UST’s Retail GenAI Platform—bringing order to the AI chaos

Generative AI (GenAI) has been hailed as a transformative force in retail, promising to streamline operations, enhance customer engagement, and unlock new efficiencies. Yet, despite the evident potential, many enterprises remain mired in uncertainty. HFS Research found that the chief impediment to GenAI adoption is not the technology itself but the absence of a coherent implementation strategy (see Exhibit 1). Without a strong strategy, companies risk succumbing to a cycle of experimental enthusiasm, generating pockets of innovation without a clear path to consistent enterprise-wide deployment.

Exhibit 1: The most significant barrier to GenAI in retail is a lack of strategic direction

Source: HFS GenAI Survey of 132 Retail and CPG Executives, 2025

UST’s Retail GenAI Platform aims to introduce structure and organization to this landscape. It offers a structured, business capability-led framework to guide Enterprise CXOs through GenAI’s prioritization, contextualization, and scaling. While many organizations have embarked on pilots, UST’s Retail GenAI Platform, which the digital transformation solutions company launched in late 2024, provides a blueprint for expanding beyond isolated experiments to align AI with overarching business imperatives. The platform provides a snapshot of GenAI’s propensity to disrupt an industry or domain to help CXOs decide on a roadmap. AI’s efficacy depends on the quality of the data it processes—retailers must invest in clean, structured, and contextualized data to extract meaningful value.

Inside UST’s Retail GenAI Platform: A business-first approach

UST’s platform adheres to a business capability model, ensuring that AI initiatives support fundamental enterprise objectives rather than becoming siloed technology projects. The defining features include:

• Industry-standard business capability mapping: By leveraging the APQC retail business capability model, the platform systematically dissects retail operations into granular steps, identifying where GenAI can drive the most significant impact.
• Scenario cards for contextual AI: Unlike generic AI tools, UST’s Retail GenAI Platform enables the development of scenario cards to capture proprietary business knowledge and embed it within AI-driven processes. This enables business leaders—not just IT specialists—to shape AI applications.
• Composable and adaptive architecture: The platform seamlessly integrates with enterprise applications, intelligently maps and transforms data to enhance efficiency and insights, and supports multiple LLMs for flexible, business-driven AI capabilities.
• Clarifying AI investment decisions: By categorizing AI’s role across search, summarization, creation, and validation, the platform helps executives make informed investment choices, emphasizing business impact over technical novelty.

Retailers increasingly view GenAI as an enabler for merchandising, rapid product onboarding, order management, and financial forecasting. UST’s structured approach offers a systematic way to align AI investments with these high-impact areas. To scale effectively, UST should seek strategic alliances with cloud providers and retail technology platforms, accelerating integration and adoption. Additionally, it must define clear success metrics, ensuring that AI-driven initiatives translate into tangible business gains.

The job ahead is proving scalability and business value

While UST’s platform introduces much-needed structure to AI adoption, its ultimate success hinges on its ability to achieve large-scale implementation. The platform has already attracted 15 enterprises conducting experimental trials, and five customers are progressing toward full-scale deployment. However, the decisive success factor will be demonstrating quantifiable business value and cost efficiencies to justify broader adoption.

The competitive landscape is also shifting rapidly. Other players are embedding context-aware AI into their solutions, and firms are leveraging frameworks such as Microsoft’s MarS, a unified financial market simulation engine for decision-making. UST’s differentiation will rest on how effectively it can substantiate its claims with real-world results.

The Bottom Line: Retailers grappling with the complexities of GenAI adoption should consider UST’s Retail GenAI Platform. Its structured, business-first methodology prioritizes strategic decision-making, contextual AI integration, and scalable deployment frameworks, providing clarity for CXOs navigating the AI hype cycle.

Platform adoption can be beneficial, but success requires internal readiness. Before committing to this or any platform, retailers must critically assess their data infrastructure, integration pathways, and ROI expectations. UST’s platform is not a plug-and-play solution; it demands organizational alignment and investment in AI as a business enabler.