GenAI Market Will Reach $235B in 2028, But Poor Data Quality Hinders Effective Deployment Across Consumer Industries
“AI and Unified Data: Empowering Next-Generation Product and Shopper Intelligence”
Despite the exponential growth of GenAI and other AI applications, the report finds that consumer industries still face daunting challenges that can result in lower margins, poor operational performance and missed opportunities. Findings from the Coresight-Digital Wave Technology report include:
- Only 41% of U.S.-based retailers have price planning “fully integrated” with complementary business functions including assortment planning, allocations, promotional planning and markdown optimization.
- 52% of U.S. retailers surveyed cannot execute at least 10% of their promotional campaigns properly in any given selling period.
- On average, retailers misprice 10% of their products in any given sales period.
The lack of clean, high-quality data and analytical capabilities are critical barriers to effective AI deployment. Without a single source of real-time, unified data for all applications, disconnects occur, and the full potential of AI cannot be realized. Gartner predicts that 30% of GenAI projects will be abandoned after proof of concept due to poor data quality, escalating costs and lack of business value.
Next-Generation, AI-Native Platforms Can Help Companies Realize True Value of AI
To address these challenges, a new generation of AI-native platforms is emerging, with Master Data Management at the core and sharing five key characteristics:
- Unified data model – Modern retail platforms must integrate vast amounts of data from diverse sources. A unified data model ensures consistency and accuracy, enabling better decision-making and operational efficiency.
- Enterprise-grade – AI platforms must be scalable, reliable, and able to handle large volumes of transactions and data, while ensuring high performance.
- Cloud-ready – Modern AI solutions must seamlessly integrate with cloud services to provide scalability and flexibility.
- Secure – Advanced security features such as encryption, multi-factor authentication and continuous monitoring are essential to protect customer and product data.
- Low-code/no-code, rapid development and extensible – Platforms that support low-code/no-code development empower users to create business applications with minimal coding; extensibility ensures that the platform can be customized and integrated with other systems as needed.
“The transformative potential of artificial intelligence for the retail and consumer sectors is indisputable, and it will affect every facet of business connected to both internal productivity and external consumer interactions in the near future,” said Deborah Weinswig, CEO, Coresight Research. “Nevertheless, it is imperative that organizations empower themselves with the right tools and technologies to dismantle data silos and ensure a seamless, integrated approach across all operational functions. The scale of potential impact is substantial, and those enterprises that do not adeptly navigate the transition to AI risk falling behind. We believe that companies are worrying about FOBO, the fear of being obsolete, if they do not get started with an AI roadmap.”
“The lack of high quality and unified data has been a huge barrier to successful AI adoption, but Digital Wave Technology has changed that paradigm with our ONE Platform,” said Lori Schafer, CEO, Digital Wave Technology. “Many of the world’s largest consumer-facing companies rely on the ONE Platform as their enterprise AI solution for enhancing customer satisfaction, profitability, improving product availability and driving greater efficiency.”
