Edward Jones is All In on Its Real-time AI Strategy


To the company, AI means “advisor intelligence,” and this is at the core of its initiatives to increase the quality of real-time customer conversations.

Edward Jones, with its network of 18,000 financial advisors, is employing artificial intelligence to help these advisors engage in deeper, more meaningful real-time conversations with its customers. The company recognizes it is sitting on mountains of data, much of which can be put into action. And AI is just the way to achieve that.

The company’s effort to convert petabytes upon petabytes of data, reflecting customer information as well as interactions, was explored in a panel discussion at the recent Databricks Data + AI Summit held in San Francisco. To the company, AI means “advisor intelligence,” and this is at the core of its initiatives to increase the quality of real-time customer conversations.

The goal is to “build a human-centered, innovative and responsible approach to harnessing the collective experience that we have,” said Lindsay Turner, principal for data science, analytics, and business intelligence. “That collective knowledge experience with us is really vast. It spans across 18,000 employees that we have today, collectively over 500,000 years of experience, and data and knowledge that we’ve collected from more than 8 million clients.”

The company’s strategy is being built around AI, says Thomas Renfert, director of IT operations, another panelist at the event. His team supports a “copilot” (not to be confused with Microsoft or GitHub Copilot) that supports advisers “having conversations with customers, with information to help them react real-time,” he explained.

See also: Top 10 AI Trends for the FinTech Industry in 2024

Efforts to deliver these capabilities include enhancing enterprise search with AI-generated answers. “We have tons of information that we deliver over what we call ‘JonesLink,'” he said. “There are 67,000 pages out there that we want to put to use for our branches and advisors.” The system also delivers “nudges,” or recommended next-best actions to carry conversations between advisors and customers forward. “When a client is having an interaction with a financial advisor, how can they really have a deeper conversation? Because of that data that we have, we can have those nudges, and be really crisp with those conversations. That’s really powerful for our branches.”

Ultimately, it’s about bringing “the right data at the right time to the right people for the right reasons,” said Paul Woods, the firm’s director of data, also at the panel. AI and analytics technology delivery. Data is only valuable when it delivers insights that result in actions. “An insight without an action is like a lightbulb without a switch,” he said. “The lightbulb always has the potential to illuminate something, but unless you actually connect it with power, nothing’s going to happen. It’s just potential.”

Paradoxically, this can be challenging in a company rich in data. “We’re a 100-year-old company,” Woods said. “We have data silos, we have integration challenges, we have petabytes of data that are trapped in hundreds or thousands of systems, we have petabytes of data in our legacy Hadoop environments, we have hundreds of terabytes of data in Oracle data warehouses that are in the process of coming through our data pipeline. Getting those silos unlocked we had to run through a lot of integration challenges.”

Capturing new data is also a challenge that requires involvement across the entire organization. “Data is the gold and we have a ton of it,” said Renfert. “How are we teaching our branches to make sure they’re capturing it. How do they have conversations and also capture that? Because that data can feed back into our systems. Are branches capturing them the right way?”

It’s important to keep data continuously refreshed, as well, Renfert added. “Knowledge content creation, curation, that’s really most important.”


About Joe McKendrick

Joe McKendrick is RTInsights Industry Editor and industry analyst focusing on artificial intelligence, digital, cloud and Big Data topics. His work also appears in Forbes an Harvard Business Review. Over the last three years, he served as co-chair for the AI Summit in New York, as well as on the organizing committee for IEEE's International Conferences on Edge Computing. (full bio). Follow him on Twitter @joemckendrick.

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