Mihir Joshi

Iceberg diagram showing AI readiness gap with strategy above water and execution factors like data, process, and systems below

The AI Readiness Trap: Why AI Readiness Assessment Should Come Before Roadmap

Most organizations believe they’re ready for AI because the roadmap looks solid. But execution tells a different story. When ambition outpaces data, processes, and systems, initiatives stall. This gap between intent and capability is where AI efforts fail, and where the real work of readiness actually begins.

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AI prioritization framework showing progression from ideas to impact using business impact and data readiness model

Where Should You Start with AI in Aftersales? A Practical Prioritization Framework for Service Organizations

Most AI initiatives in aftersales fail not due to lack of ideas, but poor prioritization. This article introduces a practical framework to help service organizations decide where to start, based on business impact and data readiness, so they can sequence AI investments effectively and avoid costly, unscalable pilots.

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CRM junk folder showing ignored installed base service leads worth $10M in lost service revenue

The $10M Junk Folder: Why Installed Base Revenue is Lost

Installed base revenue often goes unrealized even when analytics uncover valuable service opportunities. In many organizations, these leads disappear inside CRM pipelines as sales teams prioritize larger deals. This article explores why service-generated opportunities get ignored, and how manufacturers can redesign the service-to-sales handoff to capture millions in lifecycle revenue.

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IT OT integration in manufacturing connecting machine data with aftermarket service operations

IT-OT Integration in Aftersales: Turning Machine Data into Service Revenue

Manufacturers invest heavily in ERP systems and industrial IoT, yet many still operate with a critical blind spot: enterprise systems disconnected from machine reality. This article explores how IT-OT integration in aftersales operations unlocks service revenue, improves field service efficiency, and enables outcome-based service models.

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team working while mirror reflects executive dashboard showing project status indicators

When the Dashboard Becomes the Project

Executive dashboards promise clarity, but poorly sequenced rollouts can shift teams from execution to optics. When red-green status indicators become visible to leadership before workflow discipline stabilizes, teams optimize for the dashboard instead of the work. This article explores how transformation leaders can design dashboard rollouts that improve governance without creating delivery friction.

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Digital industrial control panel connecting installed base assets to revenue levers and growth dashboard.

Service Revenue Execution: Where the Five Levers Actually Break

Service revenue strategies generally fail at execution. This piece breaks down the five levers where manufacturers actually lose revenue: contracts, parts pricing, field upsell, warranty-to-contract conversion, and modifications. Each leaks at a specific handoff between functions with conflicting incentives, and each has a clear, ownable fix.

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Agentic AI decision orchestration across warranty, parts, dealers, CRM, FSM, and ERP in aftersales

Business Case for Agentic AI in Aftersales: Quantifying Incremental Value Beyond Copilots

Most AI investments in aftersales improved productivity but failed to deliver material ROI. This article explains how Agentic AI changes the equation by orchestrating decisions across warranty, parts, dealers, and enterprise systems, unlocking incremental value beyond copilots in aftersales operations.

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