Integrate machine learning into pricing workflows while keeping human judgment at the center of the process.
Pricing is one of the most consequential decisions an organization makes. Yet many companies begin exploring dynamic or personalized pricing before they have established the data foundation required to understand demand reliably.
Leveraging AI for Competitive Pricing Advantage is a new Executive Education program at the Yale School of Management focused on the role of AI in pricing strategy. Participants examine where AI can strengthen pricing decisions, what must be in place before it can be used effectively, and how leaders can evaluate its recommendations with appropriate judgment.
The program combines approximately six hours of instruction with three weeks of applied work in a shared cohort experience. Each module introduces a pricing problem and a series of cases and activities. Participants have time to complete the work, consider how it applies within their organization, and bring their analysis into the next module.
The modules are designed for managers and leaders who set, negotiate, approve, or influence price.
About the Program
AI can expand what organizations are able to observe, analyze, and adjust in pricing. Its contribution to pricing decisions relies on the quality of the underlying pricing strategy, the data used to understand demand, and the judgment of the leaders directing the work.
This program is designed around application, and each module moves from faculty instruction to cases, activities, peer input, and feedback.
As the program progresses, participants examine their competitive position, assess their organization’s readiness for AI-assisted pricing, and develop a response to a priority implementation risk.
Participants apply their insights to a series of assignments. Collectively, these assignments form a Pricing Strategy Portfolio, ready for participants to use at work and share with their teams.
What to Expect
1. Evaluate where AI can contribute to pricing: Learn what to ask of an AI-assisted pricing model and how to interpret what it produces. No coding experience is required.
2. Work through applied pricing decisions: Cohort polls and discussion activities create opportunities to compare approaches and consider how pricing decisions differ across organizations and industries.
3. Build a portfolio you can show your team: The Pricing Strategy Portfolio includes a map of the participant’s competitive position, an AI Pricing Readiness Snapshot, and a risk action plan. Because the activities build on one another, participants develop their analysis throughout the program rather than completing a single exercise at the end.
Who Should Attend
- Mid- to senior-level managers responsible for pricing, revenue, or commercial performance: Leaders who set or approve prices and want to make informed decisions as AI becomes more widely used in pricing.
- Professionals in marketing, operations, finance, product, or strategy: Cross-functional contributors who influence pricing and want a shared framework for evaluating where AI may be useful.
- Founders, entrepreneurs, and leaders of small and midsize businesses: Leaders interested in practical applications of AI-assisted pricing, including those without a large data-science team.
- Managers who work with data teams, vendors, or technical specialists: Decision-makers who need to understand AI-assisted pricing well enough to frame the business problem, direct the work, and evaluate the analysis they receive.
- High-potential managers and aspiring executives: Rising leaders seeking to develop the strategic and data-informed judgment increasingly required in pricing decisions.
Agenda
- Module 1: Reading the Competitive Landscape
Examine three established approaches to pricing: cost-plus, competition-based, and value-based pricing. Participants identify their organization’s current approach, compare it with named competitors, and consider how the role of AI differs across pricing strategies. Participants begin their Pricing Strategy Portfolio by mapping their organization’s competitive position and identifying a pricing question that warrants further examination. - Module 2: Applying AI Across the Pricing Process
Explore the role of AI across the pricing process, beginning with the data used to understand demand. Participants consider applications including demand estimation, market research, dynamic pricing, algorithmic pricing, and personalized pricing. The module examines the organizational and data conditions that must be established before more advanced applications can be used effectively. Participants complete an AI Pricing Readiness Snapshot to identify where their organization may be prepared to act and where further work is needed. - Module 3: Managing Risk and Readiness
Examine the risks that may arise when AI is introduced into pricing, including implications for customers, markets, regulation, organizational decision-making, and operational execution. Through a cross-functional case, participants consider how different stakeholders may interpret the same pricing decision. They conclude the program by developing an AI Pricing Risk Checklist, a risk action plan, and a governance step their organization could take within 90 days.
Faculty
Kosuke Uetake
Professor of Marketing, Yale School of Management
Areas of Expertise: Pricing, Quantitative Marketing, Industrial Organization, Market Design
Read the full bio
Kosuke Uetake is Professor of Marketing at the Yale School of Management. His research examines questions in quantitative marketing, industrial organization, and market design, with particular attention to pricing and competition. He is also a Faculty Fellow at the Yale Center for Algorithms, Data, and Market Design.
