When generative AI exploded in popularity around April 2023 — primarily through conversational AI tools like ChatGPT — it introduced a new level of efficiency for banks and other financial institutions. In fact, McKinsey estimates that the banking industry could unlock between $200 billion and $340 billion in value with these tools. However, with this added productivity comes new potential risks, and while most banking leaders are on board, adopting and deploying these tools takes time. 

But with 2023 coming to a close, many organizations have had a year to discuss their AI development, and they’re looking forward to a year of action. So, what can banks expect from AI solutions in the future?

In this blog, we’ll take a deep dive into the latest AI trends set to shape the new year.

Top 5 Banking Artificial Intelligence Trends to Watch in 2024

It’s safe to say that 2024 is shaping up to be another transformative year in the artificial intelligence space, especially for banks and other financial institutions. From the rapid pace of innovation to the potential AI regulation in the field, navigating this complex landscape will require staying up-to-date on the key emerging trends and developments that are shaping the use of AI in the banking sector.

To help, we’ve compiled a list of the top 5 biggest banking AI trends for 2024 and what they mean for your institution:

1. From AI Talk to Tool Deployment

While 2023 was the year of generative AI, with many organizations looking into how to use these tools to automate processes like customer service calls, not every bank deployed an AI system immediately. According to an American Banker survey, almost half of all bank executives cited skill gaps as the top challenge they faced, while 99% reported they were actively hiring talent to support these initiatives. As these organizations fill these vital positions moving into 2024, we’ll likely see talk about AI technology turn into actual action as more banks secure the skilled talent they need to support adoption efforts.

2. Leveraging Data for Personalization

As more AI solutions are deployed, they’ll continue to collect data on customers, from past interactions to engagement across digital channels; and with natural language processing, these tools will be able to build on historical knowledge and context to better personalize each interaction. Whether it’s providing tailored financial advice, optimizing product or service offerings, or delivering highly relevant content recommendations, new AI and machine learning technologies will be able to scale personalization efforts while maximizing engagement. Of course, these applications will also open up discussions around data privacy, ethical AI and cybersecurity, but fortunately, many great minds are already working on solutions.

3. Integrating AI for Cybersecurity

As the cybersecurity landscape becomes increasingly sophisticated and malicious actors find new, complicated exploits, banks will need a way to safeguard their data and ensure their solutions don’t open new vulnerabilities. According to Goldman Sachs, some cybersecurity companies are adopting generative AI technology to automate time-sensitive, repetitive tasks like threat identification. Meanwhile, banks are already leveraging deep learning models to detect and prevent fraudulent activities in real-time. By leveraging large language models and vast amounts of data, they can train AI tools to distinguish between internal and external normal and anomalous activities, bolstering the bank’s overall security.

4. New Applications in Natural Language Processing

Natural language processing (NLP) is a field of computer technology that, combined with machine learning, enables conversational AI solutions to “understand” text and speech prompts. While machine learning was first introduced to NLP in the '80s, the field continues to innovate rapidly with applications such as chatbots and digital assistants thanks to modern computing. In 2024, NLP applications will no doubt continue to evolve as banks and AI companies expand their use to include broader analytics capabilities, from customer sentiment assessments to fraud detection, compliance, and more. While NLP will continue improving conversational generative AI applications, it will also become a critical component for breaking down and interpreting vast volumes of data.

5. 24/7 Customer Support Systems

The “AI revolution” will continue to dominate the conversation around customer service in the new year. While this year saw many banks move toward adopting an internal AI assistant to help agents streamline their workflows, 2024 will see a rise in customer-facing solutions as more teams become comfortable with their existing tools and set their sights on expanding their capabilities. For instance, Gartner expects to see a roughly 24% increase in call center investments in the next year — all thanks to conversational AI tools. The result? Delivering top-notch, 24/7 support with an AI chatbot will become the norm, setting the standard for a convenient customer experience. 

Navigating the Future of AI in Banking

While 2023 told the story of AI’s rapid rise in popularity, 2024 is set to shape how we use these solutions in the workplace. For the banking industry, this will mean managing countless shifts and emerging trends — all while staying competitive in the present and the future.

As AI becomes an integral part of banking, Posh stands ready to help our partners take charge of their journey. With innovative AI solutions at the forefront and responsible decision-making and security at the foundation of everything we do, we’re here to redefine the banking experience for employees and customers.

Ready to see what AI can do for your institution? Request a demo today.