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Why Replacing IBM I Core Completely Is Not A Prerequisite For AI Readiness

تكنولوجيا
Forbes
2026/06/05 - 13:15 501 مشاهدة
InnovationWhy Replacing IBM I Core Completely Is Not A Prerequisite For AI ReadinessByMohit Gupta,Forbes Councils Member.for Forbes Technology CouncilCOUNCIL POSTExpertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. | Membership (fee-based)Jun 05, 2026, 09:15am EDTMohit Gupta, the CEO of Damco Solutions, is a visionary business leader with over 30 years of industry experience. gettyThere is a conversation happening in boardrooms and technology leadership meetings across every major industry. It follows a logic that feels airtight: The core system is IBM i, but IBM i is legacy, therefore the platform must be exited before the organization can meaningfully pursue AI.The reasoning is clean, but there is a possibility that this transition goes wrong, at a cost that far exceeds the problem it purports to solve.This is not a case for inertia. The modernization pressures bearing down on CIOs are real. Boards are demanding AI readiness on timelines that leave little room for deliberation. Capital budgets cannot absorb the full weight of a platform migration without crowding out other strategic priorities. The report program generator (RPG) talent pool is contracting, and the generation behind it is not replenishing it. These are legitimate constraints.Yet, through all of it, the platform runs well in most cases, processing the transactions the enterprise depends on every hour, every day.In some cases, rigorous examination may highlight complete migration as the genuine need of the hour. In many others, the instinct under sustained pressure is to treat the system itself as the problem.Before that instinct hardens into strategy, it deserves a deeper look.The Legacy Label Obscures More Than It RevealsWhen technology leaders describe IBM i as legacy, they are pointing to something real: an interface layer that has not kept pace with modern expectations, limited native exposure to AI and data tooling and business logic that l...
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