Key Takeaways
- Banks are increasingly using artificial intelligence (AI) to cut costs and improve customer service, with significant savings in call center operations.
- AI-handled calls can cost as little as $0.25 per interaction, compared to $9 for human-handled interactions.
- Conversational and generative AI can lower operational costs when deployed thoughtfully, and are being used by banks such as KakaoBank and Lloyds to modernize their customer service.
- AI is being used to automate tasks across various functions, from customer support to internal operations, and can help banks reduce costs and improve efficiency.
- Personalization is a key driver of customer engagement, with 72% of bank customers saying it influences their choice of bank.
Introduction to AI in Banking
Banks are increasingly turning to artificial intelligence to cut costs and improve customer service, with savings showing up most clearly in call center operations. As KeyCorp CEO Christopher Gorman noted during the company’s fourth-quarter 2025 earnings call, "AI is already delivering per-interaction cost advantages." AI-handled calls cost roughly $0.25 each, compared to $9 for human-handled interactions. This significant cost savings is driving banks to invest more in AI technology, with KeyBank increasing its tech spend from $800 million to $900 million in prior years to about $1 billion in technology and operations investment.
Conversational AI in Banking
Conversational and generative AI can lower operational costs when deployed thoughtfully. Traditional call centers, long plagued by inefficient interactive voice response menus and staff bottlenecks, are being modernized with AI that can interpret customer intent and route or resolve inquiries faster than legacy systems could. As Gorman said, "while it’s early to quantify broad AI-driven efficiencies, the bank has found roughly $100 million in annual savings through continuous improvement efforts, which will help fund ongoing digital transformation." International banks such as KakaoBank and Lloyds are also using conversational AI to modernize their customer service. KakaoBank has deployed conversational AI built on Microsoft Azure OpenAI to serve as a primary interface for customer inquiries, allowing customers to interact naturally about account activity, transactions, and financial services inside the bank’s mobile app.
Scaling Conversational AI
KakaoBank’s approach reflects a digital-native strategy where AI is embedded directly into the core customer experience rather than layered on top as a support tool. By resolving routine questions conversationally, the bank reduces service costs while keeping customers inside its digital ecosystem, where engagement tends to be higher and servicing costs lower. In the United Kingdom, Lloyds Bank has taken a different but complementary path with its generative AI platform called Athena. Lloyds is using the tool to assist customers and employees, automating responses to common queries and helping staff access information more quickly. As the bank noted, "Athena is positioned to improve service quality and productivity while easing pressure on contact centers." Rather than replacing human agents, Lloyds has emphasized AI as an augmentation layer that speeds resolution and reduces manual effort.
Agentic AI and Workflow Automation
Beyond frontline customer service, banks are deploying more advanced agentic AI systems that perform tasks across varied functions, from customer support to internal operations. Wells Fargo, for example, has expanded its partnership with Google Cloud to deploy AI agents at scale. The tools automate tasks, including balance inquiries and debit card replacements, freeing human staff to focus on higher-value work and strategic customer relationships. As the bank noted, "the initiative also covers internal workflows, such as complex trade inquiries and document review, with AI agents helping employees find insights faster and complete tasks more efficiently, contributing to operational savings and improved agility." These agentic systems go beyond reactive chatbots by synthesizing information across internal data sources and offering 24/7 personalized interactions, a capability that has the potential to reduce overall cost structures and time to resolution for many service functions.
The Future of AI in Banking
While call center AI delivers immediate operational savings, banks are expanding the scope of these technologies to enhance customer engagement and retention. As the PYMNTS Intelligence report "Beyond the Bot: Why Embedded Conversational AI Is Banking’s Next Strategic Advantage" found, "72% of bank customers say personalization influences where they choose to bank, and conversational AI is now being positioned as more than a cost-saving tool. It’s a value generator that deepens engagement and captures valuable insights." As banks continue to invest in AI technology, it is likely that we will see even more innovative applications of AI in the banking industry, from personalized financial coaching to automated internal workflows. As Gorman noted, "AI is already delivering per-interaction cost advantages," and it is likely that this trend will continue in the future.
