2026
Register Now
Program fee includes instruction, all learning materials, parking on campus, and lunch and refreshments each day. Participants are responsible for their own travel and lodging. Payment is due prior to the course start date and accepted by check, credit card, or purchase order. Early registration is strongly encouraged as space is limited.
See discount and cancellation policies.
Organizations enrolling three or more participants may be eligible for group pricing. Contact us to discuss team enrollment and custom programming options.
FACULTY
Thomas Gilbert
Thomas Gilbert is an Associate Professor of Finance and Business Economics at the Michael G. Foster School of Business and an Adjunct Associate Professor of Economics at the University of Washington. He holds a Master’s in Physics from Imperial College London and a Ph.D. in Finance from the Haas School of Business at the University of California, Berkeley. His academic research spans optimal portfolio choice and information aggregation in financial markets, with publications in leading journals including the Journal of Finance, Review of Financial Studies, Journal of Financial Economics, Journal of Monetary Economics, and Management Science.
Thomas serves as the AI Strategy Lead for the Foster School of Business, where he coordinates all AI-related initiatives across teaching, research, and operations (https://foster.uw.edu/about-foster-school/ai-at-foster/). He teaches courses in managerial finance, data analytics, machine learning, and artificial intelligence. He recently developed a new MBA elective called “Leading AI Business Solutions” inspired directly by his work as an Amazon Scholar with AWS’s Machine Learning University team, where he designs and delivers non-technical AI training for mid-to-senior-level business leaders across the firm. He also teaches executive education classes at Foster and at UC Berkeley’s Haas School of Business.
A recognized educator and public voice on AI, Thomas has received many teaching awards including the PACCAR Award for Teaching Excellence in 2010 and 2017. He is a frequent contributor to Seattle news media and has published independent opinions in the Wall Street Journal.
MODULE 2 FACULTY
Masha Shunko
James D. Currie, CPA Endowed Associate Professor of Operations Management
Biography
Masha Shunko studies how organizations transform their operations through technology — from AI-driven decision-making and intelligent automation to the redesign of global supply chains. Her research spans the optimization of complex operational systems, behavioral dynamics in service delivery, and the strategic implications of embedding AI into core business processes. She serves on the board of the Responsible Research in Business & Management Society and consults with organizations including Microsoft, Mayo Clinic, and Caterpillar on technology-enabled process transformation.
Masha brings both analytical rigor and a practitioner’s lens to these questions. She holds a PhD in Operations Management and Operations Research from Carnegie Mellon University and is the James D. Currie, CPA Endowed Associate Professor of Operations Management at the Foster School of Business, University of Washington. Her research has appeared in Management Science, M&SOM, and POM, and has been featured in the Harvard Business Review, the New York Times, the Wall Street Journal, and Scientific American. A multiple teaching award winner, she pioneers the use of AI in her courses — including vibe coding, where students use natural-language AI tools to rapidly prototype working applications — and teaches in the Executive MBA and multiple Executive Education program. She holds editorial positions at M&SOM, POM, and Decision Sciences.
MODULE 3 FACULTY
Benjamin Hallen
Neal and Jan Dempsey Endowed Professor in Strategy and Entrepreneurship
Biography
Ben Hallen studies how companies drive exceptional growth in a range of contexts, from AI-native startups to mid-size private companies to large public corporations. His recent research has focused on how companies such as these build AI capabilities, how constellations of interwoven AI systems are changing the way organizations compete, and how leaders can navigate the strategic challenges AI introduces. He co-chairs the University of Washington’s new initiative bridging the Foster School of Business and the College of Engineering. His work has been published in the Harvard Business Review, including in their recent special issue on New Strategies for Growth.
Ben brings a combination of engineering depth and strategic insight to these questions. He holds three engineering degrees – including a PhD in Management Science and Engineering from Stanford University – and left graduate study in computer science to become an entrepreneur, serving as both CTO and CEO before returning to academia. He is the Neal and Jan Dempsey Endowed Professor in Strategy and Entrepreneurship at the Foster School of Business, where he helped launch the MS in Entrepreneurship and teaches in the Executive MBA program. He recently completed a term as an Associate Editor of Strategic Management Journal and previously taught at London Business School. His research draws on deep interviews with executives, board members, and investors, as well as large-scale machine learning methods, spanning companies from early-stage startups to large established firms.
SCHEDULE OVERVIEW
Day 1
- 8:30 a.m. – 9:00 a.m. — Check-in, coffee and tea provided
- 9:00 a.m. – 12:00 p.m. — Class
- 12:00 – 1:00 p.m. — Lunch provided
- 1:00 – 4:00 p.m. — Class
Day 2
- 8:30 – 9:00 a.m. — Coffee and tea provided
- 9:00 a.m. – 12:00 p.m. — Class
- 12:00 – 1:00 p.m. — Lunch provided
- 1:00 – 4:00 p.m. — Class
Day 3
- 8:30 – 9:00 a.m. — Coffee and tea provided
- 9:00 a.m. – 12:00 p.m. — Class
- 12:00 – 1:00 p.m. — Lunch provided
- 1:00 – 4:00 p.m. — Class
SEMINAR LOGISTICS
Location: Bank of America Executive Center (BAEC), UW Main Campus, 4275 NE Stevens Way, Seattle, WA 98195 View Map
Parking: Included in the program fee. A parking code and instructions will be emailed to participants before the seminar.
Commuting: Bike, bus, and light rail commuting options are available.
Accessibility: The University is committed to access and accommodation. Submit a request as needed.
CEUs: Continuing Education Units available. Request tracking when registering. Learn more about Continuing Education Units.