Banking executives across the globe rank artificial intelligence (AI) as one of the most game-changing opportunities of our time, according to a recent report.
AI is transforming the banking industry by driving personalized, 24/7 customer service through intelligent chatbots and virtual assistants, enabling banks to meet customer needs with unprecedented accuracy and immediacy. In fraud detection, AI allows banks to move beyond basic alerts and delve into predictive behavior modeling, proactively identifying and preventing fraud before it even happens. On the operational side, AI-driven automation does more than just handle routine tasks; it fine-tunes complex processes like loan underwriting, credit scoring, and staying on top of regulatory compliance. AI is also being leveraged for risk management, helping banks forecast market trends and assess credit risks with remarkable precision.
But, as with any powerful tool, these advances bring their own set of risks that we must carefully navigate. The same technology that empowers personalized services and advanced fraud detection can, if not properly managed, expose banks to new vulnerabilities, including data breaches, algorithmic biases, and regulatory challenges.
This article highlights the risks and challenges associated with advanced AI and explores how community banks can address these issues to successfully integrate AI and future-proof their operations.
Risks and Challenges to the Bank Customer Experience
Loss of Personal Touch 
Despite its ability to communicate, AI is robotic and thus lacks empathy. Recent advancements in natural language processing and sentiment analysis have allowed AI to mimic empathetic communication to some extent, but AI still significantly trails behind the human warmth customers seek when reaching out for assistance.
Ultimately, AI works best when it’s supported with the human-in-the-loop (HIL) element, where humans are involved in both the testing and training stages of building AI algorithms. This kind of collaborative relationship fine-tunes AI accuracy, reduces bias, and increases system efficiency.
Customer Trust and AI
According to a 2023 report produced by the Federal Trust Commission (FTC), one of the biggest problems of AI is its trust factor. AI trained on distorted information tends to produce unreliable results. Generative AI “hallucinates”, providing false or misleading information more often than most users realize. AI may also not be trained on the most recent information available.
These issues are challenging to resolve, but the most reliable way to bridge the trust gap is through comprehensive training and actively involving humans in the management of AI tools.
Data Privacy and Security
Today’s advanced AI systems require large amounts of customer data for effective insights, which increases the risk of data leakage, as evidenced by the 2023 case where ChatGPT leaked one user’s conversations to another user.
Although there are stringent data protection regulations and legal mandates, there’s no federal law to protect members of community banks from harm, leaving institutions with the potential fallout of data breaches. Community banks can hedge risks by being transparent about how they use data, improving their data security measures and regularly updating their AI systems to prevent potential data breaches.
Risks and Challenges to the Bank
Operational Integration
Implementing AI solutions at community banks demands robust controls and human oversight. Organizations must ensure that future AI tools integrate seamlessly with existing systems and processes, avoiding technological silos. As Digital Strategist Eric Cook suggests, leaders can motivate employees by launching reputable, company-wide AI training that highlights how AI can significantly streamline their work, relieving them of routine tasks and empowering them to focus on delivering exceptional service to customers.
Cybersecurity and AI 
As technology becomes more advanced, it also becomes more vulnerable to breaches. The remarkable sophistication of modern AI has, unfortunately, made it a powerful tool for bad actors. This misuse includes cyberattacks, spreading misinformation, manipulating markets, and using deep fakes to undermine trust in financial institutions. The best methods to protect community banks’ systems are implementing multi-factor authentication (MFA) and robust encryption measures, and deploying firewalls, antivirus, and anti-malware software. Community banks are also advised to continuously stay updated on the ever-expanding threat landscape.
Regulatory and Compliance Risks
Lack of clear regulatory direction complicates bank oversight efforts, making it difficult for management to keep up with an evolving field. Current governance models include data privacy rules such as the General Data Protection Regulation (GDPR) and the more recent Artificial Intelligence Act (by the European Commission) which stipulates when AI can and cannot be used. But AI regulations are poorly understood, as AI risks continue to grow.
According to a best-practice EY report, community banks could benefit by actively engaging with regulators in industry initiatives. This proactive approach helps establish AI adoption standards within the industry.
Financial and ROI Considerations 
AI poses risks for community banks when assessing the true costs, potential savings, and long-term financial impact of adoption. While AI promises efficiencies, accurate cost estimation is challenging due to initial investments in technology, infrastructure, and training.
Assessing ROI requires careful analysis of these factors alongside potential regulatory changes. Successfully navigating these complexities requires thorough planning, continuous evaluation, and agile adaptation to ensure AI adoption aligns with strategic financial goals.
Ethical Implications of AI
The use of AI in banking raises ethical concerns, such as bias in decision making and discrimination. If AI is trained on distorted data, output can result in discriminatory lending practices, unfair insurance rates, and exclusion from financial services. This can damage customers’ trust in their bank and erode the mission of the community bank.
For financial institutions that want to harness the transformative power of AI without its risks, the key lies in prioritizing ethical considerations, proactively managing AI risks, and adopting robust data governance and security measures
Risk of Doing Nothing
While certain regulators warn that AI may produce more harm than good, consistent studies show that community banks that don’t embrace AI risk being left behind.
In a 2024 article on Ally Financial’s successful use of AI in marketing, Sathish Muthukrishnan, Ally’s chief information, data, and digital officer, suggests that management appreciate AI for its inherent potential and realize that for this to be maximized it needs human collaboration.
Unlock the Power of AI with Strategic Guidance
For bank executives looking to integrate AI into their business, it is essential to understand its potential impact and risks and develop the strategies necessary to incorporate it into your bank operations. Hartman’s IT and industry experts are uniquely positioned to assist you on your AI journey. Contact us to learn more about our AI services. We will help you evaluate your organization’s current capabilities, identify areas where AI can make the most impact, and develop an AI roadmap.
