The Rise of AI in Banking and the Critical Role of Data

As banks across Nigeria and the broader African continent increasingly invest in artificial intelligence (AI) to streamline operations and enhance customer experiences, a growing concern has emerged among experts. They warn that these investments may not yield meaningful returns unless they are underpinned by strong and reliable data foundations.

This warning comes as AI technologies gain traction within the financial services sector. Banks are deploying AI solutions for fraud detection, credit scoring, customer service automation, and operational efficiency. However, despite the enthusiasm, many AI initiatives are failing to deliver on their promises.

According to a report published by Oradian, a core banking technology provider, in its white paper titled The Digital-First Bank's Guide to AI in 2026, the success of AI projects hinges largely on the quality and accessibility of the data that powers them. The report highlights that up to 95% of AI projects undertaken by banks fail due to a lack of focus on data infrastructure.

The report further notes that while banks globally are investing billions of dollars in AI development, many institutions still face challenges such as fragmented databases, poor data governance, and inadequate digital core systems. These issues limit the effectiveness of AI applications and hinder their potential to transform banking operations.

Despite these challenges, AI is widely recognized for its potential to revolutionize banking through faster decision-making, improved customer engagement, automated processes, and enhanced risk management. However, experts emphasize that these benefits can only be realized when financial institutions establish a solid digital foundation capable of supporting advanced analytics and machine learning systems.

The white paper predicts that global banking institutions will invest approximately $97 billion in AI infrastructure by 2027 as they seek to leverage emerging technologies to drive innovation and competitiveness. The anticipated benefits include lower operating costs, improved productivity, faster service delivery, and stronger profitability.

Yet, experts caution that heavy spending on AI without corresponding investments in data quality, integration, and governance could result in a costly misallocation of resources. The report states, "Every AI initiative stands on the shoulders of data. The quality and accessibility of data can make or break an AI project."

Analysts argue that the challenge facing many banks is not a lack of enthusiasm for AI adoption but rather weaknesses in execution and foundational infrastructure. They point out that institutions that successfully integrate AI are often those that first modernize their core banking systems, establish robust data management frameworks, and ensure seamless access to accurate customer and operational data.

For Nigeria’s banking industry, this warning arrives at a critical time. As lenders embrace digital transformation strategies to remain competitive in a rapidly evolving financial landscape, the importance of data infrastructure cannot be overstated.

Experts suggest that banks focusing on strengthening their data ecosystems alongside AI investments will be better positioned to unlock sustainable value from emerging technologies and improve long-term profitability.