Retail CIOs are investing heavily in AI-driven demand forecasting, dynamic pricing, and hyper-personalized promotions. However, 68% of deployments stall due to siloed data from Kafka topics, Snowflake pipelines, and legacy ERP feeds. Without real-time observability into data lineage across cloud warehouses, edge POS systems, and third-party logistics APIs, AI models train on stale, inconsistent feeds.
Overview
The Info-Tech Research Group has published a blueprint, Build a Next-Gen Retail Tech Stack Roadmap, to help CIOs align business capabilities with core systems, identify modernization gaps, and build an AI-ready retail roadmap from warehouse to checkout.
Key Barriers
The firm's research highlights several recurring challenges that prevent retailers from modernizing with confidence and scaling AI effectively, including:
- Disconnected point solutions that obscure the overall architecture and make it harder to see how systems support business capabilities.
- Limited visibility into integration, security, spend, and data as departments select tools independently.
- The absence of a single source of truth, which blocks analytics maturity and limits AI readiness.
- Difficulty proving ROI when system investments are not clearly linked to measurable business outcomes.
- Legacy dependence, outdated asset inventories, and short-term fixes that delay modernization and increase technical debt.
Three-Phase Roadmap
The Build a Next-Gen Retail Tech Stack Roadmap blueprint details a structured, three-phase methodology to help CIOs and retail IT leaders turn fragmented technology landscapes into actionable modernization plans:
- Align and Assess: Executive and IT leaders define the vision, desired business outcomes, and top modernization goals.
- Design and Evaluate: Retail organizations sketch the future-state technology landscape, identify the core enabling technologies needed to close capability gaps, and score applications across key layers.
- Plan and Commit: Teams translate heatmap results and modernization priorities into a sequenced roadmap.
By applying this methodology, retail organizations can improve portfolio visibility, reduce redundancy, strengthen decision confidence, and create a clearer connection between technology modernization and business value. The result is a more coherent foundation for AI-enabled retail, helping leaders make smarter investment decisions and build a technology environment that can adapt as customer expectations, operational demands, and AI capabilities continue to evolve.
In conclusion, retailers must prioritize data flow visibility and modernize their tech stack to avoid wasting AI spend. By following the three-phase roadmap outlined in the Build a Next-Gen Retail Tech Stack Roadmap blueprint, retailers can create a more coherent and effective technology environment that supports their business goals.