Building AI for Production Requires More Engineering Than AI

GeekyAnts warns that delaying AI product modernization in enterprises incurs rising maintenance costs, slower AI deployment, and widening competitive gaps, with technical debt in the US reaching $1.52 trillion and early adopters seeing 20-30% higher EBITDA growth.

Jun 11, 2026 The Hidden Cost of Delaying AI Product Modernization in Enterprise Businesses This blog explores the business cost of delaying AI modernization, from rising maintenance expenses and AI integration challenges to the growing competitive advantage of early adopters. Author Book a call Table of Contents Across enterprise organizations, AI product modernization https://geekyants.com/enterprise-system-modernization/app-modernization keeps appearing on roadmaps and getting pushed to the next planning cycle. The reasons are familiar: migration risk, budget pressure, and systems that still perform their core functions. What receives less attention is the cost of that delay in the current year. Maintenance expenses continue to rise, AI initiatives take longer to launch https://geekyants.com/blog/the-cost-of-delaying-production-readiness-in-ai-fintech-product-development , and competitors gain experience that cannot be acquired through spending alone. Those costs accumulate whether they appear in planning documents or not. Maintenance Is Consuming Resources Meant for Growth 20 to 40% https://www.mckinsey.com/capabilities/tech-and-ai/our-insights/tech-debt-reclaiming-tech-equity of the value of an enterprise's technology estate. The Consortium for IT Software Quality estimates that technical debt principal in the United States has reached $1.52 trillion https://www.it-cisq.org/the-cost-of-poor-quality-software-in-the-us-a-2022-report/ . improved customer experiences https://geekyants.com/customer-experience , or AI initiatives. Organizations facing these costs are funding stability rather than progress. Legacy Infrastructure Creates AI Adoption Barriers AI model https://geekyants.com/ai/ai-development-services enters production. Successful AI systems https://geekyants.com/ai depend on data that is accessible, structured, and consistent across the organization. AI tools https://geekyants.com/blog/top-10-ai-tools-every-uiux-designer-should-master on top of this architecture does not remove the underlying limitation. In many cases, it exposes the problem at a larger scale. AI-assisted modernization https://geekyants.com/blog/modernize-your-enterprise-systems-how-generative-ai-revolutionizes-integration can reduce modernization timelines by 40 to 50% compared with traditional approaches. The benefit is significant, but modernization still needs to occur before organizations can realize those gains Competitive Gaps Expand With Time 20 to 30% https://blog.phenomecloud.com/featured-blogs/why-enterprises-that-delay-ai-adoption-or-ai-strategy-will-fall-behind-by-2027 higher than sector peers during the same period. EBITDA is a measure of operating profit before interest, taxes, depreciation, and amortization. Higher profitability creates more capacity for future investment, while organizations that delayed modernization must fund both catch-up efforts and ongoing operations. Generative AI adoption https://geekyants.com/service/generative-ai-development-services increased from 33% to 71% during the same period. What Waiting Is Costing Enterprises GeekyAnts https://geekyants.com/ works with enterprise teams to assess existing technology environments, identify modernization priorities, and build implementation roadmaps https://geekyants.com/artificial-intelligence-consulting/ai-discovery-sprint that reduce risk throughout the process. If your organization is evaluating its next step, our team can help determine where modernization will deliver the greatest impact. Subscribe to Our Newsletter Subscribe to RSS Press & Media Hub RSS Feed /rss/insights.xml Related Articles. More from the engineering frontline. 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