Legacy Tech Killing AI: GFT Study Reveals 84% of Firms Abandon Pilots Due to Infrastructure

GFT Technologies has released a global study revealing that legacy infrastructure is the primary barrier to enterprise AI success, forcing 84% of technology leaders to abandon initiatives. For fintech professionals, this highlights a critical disconnect between AI ambitions and the underlying technical debt that threatens security, scalability, and long-term return on investment.

What was announced

GFT Technologies released findings from a comprehensive AI study conducted by Wakefield Research, surveying 945 CIOs and CTOs across 19 countries. The research, which focused on companies with at least $500 million in annual revenue, was fielded between August 11 and August 31, 2026. The data indicates a significant "implementation gap" where the speed of AI adoption is outstripping the capacity of existing technical foundations. Key metrics from the report show that 84% of respondents have been forced to cancel an AI pilot or project specifically because of limitations in legacy systems. Furthermore, 93% of technology leaders believe that failing to modernize infrastructure before deploying AI will eventually trigger an enterprise-wide security crisis.

This technical friction is compounded by financial skepticism; 89% of those surveyed expressed concern that global AI investment is growing faster than the realistic business value it can deliver. The study also highlights geopolitical and internal pressures. Approximately 99% of leaders believe government restrictions on AI access make it essential to avoid dependency on a single provider. Internally, 91% of respondents suspect that some public companies are using AI as a justification for workforce changes intended primarily to inflate share prices. This environment has increased personal risk for executives, with 89% worried that a wrong workforce decision during AI scaling could put their own job at risk, while only 20% believe their organization's other C-suite executives and board members fully understand the security risks of running AI on legacy systems.

"AI adoption is moving quickly, but our research shows that enterprises are increasingly recognizing the importance of the foundation underneath it. For many organizations, legacy infrastructure is becoming a real constraint—not only on innovation, but also on security and scalability. Closing that gap between AI ambition and infrastructure readiness is critical to turning AI investment into sustainable business value."

Marco Santos, Global CEO at GFT Technologies.

The companies involved

GFT Technologies is an AI-centric global digital transformation company operating on a worldwide scale. The firm positions itself as a partner for enterprises looking to navigate complex technological shifts, particularly in the realm of artificial intelligence and infrastructure modernization. As a global player, GFT focuses on bridging the gap between high-level digital ambition and the practicalities of implementation, governance, and sustainable scaling. The company’s focus on "ground-up" investment suggests a market position that prioritizes the structural integrity of IT environments over superficial software layers.

The study was executed in partnership with Wakefield Research, a professional research firm that specializes in quantitative and qualitative data collection for global brands. By targeting CIOs and CTOs at large-scale organizations—specifically those generating half a billion dollars or more in annual revenue—the collaboration aimed to capture the sentiment of decision-makers who manage the highest stakes in the current AI transition. GFT’s role in the market involves addressing the exact "legacy constraints" identified in the report, providing the services necessary to update outdated environments so that they can support modern, data-intensive AI applications without compromising security or operational stability.

What this means

This report signals a necessary reality check for the fintech sector, where the rush to integrate generative AI has often ignored the structural rot of decades-old core systems. The finding that nearly all tech leaders are now prioritizing multi-provider strategies suggests a move away from the "all-in" cloud partnerships of the last decade, driven by a fear of geopolitical volatility and vendor lock-in. Furthermore, the high level of distrust regarding workforce narratives puts immense pressure on C-suite transparency. The industry is reaching a tipping point where "AI-first" marketing must be replaced by "infrastructure-first" engineering, or risk a wave of high-profile security failures and abandoned investments.