The promise of artificial intelligence (AI) is best achieved at scale.
That’s why it should be no surprise that JPMorgan Chase, the largest bank in the U.S. as well as the biggest bank in the world by market capitalization, is so keen on the technology’s ability to provide value.
While many of the most promising, and safest, applications of AI are internal facing (think: realizing operational efficiencies and streamlining back office processes), the bank’s latest AI intentions, per a recent patent filing, appear to be pivoting to the customer-facing side.
The financial firm is reportedly in the process of developing a novel AI system that determines “dissatisfaction data” in real time during customer service interactions using machine learning (ML) capabilities.
And JPMorgan isn’t alone — developing smarter, more reactive and dynamic customer service-focused chatbots is emerging as a crucial answer to the question of what AI’s right-now utility could look like for larger enterprises.
After all, the ability to access and leverage best-in-class data is increasingly a key determinator of business success and competitive advantage in the 21st century, and bigger firms are sitting on untold troves of content they can leverage to train large language models (LLMs) and other emergent tools.
PYMNTS’ 2023 study “How Consumers Want to Live In the Voice Economy” found that more than 6 in 10 U.S. consumers (61%) say that voice assistants will become as smart and reliable as human assistants, with just under half (46%) believing this will happen within five years.
While AI chatbots have long been deployed in customer service scenarios, historically the bots often end up frustrating customers by failing to appropriately engage with their queries — leading to upset customers requesting to speak to a human either way.
The latest wave of AI innovations promises to transform chatbot capabilities from single-point engagements to more dynamic and effective platforms for communication and support, while alleviating the need to keep call centers staffed 24/7.
“This didn’t happen overnight,” Amir Wain, CEO and Chairman at i2c, told PYMNTS earlier this month about the commercialization of AI. “There’s been a lot of work going on in AI, and now the product is at a stage where it can be deployed commercially across various applications.”
By tapping future-fit AI solutions, including natural language processing (NLP) tools, Wain explained that his own firm, i2c, is now able to process millions of calls and identify key problem areas in real time, rather than having to parse through an immense amount of data manually.
And AI has integrated itself into customer service far beyond just evolving the average chatbot. Companies are now using it to determine how long to leave customers on hold, as well as to understand and act against a host of other behavioral clues.
“There is a lot of opportunity to build new user-facing products, or those that better delight users in an existing experience, using AI,” Emily Glassberg Sands, head of information and data science at Stripe, told PYMNTS in March.
Read more: Preparing for A Generative AI World
Currently, a lot of customer-facing innovations leveraging AI use the tech’s generative prediction capabilities for things like bespoke product recommendations, personalized advertising and tighter sales funnels.
PYMNTS has previously covered how applications of generative AI tools can have an impact on reducing organizations’ legacy cost centers by helping them optimize headcount for a more modern operating environment.
While it remains unclear just what exactly JPMorgan’s patent for an AI-driven customer service tool implies, the bank appears to be fully committed to positioning itself as a leader across tomorrow’s AI-driven operational landscape.
Still, a word to the wise — as PYMNTS reported, America’s consumer protection watchdog says it’s monitoring the banking sector’s use of AI-powered chatbots after receiving a number of complaints from customers frustrated by their interactions with banks’ AI used to answer questions or solve problems.
The Consumer Financial Protection Bureau (CFPB) said its analysis of the issue found that banks run the risk of providing customers with inaccurate information or failing to protect consumer data and privacy, in violation of consumer financial protection laws.