His research considers the limitations of estimating demand from historical prices and sales alone, particularly when those observations also reflect managers’ earlier pricing decisions. This distinction informs the program’s examination of the data and assumptions used in AI-assisted pricing.
Professor Uetake holds a Ph.D. from Northwestern University.
Registration Information
Program Details
Length: About 6 hours (3 modules, roughly 2 hours each)
Location: Online
Program Fee: $850 (Payment of program fee required at registration.)
Contact Joanne Legler, Senior Director of Learning Partnerships, at somexeced.info@yale.edu for more information.
Program Fee Assistance
Yale SOM Executive Education offers a 15% reduction in program fee for:
- Those who work in the nonprofit sector. (Apply NONPROFIT code at time of registration.)
- Those who work in government. (Apply GOV code at time of registration.)
- Yale University alumni. (Apply YALEGRAD code at time of registration.)
- Groups of 3-6 participants. Groups can be from an organization or be self-formed.
- Those who have previously participated in a Yale Executive Education program with Yale SOM or 2U/GetSmarter.
Discounts cannot be combined.
Refunds & Cancellation
Payment in full is required at the time of registration.
- Refunds: Withdrawals made more than 7 business days before the program start date will be eligible for a full refund.
- Deferrals: Requests to defer to a future cohort may be considered up to 7 business days before the program start date, subject to availability and Yale approval.
- No refunds or deferrals will be granted after the start date of the program.
All refund and deferral requests must be submitted in writing to the Yale Executive Education Registrar.
Yale reserves the right to cancel or reschedule programs if enrollment is deemed insufficient or health and safety would otherwise be jeopardized. Yale School of Management is not responsible for any travel or incidental costs incurred by a registrant if a program becomes canceled. If a program is canceled by Yale, a full refund of fees paid will be processed within 30 days.
While it is our goal to deliver our programs as scheduled, we may postpone programs, deliver them online, or cancel them. If one of our programs has a scheduling change, we will notify those affected as soon as possible.
Frequently Asked Questions
Do I need a technical or data-science background?
No. This is a strategy program, not a coding course. Participants learn how to frame questions for AI-assisted pricing, examine the assumptions behind the analysis, and judge how the results should inform a business decision. The technical development of a model would remain with an organization’s data team, technical specialists, or external vendor.
Why focus on AI and pricing now?
AI is expanding the range and speed of pricing decisions organizations can make. Its value depends on whether leaders understand the pricing problem, the underlying demand data, and the risks created by implementation.
This program approaches AI-assisted pricing from a managerial perspective. It is grounded in Professor Uetake’s expertise in pricing, quantitative marketing, industrial organization, and market design rather than in a particular technology platform or vendor.
How is the three-week program structured?
The program includes approximately six hours of content across three modules, with one module released each week. Participants complete the work asynchronously, at about two hours per week, within a shared cohort period.
Each module includes faculty instruction, applied cases and activities, and opportunities to compare perspectives through cohort polls and discussion. Because modules open on a shared schedule, participants move through the material alongside their cohort. Participants also develop a Pricing Strategy Portfolio across the three modules.
Why is six hours of content completed over three weeks?
The three-week structure gives participants time to apply what they are learning. Activities completed in one module contribute to the work undertaken in the next.
Rather than moving through all six hours as a single block of content, participants have time to examine their own pricing context, document their thinking, and develop their analysis as the program progresses.
What will I work on during the program?
Participants develop a Pricing Strategy Portfolio that includes a map of their organization’s competitive position, an AI Pricing Readiness Snapshot, an AI Pricing Risk Checklist, and an action plan addressing a priority risk or governance concern.
Who is the program for?
The program is designed for managers and leaders who set, approve, negotiate, or influence pricing. It may also be relevant to professionals in revenue, marketing, finance, product, operations, and strategy, including those who work in organizations without a dedicated data-science team.
Is the program online or in person?
The program is delivered online. Participants complete it asynchronously within a three-week period.
Will I receive a certificate?
Yes. Participants who successfully complete the program will receive a Yale School of Management Executive Education certificate of completion.