Target names its first chief artificial intelligence officer, Chandhu Nair, effective Aug. 24

Target has appointed its first chief artificial intelligence officer, Chandhu Nair, as the retailer moves to formalize an internal leadership role dedicated to AI, according to a report published Aug. 12. The new position begins Aug. 24, with the company describing the expanded effort as part of a broader push to use artificial intelligence across areas including inventory management, operations and customer experience.

Nair’s title is notable because it makes AI a named executive function, rather than an effort spread across technology teams and business units. While Target has been adopting data-driven tools for years, the creation of a dedicated AI executive role suggests the company wants a clearer line of accountability for how models are developed, tested and deployed across the retail stack.

In the reported description of the role, Target tied AI initiatives to three operational goals. First, AI is being used to improve inventory, a core challenge for retailers that must balance demand forecasts, product assortment and supply constraints while limiting excess stock. Second, the company pointed to AI for operations, which can include everything from labor scheduling and process automation to anomaly detection in logistics and stores. Third, Target linked its AI expansion to customer experience, which typically includes personalization and service improvements informed by customer behavior and product interactions.

For investors, the timing and framing matters. Retailers increasingly face competitive pressure to lower costs and reduce waste, while also differentiating on service and relevance. Turning AI into a centralized executive priority can be interpreted as Target trying to move from isolated pilots to scaled deployments, where the benefits are measurable and the execution is coordinated.

The report also positions the announcement as part of a continued push into artificial intelligence, at a moment when the broader industry is experimenting with generative AI for tasks such as customer support and internal knowledge tools, while also relying on more traditional machine learning for forecasting and optimization. Target’s emphasis on inventory and operations aligns more directly with the latter category, where improvements can show up in planning accuracy and operational efficiency, rather than purely in marketing copy.

Target does not disclose, in the report, specific details such as the size of the AI budget, the scope of Nair’s remit beyond the listed areas, or whether any new AI products are expected to roll out immediately after the Aug. 24 start date. It also does not provide information about whether Target will change its organizational structure around AI, such as consolidating data science teams or expanding partnerships with cloud or AI vendors.

Even without those particulars, the appointment offers a window into how large retailers are organizing around AI. As AI use grows, companies often need tighter governance around data quality, privacy, model performance and integration with enterprise systems like merchandising platforms and store operations tools. A chief AI officer role can also help align business priorities with technical constraints, especially when multiple teams are using different models for different use cases.