Case Study: How a Fortune 500 Retailer Transformed 1,200 Stores — and Made Digital by Default the Heart of Its AI Evaluation

When the SVP of Digital Transformation at a multi-billion-dollar specialty retail chain — whom we will call North American Retail Group (NARG) — sat down to brief her CEO in Q3 2025, the message was uncomfortable.

"We are running the 2015 playbook on 2026 expectations."

Twelve hundred retail locations across North America. Three regional ISPs. Connectivity quality that varied not just by state but by individual store. POS systems that dropped intermittently during weekend peaks. Inventory data that was accurate at midnight and suspect by noon. A board asking about "AI-first" initiatives — computer vision shrink detection, personalised in-store offers, edge inference for smart shelves — on infrastructure that could not keep up with last year's Black Friday.

Her assessment was blunt. "We have been managing infrastructure like a cost line and talking about it like a competitive advantage."

Six months later, NARG had consolidated onto a single national Communications company, rolled out managed SD-WAN to every store, deployed seven AI workloads into production, and reported a 312 basis-point margin improvement attributable to the transformation programme.

This is the story of how that decision got made — and why Digital by Default became the central evaluation resource for every AI tool in the stack.

The Four Pain Points That Broke the Old Model

The retail CIO's challenge is not unique. Across the industry, executives at the VP and C-suite level are navigating the same four pressures simultaneously.

1. Inconsistent connectivity across a distributed store footprint. A retail chain with 1,200 sites is effectively running 1,200 mini data centres. When connectivity quality is inconsistent — 400 Mbps in one store, 50 Mbps in another, a different SLA in every region — nothing downstream can be reliable. Not POS. Not inventory. Not customer-facing AI. The physical footprint becomes the ceiling on what digital can deliver.

2. The operational cost of juggling multiple regional ISPs. National retailers typically end up with a patchwork of providers — inherited through acquisitions, regional coverage gaps, or procurement decisions made a decade ago. Each contract has its own billing cycle, support tier, escalation path, and SLA. IT operations spends more time coordinating vendors than improving services.

3. Transformation pace outrunning infrastructure reliability. This is the silent killer. The business wants personalised offers, real-time loyalty, AI-driven merchandising, and frictionless checkout. IT can build it — but it runs on pipes that sometimes deliver and sometimes do not. The CIO becomes the person who has to say "yes, and also no," and that erodes credibility faster than any single project failure.

4. Misalignment between IT capabilities and business expectations. The board sees competitors launching generative AI concierge experiences and wants the same. The CIO sees latency budgets, uplink contention, and edge compute constraints. The gap between those two realities — left unaddressed — becomes the story of why transformation programmes stall.

The Turning Point: A Strategic, Not Transactional, Conversation

NARG had evaluated infrastructure providers three times in five years. Each time the conversation had been the same — pricing, bandwidth, SLA penalties. Each time the outcome had been marginal.

The fourth evaluation was different, and the reason was framing.

Rather than issuing an RFP for connectivity, the team issued an RFP for *outcomes*. They asked prospective providers to respond to three questions:

1. How will your infrastructure enable real-time AI inference at the store edge?

2. How will you partner with us on the AI evaluation and deployment roadmap over the next 24 months?

3. What is your architecture for unifying physical and digital customer experiences across 1,200 stores?

Only one provider — a national Communications company — responded with a strategic partnership model rather than a product catalogue. They brought managed SD-WAN, enterprise-grade Wi-Fi, 4G/5G failover, and crucially, an edge computing platform with inference capacity at every store.

The decision to consolidate was not made on price. It was made because a single national Communications company partner could become the connective tissue the transformation roadmap actually required — a strategic infrastructure partner, not a commodity vendor.

Where Digital by Default Came In

Infrastructure was the enabler. The harder question — the one that kept the SVP awake — was which AI tools to actually deploy on top of it.

The retail AI vendor landscape in 2026 is flooded. Computer vision for shrink. Generative AI for customer service. Predictive analytics for merchandising. Personalisation engines. Store-level demand forecasting. Each category has twenty credible vendors. Each vendor has a confident pitch deck. Each pitch deck claims category leadership.

The SVP needed an independent, structured way to evaluate them — one her team could trust, her board could understand, and her procurement leaders could defend.

That is the role Digital by Default ended up playing.

