Programme Content
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.
