The Inventory Intelligence Shift

A Moment of Clarity

When Akash Khurana joined Wesco in November 2020, the global supply chain was unraveling. From product shortages to delivery disruptions, the market was under incredible strain. But Khurana, stepping into his role as EVP and CIO amid Wesco’s $4.5 billion merger with Anixter, immediately identified a deeper threat: a reliance on aging, linear IT systems that were ill-suited to the company’s new scale.

Wesco had grown into a $20 billion global enterprise with operations in over 800 locations, but its technological foundation struggled to keep pace. Khurana didn’t just want to upgrade systems; he wanted to shift Wesco into a technology-first organization where real-time decisions could be made, powered by data and AI.

The Old Way Unraveled

Before this shift, Wesco’s operational model was bound by tradition. Sales representatives made decisions based on memory and familiarity with specific product sets, offering customers what they knew best rather than what was most optimal. “It was very linear in terms of responses,” Akash recalled, highlighting the limited scope and speed of legacy decision-making.

The company’s back-end processes, grounded in spreadsheets and siloed systems, failed to offer the scalability or agility needed for a global operation. Customers were often left frustrated by frequent stock-outs or sub-par alternatives, and internally, teams battled 15% reliability faults and reactive maintenance cycles that drove up costs. Fragmentation across platforms and regions made data integration and insight nearly impossible, which led to inefficiency and a lack of competitiveness.

Reframing with AI

Khurana responded by launching an internal initiative that he termed the “AI Factory,” a conceptual and operational blueprint for reimagining how technology could permeate every aspect of Wesco’s business. He asked: “If we think of every business model or opportunity, [we need to ask] ‘what can AI do in this area?’” 

This reframing allowed him to rally teams from data engineering, supply chain, commercial operations, and IT under a unified transformation agenda. Sales processes were reimagined through AI-powered recommendation engines that could instantly generate multiple product mix scenarios, factoring in cost, availability, and customer-specific needs. 

At the same time, data teams migrated critical business information into a cloud-native infrastructure, enabling real-time access to pricing, inventory, and logistics data across regions. On the operations side, AI was integrated into supply chain orchestration platforms, allowing Wesco to shift from reactive replenishment to predictive inventory management.

Still, the transformation wasn’t frictionless. Sales teams feared that AI tools might devalue their expertise and organizational data silos created technical bottlenecks. Khurana addressed this tension by embedding transparency into the rollout process. Pilot programs were launched within focused business units, and workshops were hosted to demystify AI’s role.

More importantly, domain experts were paired directly with data scientists, reinforcing that AI would augment rather than replace human decision-making. The implementation followed a structured but agile methodology, with clear objectives and KPIs tied to outcomes like fill rate, quote turnaround time, and cart abandonment reduction. The full deployment, aligned with typical enterprise critical path timelines, took nine months from blueprint to rollout.

Measurable Impact

Within a year, the shift from theoretical AI to practical implementation began producing tangible results. Stock shortages across major segments dropped by 20%, directly improving fulfillment rates and customer satisfaction. Maintenance costs declined by 15%, largely due to the predictive capabilities of AI-driven asset management. 

On the frontlines, the time it took sales teams to generate and deliver tailored proposals dropped significantly, leading to increased conversion rates. Wesco’s employees also began to feel the cultural shift. “AI is freeing reps from mundane tasks,” Akash noted, “and letting them focus on strategic selling and relationship-building.” 

Beyond internal metrics, customers began to perceive Wesco as a supplier and a strategic partner that used analytics and technology to drive mutual efficiency and business growth.

What Others Can Learn

The success at Wesco reinforced a foundational belief: AI must be embedded into the operating model, not layered on top of it. For Khurana, the first step is intent, not technology. Leaders need to ask where AI can create value within existing business models and then pursue those opportunities through cross-functional squads that pair domain expertise with technical fluency.

By anchoring pilots to specific business goals and KPIs and by positioning AI as a collaborative force, Wesco was able to transform its internal skepticism into momentum. The “AI Factory” that started as a conceptual model is now a systemic capability. 

Looking ahead, Khurana plans to expand AI use into dynamic pricing and logistics optimization, capitalizing on Wesco’s expanding data infrastructure to forecast demand and respond with real-time price adjustments.

Takeaways

What sets Wesco’s transformation apart is the technological breadth and clarity of its execution. Under Akash Khurana’s leadership, the company didn’t simply adopt AI; it reframed its identity around it. 

By embedding intelligence into decision-making, championing cultural change, and treating AI as an integral part of operations, Wesco evolved from a traditional distributor into a technology-first enterprise. The result is a company better equipped to meet customer needs, empower its workforce, and lead in a digital economy.