AI Won't Save Enterprises from Tech Debt Unless They Change the Architecture First

New HFS Research–Unqork study finds 43% of enterprises say AI will create new tech debt even as 84% expect cost cuts; maintenance dominates today's budgets because of code sprawl

NEW YORK, Nov. 18, 2025 /PRNewswire/ -- A new study from HFS Research, in collaboration with Unqork, exposes a striking paradox at the center of enterprise AI adoption: while 84% of organizations expect AI to reduce costs and 80% expect productivity gains, 43% report AI will create new technical debt. Sentiment is split almost down the middle on AI's long‑term impact on tech debt with 55% expecting a reduction and 45% expecting an increase, reflecting real anxiety about security, legacy integration, and black-box behavior as AI scales across the stack. Top concerns include security vulnerabilities (59%), legacy integration complexity (50%), and loss of visibility (42%).

The research also shows transformation economics are upside down. Only 18% of large transformation budgets is devoted to software, and 58% of organizations dedicate over 70% of their three‑year transformation budgets to services. Most enterprises spend 2–7x their license cost on implementation and integration turning a $1 million software decision into a $2-$7 million total commitment.

"AI is not a silver bullet, it's an amplifier of whatever already exists in your enterprise stack," said Phil Fersht, CEO and Chief Analyst, HFS Research. "If your architecture is brittle and code-heavy, AI will accelerate the chaos, not cure it. The true leaders will re-engineer their foundations, productize integration, embed governance, and shift investment from endless services to scalable software outcomes. That's how AI moves from hype to genuine enterprise reinvention."

"The antidote to code-heavy, legacy stacks is a componentized, no-code architecture with integration included in the product," said Gary Hoberman, CEO and Founder, Unqork. "That's how businesses can shift their spend away from maintenance to focus on what's most important, accelerate delivery, and avoid the next wave of tech debt as AI scales."

Key findings from the HFS-Unqork study underscore an ecosystem ripe for change:

• AI tech-debt paradox. 84% expect cost cuts; 80% expect automation; 43% say AI creates new tech debt; split 55/45 on long-term impact; top risks: security (59%), legacy integration (50%), visibility (42%).
• Hidden maintenance tax. Only 18% of transformation budgets are spent on software; 58% allocate >70% of budgets to services; most spend 2–7× license cost on implementation, integration and maintenance.
• Shadow IT pressure. 97% of business units want to build in parallel to IT (Sales 51%, Data/Analytics 45%, Operations 44%), signaling demand for governed self-service platforms and tools.
• The SI mandate to evolve: Satisfaction with systems integrators is problematic (only 20% "extremely satisfied"). One in three has permanently ended a relationship with an SI after a failed engagement. 58% say the traditional SI model is unsustainable within five years, and 76% want integration bundled with software. (Frustrations like long cycles (47%), custom‑code reliance (37%), and missed outcomes (37%) were reported on a smaller base, n=57.)
• Reuse could be the silent value lever: Average code reuse is just 33%, meaning teams rebuild about two‑thirds of functionality, driving cost, delay, and future debt.
• Ready for a "Services‑as‑Software™" model. 98% are open to offloading legacy to a services‑as‑software model under the right conditions; 69% would do so if AI‑enabled management is included. Buyers prioritize quality (61%), security (57%), and speed (53%) over pure cost reduction (42%).

"Our research shows that enterprises are waking up to the economic reality of transformation: the real cost isn't in buying software, it's in maintaining and integrating it," said Hansa Iyengar, Practice Leader and research author. "The shift toward componentized, no-code platforms offers a way to break free from the maintenance treadmill and focus resources where they matter most—on innovation and adaptability as AI takes center stage."

The report points to no‑code platforms amplified by AI and a services‑as‑software delivery model (i.e., integration and operations bundled into the product) as the fastest route to value without compounding technical debt.

The full report from HFS Research is available for download at: https://www.hfsresearch.com/research/modernization-tipping-point-architecture-over-arbitrage

About the research (survey methodology):
HFS Research conducted a multi‑question survey in September 2025 with 123 respondents (Global 2000–scale organizations). Topics included platform economics, development practices, SI partnerships, AI adoption, and governance. Unless otherwise noted, percentages refer to the total sample for each question; base sizes vary by item. The study was executed in collaboration with Unqork.

About Unqork
Unqork is the enterprise-grade platform that powers secure, no-code application development at scale. Unqork's platform, and new proprietary intelligence layer, Unqork AI, helps enterprises reduce technical debt to focus on transformation and innovation. Unqork is trusted by enterprises like Goldman Sachs, Marsh and BlackRock, in highly regulated industries for mission-critical systems, because of its superior governance, compliance and stability. To learn more, visit: https://www.unqork.com.

About HFS Research
HFS Research is a leading research and advisory authority on enterprise transformation, serving Fortune 500 companies with fearless insights and actionable strategies. With unparalleled access to Global 2000 executives and deep expertise in AI, automation, and digital business models, HFS empowers organizations to make confident decisions that create sustainable competitive advantage. For more information, visit: www.hfsresearch.com.

SOURCE HFS Research