Build a Next-Gen Retail Tech Stack Roadmap

Power smart retail with AI, from warehouse to checkout.

Analyst perspective

Turn digital chaos into a competitive advantage

CIOs face a paradox: technology has never been more abundant, yet achieving digital coherence has never been more difficult. In their pursuit of AI, many rush ahead without first understanding their existing tech stack or addressing underlying data quality issues. A costly mistake that leads to wasted time, effort, and investment.

Modern retailers now operate within sprawling ecosystems of point solutions, each promising innovation, efficiency, or AI-driven insights, but collectively they can inadvertently create more fragmentation, redundancy and disconnected data. True progress of powering smart retail with AI, from warehouse to checkout, begins not with more technology but with a unified, well-understood foundation, capable of supporting intelligent, connected retail.

Donnafay MacDonald

Research Director, Industry Research
Info-Tech Research Group

Executive summary

Your Challenge

When evaluating how to implement AI into their tech stack CIOs are faced with:

• A flood of disconnected point solutions that obscure the overall architecture.
• Loss of visibility over integration, security, and spend as departments act independently.
• Inability to establish a single source of truth, blocking analytics and AI adoption.
• Difficulty proving ROI when system investments aren’t linked to business outcomes.
• Entrenched legacy dependence and short-term fixes with familiar tools that prevent modernization.

Common Obstacles

Obstacles that CIOs face in modernizing and rationalizing the retail tech stack:

• Short-term goals are prioritized over shared architecture principles.
• Outdated or inconsistent asset inventory makes it difficult to map dependencies, assess risk, or identify redundancies.
• Tight margins due to competing priorities and high cost of projects delay modernization efforts.
• Familiarity with existing systems and talent shortages lead to slow transformations.

Info-Tech’s Approach

Overcoming these challenges starts with a clear roadmap that unites, clarifies, delivers quick wins, and equips people for change; this research will help CIOs:

• Establish a shared vision that connects strategy to business outcomes.
• Use tools to build a transparent technology landscape view for better decision-making.
• Create a phased implementation plan that balances quick-wins with long-term scalability.
• Generate insights into embedding collaboration to sustain continuous improvement.

Info-Tech Insight

The greatest obstacle in retail transformation isn’t the pace of innovation; it is the lack of coherence. Modern retailers succeed when they align vision across the enterprise, bring clarity to a complex tech stack, modernize with intent, and empower people to drive lasting transformation.

Your challenge

Making AI real in a fragmented tech stack is a challenge and most organizations are faced with:

• Mounting pressure to deliver AI-driven solutions, and yet many are navigating a maze of disconnected systems.
• Departments are adopting tools independently, which erodes visibility into integration, security, spend, and data.
• As legacy platforms and high technical debt continue to dominate, modernization efforts become secondary priorities.
• Without a unified view of systems, data, and process, proving ROI on AI investment becomes nearly impossible, leaving organizations stuck between ambition and execution.

The AI Integration Bottleneck

42%

To deploy AI agents successfully, 42% of enterprises must connect data scattered across eight or more systems.

86%

Outdated tech stacks are blocking more than three-quarters of enterprises from implementing AI agents.

Source: Architecture & Governance Magazine, 2025

Common obstacles

Breaking through barriers to modernization; what is holding organizations back?:

• Modernization is an organizational problem, not just a technology problem.
• Many organizations prioritize immediate goals over architectural discipline, which leads to fragmented systems that are difficult to align.
• Outdated or inconsistent asset management adds to the difficulty of mapping dependencies or identifying redundancies.
• Organizations are locked into the systems they are trying to evolve out of due to tight budgets, familiarity, and talent scarcity.

The Alignment Deficit

61%

EA practitioners who report that shifting organizational priorities disrupt architectural planning.

74%

EA practitioners who say short-term operational needs override strategic goals.

Source: Madhuri Koripalli, “Enterprise Architecture in modern business: Overcoming challenges and ensuring success,” 2025

Start with the business reference architecture

Define how the business creates value before designing how technology enables it.

Before building the Next Gen Retail Tech Stack Roadmap, teams must first establish the Retail Business Reference Architecture and have worked through the exercise of ranking business capabilities that must and should be addressed.

The Retail Industry Business Reference Architecture research ensures that technology strategy aligns with real business needs. It identifies the core value streams and level 1 & 2 business capabilities and takes the team through the exercise of a heat mapping process to find data gaps within the organization; that knowledge is then referenced in this research.

With this foundation piece in place, the Tech Stack exercise uses the final output to map the key technology that supports the key business capabilities.

Retail Business Reference Architecture

Download Retail Business Reference Architecture

Retail Teck Stack Modernization

Retail CIOs don’t need another long-range transformation plan; they need clarity by Friday.
This one-week sprint produces a clear vision on the core platforms needed to support under-served business capabilities

Info-Tech’s methodology for Building a Next-Gen Retail Tech Stack Roadmap

Insight summary

Architecture is the new AI enabler

The gap between ambition and execution isn’t the lack of innovation, it is a lack of integration. Enterprises that modernize their tech stack, unify data, and enforce architectural discipline are the organizations that will be able to scale AI beyond isolated pilots.

Clarify before complexity

Organizations must align first on shared business outcomes and access their true readiness. When the picture is clear around systems, data flow, and ownership, every AI initiative becomes an opportunity to enable efficiency, improve decision-making, and enhance the overall experience.

Blueprints beat band-aids

Designing systems for AI implementation requires intentional architecture and not incremental fixes. Clearly mapping dependencies and validating integration paths helps to replace short-term workarounds with a scalable framework that can adapt as AI evolves.

Transformation demands discipline

Commitment to modernization means linking architecture decision directly to business value. This helps in reducing drift and ensuring long-term impact beyond initial enthusiasm.

Reduce the architecture deficit

When priorities shift, and inconsistent standards erode the foundation, re-establishing architectural governance is the fastest way to rebuild trust in the stack.

Platform thinking

CIOs must replace fragmented tool choices with unified and interoperable platforms to ensure AI deployment delivers on its promise.

Key Deliverable

Each step of this blueprint is accompanied by supporting deliverables to help you accomplish your goals:

Build a Next-Gen Retail Tech Stack Tool

Key deliverable:

Consolidate all your activities through the Build a Next Gen Retail Tech Stack Tool into a single, actionable roadmap that visualizes modernization priorities by system, architecture layer, and time horizon, all in one view!

Note: Visuals are examples from the Excel Workbook transcribed to PowerPoint.