Adopting emerging technologies, especially artificial intelligence (AI), has become essential for driving growth in today’s competitive banking industry. In fact, sectors that have embraced AI are seeing productivity boosts nearly five times greater than those that have not. However, in highly regulated industries like banking, the transformative potential of AI often collides with concerns over compliance, bias, and security.

This hesitation can result in missed opportunities. The key to fully unlocking AI’s value lies in combining the technology with existing human expertise. By doing so, banks can navigate regulatory challenges, reduce risks, and foster innovation.

AI’s Journey from Administrative Tasks to Customer Experience

Generative AI has gained significant attention in recent years, prompting senior leaders to take a closer look at its potential for their businesses. While AI may be commonly associated with chatbots that people use daily, many enterprise applications of AI have been around for quite some time. The banking sector, for example, has been using traditional AI for years to manage tasks such as data classification and process automation.

Generative AI builds on existing machine learning (ML) techniques, adding the ability to produce creative, novel outputs. Many traditional AI tools focus on supporting the backend of an organization, reducing the administrative workload for employees so they can focus more on creative tasks.

As generative AI continues to develop, it’s expected to play a more customer-facing role. Some potential uses include enhancing fraud detection systems for real-time and cross-border payments or automating loan decisions to help serve underrepresented populations.

Generative AI-powered predictive analytics can also assist banks in managing risks and preventing fraud. By analyzing transaction patterns, AI systems can spot fraudulent activities much faster and more accurately than traditional methods. This not only helps protect customers but also saves banks valuable resources that would otherwise be spent investigating false positives. The success of these AI applications will depend on balancing the efficiency of machines with the indispensable human touch.

Merging Human Expertise and AI to Drive Innovation

AI has the potential to fuel significant growth, especially in banking, where it could increase annual revenue by $200 billion to $340 billion. Yet, only 12% of companies have developed their AI capabilities to the point where they can effectively drive growth and transform their operations. Achieving AI maturity requires a comprehensive deployment strategy, including a solid data plan, the right technology infrastructure, and, most importantly, a strategy for engaging the workforce.

Introducing new technology requires substantial education and awareness. Leaders can’t assume that their staff will naturally have the skills needed to use these new tools; only about 14% of UK workers have used generative AI in their professional roles.

For AI to be fully effective, organizations need to focus not only on installing new systems but also on building a workforce capable of using these tools to their advantage. Employees should have access to thorough training programs tailored to different roles and skill levels. Beyond initial training, it’s crucial for businesses to foster a culture that encourages continuous learning and experimentation with generative AI tools.

Given the highly regulated nature of banking, addressing the regulatory challenges of generative AI deployment is also critical. Data privacy and security are especially important since AI systems often rely on large amounts of data. Banks must ensure they collect, store, and use this data in compliance with regulations like GDPR and CCPA. Establishing strong data governance practices and leveraging privacy-enhancing technologies can help meet these needs while still enabling AI’s effective use.

By adopting a proactive, people-focused approach to AI, banks can ensure their workforce is prepared to use these tools to increase productivity, foster creativity, and spark innovation. Addressing regulatory concerns while empowering employees will help maintain trust with both customers and regulators, ensuring that AI supports rather than replaces the creative problem-solving abilities of staff.

Driving Industry Change Through Platform-Driven Transformation

AI has the potential to reshape industries when applied to the right use cases by skilled professionals. The tech sector has already embraced AI enthusiastically, particularly generative AI. For banking to follow suit, organizations will need to adopt a platform-driven strategy.

Banking-as-a-service (BaaS) models are gaining popularity, with services like Buy Now, Pay Later (BNPL) growing rapidly. BNPL allows consumers to pay for products over time, making it an increasingly common alternative payment method.

BaaS enables non-banking companies to offer financial products through API-driven platforms, integrating banking capabilities into their services. Thanks to BaaS, the finance sector has seen platforms that consolidate financial products from various institutions into a single, accessible space, simplifying money management for both businesses and consumers.

The combination of AI and BaaS represents a major opportunity for financial services. AI can be seamlessly integrated into BaaS platforms to enhance risk assessment models and personalize financial products. For instance, AI could help personalize BNPL services or detect fraud in real-time. By merging these technologies, organizations can create a more inclusive financial ecosystem.

Looking ahead, it’s clear that AI will play an increasingly pivotal role in banking. For its full potential to be realized, leaders must ensure that their teams are prepared to embrace these changes. The key to success is not replacing human expertise with AI, but encouraging employees to use AI to amplify their creativity and problem-solving skills. While AI can process massive amounts of data and uncover patterns humans might miss, it’s the human touch that provides the context, empathy, and ethical judgment that AI alone cannot offer. By combining AI with a platform-driven approach, financial institutions will be well-positioned to innovate and create lasting value for both customers and internal teams.