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The Rivera Campaign: An AI Decision in a...

Cian, Luca;Goldenb...

Case

The Rivera Campaign: An AI Decision in a Gubernatorial Primary

Cian, Luca; Goldenberg, Rachael; Fortune, Mickey; Hunter, Phillip; Klopfenstein, Amy

M-1091 | Published September 25, 2026 | 5 Pages Case

Collection: Darden School of Business

Product Details

Set in January 2026, this fictional case asks students to step into the shoes of Olivia Garcia, the campaign manager for State Senator Maya Rivera’s gubernatorial campaign. Rivera has strong support within her own district and among special interest groups, but low name recognition beyond her base. Her opponent has higher name recognition, a significantly larger budget, and more support among undecided voters. Garcia must decide whether to follow the campaign’s traditional spending plan, which would consume virtually all of its projected budget, or to contract Helix, a new AI platform that claims to be able to perform several key campaign activities more efficiently and at a lower cost than human staffers. The case supports a discussion of how to think through the criteria for applying an AI tool in an uncertain, high-stakes scenario that could expose the protagonists to significant political, legal, and reputational risk. It can also promote a discussion on how to evaluate the different use cases of a single AI platform. Helix has several potential applications for political campaigns, each of which has a different price point and risk profile. Through evaluating the benefits and trade-offs of each feature, students can develop the skills to apply a similar analysis to other AI tools and applications. The case is intended for MBA, executive MBA, and executive education courses in marketing. It would be suitable for courses in core marketing strategy, digital marketing and analytics, technology strategy, and marketing and society. As the case focuses on an emerging technology that falls within a fragmented regulatory landscape, it would also be appropriate for courses in innovation and governance.

- Apply a three-tier evidence hierarchy (strong, emerging, unresolved) to AI-related marketing decisions. - Translate research on political persuasion into a practical marketing application. - Describe the documented trade-off between persuasion and accuracy in political communication and distinguish what the evidence establishes from what governance might mitigate. - Design a bounded pilot for implementing AI in a political campaign with measurement proxy, governance architecture, and kill criteria. - Reason about politically sensitive decisions without collapsing into normative judgment. - Unbundle AI into distinct use cases with different evidence bases.