Siobhán Mc Feeney, Target’s Senior Vice President, highlights that the true competitive advantage in AI comes not from the models themselves, but from the robust frameworks and systems built around them. At VB Transform 2026, she explained that while AI models are crucial, they aren’t sufficient alone to deliver value. Target carefully evaluates whether an AI agent is needed, what kind of agent to deploy, and ensures each agent earns its autonomy gradually. These agents are deeply integrated into Target’s infrastructure, enhancing supply chain efficiency, demand forecasting, and product availability.
Mc Feeney detailed how their approach involves comprehensive governance layers, continuous monitoring, and evaluation of AI agents’ performance and autonomy. This systematic architecture enables scalability and cost-efficient use of frontier AI models suited for complex tasks. Agents operate within clearly defined guardrails and can lose their autonomy if they underperform, ensuring transparency and reliability.
The process also requires a cultural shift where builders and engineers adapt to managing AI alongside human workers, developing new skills to maintain accountability as AI adoption accelerates. This layered approach to AI adoption exemplifies how Target maximizes value in its AI initiatives by focusing on the entire ecosystem around the models, not just the models themselves.