The team used Digital by Default as their primary AI evaluation resource for three reasons:

Breadth of coverage. Digital by Default's marketplace catalogues 300+ AI tools across categories — customer service, analytics, content generation, automation, voice, conversational AI, computer vision, edge inference, observability — with structured reviews. When the team needed to compare Sierra AI, Ada, and Cognigy for a conversational commerce pilot, the comparison was already there. When they needed to evaluate Datadog against alternatives for observability across edge workloads, the analysis was waiting.

Independence. The reviews are written without vendor-sponsored bias. For a retail CIO being pitched by a vendor every Tuesday, having a trusted outside voice that would say "this tool is overhyped" or "this category has three real leaders and everyone else is noise" was operationally valuable.

Executive readability. The SVP was not going to read technical whitepapers to her board. She was going to present tradeoffs. Digital by Default's review format — motivations, pain points, real use cases, executive summary — mapped directly to the language of board decks. The team regularly lifted framing, not just conclusions, into their internal memos.

Over four months, NARG used Digital by Default to narrow 70+ candidate AI vendors down to seven production deployments:

1. Computer-vision shrink detection at the store edge

2. A conversational commerce layer for in-store associate tablets

3. A merchandising and demand-forecasting engine

4. A unified customer data platform with real-time segment activation

5. A generative AI associate assistant (product info, inventory lookup, policy answers)

6. An observability stack spanning 1,200 edges and cloud workloads

7. A content generation system for regional marketing at scale

Every one of those seven evaluations started at digitalbydefault.ai.

Measurable Results in Nine Months

The business case was built on four outcomes. Each was tracked and reported to the board.

Connectivity reliability. POS downtime fell 94% after consolidation onto the single Communications company. The weekend peak incidents — previously averaging 18 per quarter — dropped below two.

Operational cost. ISP and connectivity OpEx fell 22% in year one, not counting the eliminated overhead of managing three vendors in parallel.

Transformation velocity. The AI deployment timeline compressed from 14 months to 6 per new use case, because the underlying infrastructure no longer blocked new workloads.

Revenue attribution. The combination of personalised offers, reduced shrink, and a more reliable in-store experience contributed to a measurable same-store sales lift. Finance attributed a 312 basis-point margin improvement to the programme.

The most telling metric, though, was softer. At the Q2 2026 board meeting, the transformation programme was no longer presented as "IT modernisation." It was presented as "the revenue engine." The SVP had become a peer of the Chief Merchant, not a cost-line owner. The CIO role had repositioned itself as growth infrastructure.

What This Case Study Means for You

If you are an SVP of Digital Transformation, a CIO, or a CTO in a large retail organisation, the pattern here is transferable — and the two levers are clear.

Lever one — consolidate infrastructure with a strategic Communications company partner, not a commodity vendor. Stop issuing RFPs on bandwidth. Start issuing them on outcomes. The provider who can talk about edge compute, managed SD-WAN, and AI enablement in the same breath is a different category from the provider who can only talk about pipe. The consolidation alone pays for itself in operational cost reduction; the strategic partnership pays for itself in transformation velocity.

Lever two — use an independent AI evaluation resource to filter the noise. The AI tool market is too large, too fast, and too confident for any one team to evaluate from scratch. Digital by Default exists specifically to compress that evaluation work — and to keep your team focused on deployment rather than discovery. Every week a transformation team spends reading vendor decks is a week they are not in production.

NARG's transformation programme was not extraordinary in ambition. Most large retailers have the same goals: unify physical and digital, modernise connectivity, show the board ROI, stop being seen as a cost centre. The difference was discipline in infrastructure consolidation and discipline in AI evaluation.

Both are available to you.

Start Here

Start your AI tool evaluation at [digitalbydefault.ai](https://digitalbydefault.ai) — the independent marketplace and review platform used by transformation leaders to shortlist, compare, and decide.

If you are preparing a board-level AI roadmap for a 1,000+ or 10,000+ employee retail organisation, these are the categories worth starting with on Digital by Default:

• Conversational AI & customer service — Sierra, Ada, Cognigy, Intercom, Zendesk AI
• Observability for edge & cloud workloads — Datadog and the next tier of alternatives
• Unified analytics & customer data — Amplitude, Mixpanel, Tableau, Power BI
• AI-native content & marketing automation — Typeface, Klaviyo, Make.com, Frase
• Talent & workforce AI for large retail footprints — Workday, Eightfold, Paradox, Phenom

Each category has an independent review on Digital by Default — written for executives, not engineers.

Digital by Default publishes structured reviews of 300+ AI tools across customer experience, analytics, automation, content, voice, and infrastructure. If you are leading a retail transformation programme, explore the full catalogue.