Target is moving beyond simply “using AI” to fully “running on AI,” but surging costs from evolving pricing models by major AI providers are compelling the U.S. retailer to adopt a more deliberate and selective approach to the technology, its India head said on Monday.
Andrea Zimmerman, President of Target India, told Reuters that the company is now prioritizing intentional integration over broad deployment, carefully weighing returns on investment as AI economics shift.
“It’s about the intentional use and integration of AI rather than deploying it everywhere,” Zimmerman said.
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She highlighted that the company is making “significant investments” to ensure teams have the right tools, training, and governance frameworks in place. Discussions on AI pricing and strategy now occur at the highest levels, including architecture forums and senior leadership meetings within the technology organization.
This reassessment is driven by a broader reset in the AI industry. Providers such as Anthropic and OpenAI are increasingly moving toward token-based pricing, which charges based on actual usage rather than flat subscriptions. This model better reflects the computational intensity of advanced AI, but can lead to unpredictable and potentially higher costs for large-scale enterprise deployments.
For retailers like Target, which handle massive volumes of data across merchandising, supply chain, pricing, and customer personalization, this change requires tighter control and clearer ROI calculations.
India Operations Play a Central Role
Target’s global technology center in Bengaluru is a critical part of this transformation. The India operation employs about 5,600 people across verticals, including merchandising, digital, stores, and supply chain. Roughly 40% of Target’s global tech workforce is based in the city, making it one of the retailer’s most important innovation and execution hubs.
Zimmerman said the company is ramping up investment in its analytics teams to convert growing volumes of data into faster, more actionable insights. This capability is essential as consumer behavior shifts rapidly and the retailer seeks to respond with greater agility.
“We work to adapt really quickly when we see that consumer demand or sentiment start to shift,” she said.
The renewed focus on disciplined AI deployment comes as Target navigates a difficult period. The company has recorded three straight years of declining revenue, with cost-conscious shoppers trading down to cheaper alternatives amid persistent inflation pressures.
Under new CEO Michael Fiddelke, Target has outlined plans to invest an additional $2 billion this year in new stores, remodels, and technology initiatives, including AI.
Zimmerman acknowledged both the excitement and the realism surrounding AI adoption.
“AI is fun, exciting and interesting to think about. Change isn’t going to be immediate, and it is certainly not free,” she said.
Target’s experience indicates a maturing phase in enterprise AI adoption. After an initial wave of experimentation and pilot projects, many large retailers are now entering a phase of rigorous evaluation, focusing on high-impact use cases such as demand forecasting, dynamic pricing, personalized marketing, inventory optimization, and fraud detection.
The shift to token-based pricing is forcing companies to move from “AI for AI’s sake” to more measured strategies that prioritize measurable business outcomes. This includes building internal governance structures, developing hybrid human-AI workflows, and investing in data quality and integration capabilities.
For Target specifically, success with AI could be a key differentiator in a highly competitive retail environment. Effective use of the technology could help the company better anticipate consumer trends, reduce waste in supply chains, optimize store operations, and improve the omnichannel experience — all critical factors in regaining momentum against rivals like Walmart and Amazon.
The Bengaluru center’s growing role also highlights India’s rising importance as a strategic technology and innovation hub for global retailers. With its deep talent pool in data science, engineering, and analytics, India offers scale and cost advantages that allow companies like Target to accelerate AI initiatives while maintaining financial discipline.
As AI moves from hype to core infrastructure, retailers like Target are learning that sustainable value comes not from maximum deployment, but from thoughtful, well-governed integration that aligns with business strategy and financial realities.