According to a new Fluent Commerce report cited by TechRadar Pro, agentic AI is already embedded in many retailers’ operations: 70% are piloting or have partially implemented AI agents, while 71% expect the technology to improve operational efficiency by 2026. Yet only 8% report full deployment and a mere 5% consider their systems mature and optimised. [1][2]
Retailers view agentic AI as a competitive necessity, with 88% acknowledging its role in keeping them abreast of rivals; nonetheless ethical and regulatory concerns (43%), customer trust and transparency (43%), data quality and integration issues (39%) and skills shortages (36%) are cited as material barriers to wider rollout. As Nicola Kinsella, Chief Strategy Officer at Fluent Commerce, noted: "Retailers are clearly investing in AI, but the journey from pilot to full-scale deployment is proving more complex than expected." [1][2]
To date, the dominant retail use cases have been customer service and chatbots (56%) and personalised marketing (46%), reflecting a focus on customer-facing automation. Industry studies from Salesforce and others also show customer service and marketing as the most active areas for AI investment, while merchandising, pricing and digital commerce are significant secondary adopters. [1][4][5][6]
However, the technology’s promise is expanding beyond front-of-house functions. Nearly one-third of retailers plan to deploy agentic AI in inventory management (30%) and supply chain optimisation (32%), driven by the potential to reconcile order exceptions, speed processing and improve fulfilment and delivery decisions. Fluent Commerce suggests that, "With the right data and a thoughtful rollout, retailers can capture real, measurable benefits from AI." [1][2]
External industry analysis points to both opportunity and caution among consumers. Bain & Company finds substantial use of generative AI for product research (30–45% of US consumers), but also that roughly half of shoppers remain wary of fully autonomous purchases, underscoring the need for transparency and human oversight as retailers scale agentic functions. [3]
Broad market research indicates AI adoption in retail is already widespread, yet converting investment into measurable business impact remains challenging. A Berkeley Research Group study found AI integrated across marketing, IT, digital commerce and merchandising, but stressed that tangible outcomes require better data integration, clear governance and skills development. [4]
To move from pilots to enterprise-grade deployments, retailers will need to prioritise data quality, interoperability and workforce training, while addressing ethical and regulatory concerns to preserve customer trust. Vendors and consultants urge a staged approach that keeps humans accountable for strategy while letting AI generate insights and actions from operational data. [1][2][4][5]
If handled carefully, agentic AI could shift retail from reactive workflows to more responsive, data-driven operations, yet current maturity levels indicate the sector is still at an early stage of that transition. [1][2][5]
##Reference Map:
- [1] (TechRadar Pro) - Paragraph 1, Paragraph 2, Paragraph 3, Paragraph 4, Paragraph 7, Paragraph 8
- [2] (Fluent Commerce) - Paragraph 1, Paragraph 2, Paragraph 4, Paragraph 7, Paragraph 8
- [3] (Bain & Company) - Paragraph 5
- [4] (Retail Dive / Berkeley Research Group) - Paragraph 3, Paragraph 6, Paragraph 7
- [5] (Salesforce) - Paragraph 3, Paragraph 6, Paragraph 7
- [6] (Salesforce news) - Paragraph 3
- [7] (WebProNews) - Paragraph 1
Source: Noah Wire Services