OpenAI
November 5, 2026
Franklin Templeton uses OpenAI to support investment research
Starting with equity research, Franklin Templeton is developing AI workflows to help portfolio managers compare views and examine risks.
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Company size: Enterprise
Region: North America
Industry: Finance
Products: Codex
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Franklin Templeton wants AI to help portfolio managers examine different research views and the risks behind an investment idea. Codex is one of several tools our investment teams are using to develop workflows for investment research.
“The biggest unlock from using OpenAI’s tools is the ability to merge continuous intelligence with human judgment. It has really transitioned because, beforehand, AI was automating our human-led process. Now AI is actually automating the ability to surface intelligent insights, and that intelligence layer plus human judgment is just a fantastic unlock.”
—Katrina Dudley, Senior Vice President, Public Market Investments, Franklin Templeton
When Franklin Templeton first tried using AI, the team put data in a database and connected the models to it. But it didn’t produce the answers the teams needed because the models didn’t understand how the data fit together. When the team added agents and a semantic layer, a structured model of what the firm’s data means and how it’s connected, the results changed. The team is using Codex and other tools to develop this connected intelligence layer. "We've been able to build what we think of as a connected intelligence layer," Dudley says. "We're bringing the data into the tools, and we're surfacing insights that make a difference."
Research, risk, compliance, and trading offer different perspectives on an investment. Franklin Templeton’s ambition is to bring those inputs together for portfolio managers. “We're able to bring that all in and then use that to surface insights to the people who are making decisions, which are our portfolio managers,” Dudley says.
Dudley describes the earlier equity-research workflow as human-led and sequential: an analyst performs first-pass stock analysis, reviews earnings calls, and studies competitors in each business line. The goal is to surface useful information as analysts prepare new ideas to be pitched to portfolio managers or provide updates on existing positions in the portfolio. As she puts it, “It's just continuous intelligence combined with that human judgment.”
In the workflow Franklin Templeton envisions, its investment teams will have access to a governed, reusable intelligence foundation that brings together trusted connectors, portfolio and workflow context, and agentic capabilities that surface actionable insights for its analysts and portfolio managers.
Franklin Templeton has used Codex in hackathons, bringing experts alongside investment practitioners as they develop their own tools. Its Investment AI champions are working to turn experiments into production-ready workflows, with security review, expert support, and data controls as part of that process.
Dudley says, “We have moved from augmenting our research process to reimagining the investment research workflow.”
Some of what makes AI helpful in other settings doesn't work in asset management. Many tools learn a user's preferences and show them more of the same, so if someone favors one research provider, the tool surfaces more of that provider's reports. For an investment team, that narrowing potentially brings a biased perspective into the investment process. Franklin Templeton wants the opposite. "We want to make sure that they're accessing that diversity of research and diversity of opinion," Dudley says.
Franklin Templeton wants its AI systems to emphasize investment risks. “We need AI to understand that a great investment idea is one that is well reasoned, but it also has analyzed the risks and makes our portfolio managers aware of the risk,” Dudley says. “If you’re looking at a research note, focusing on the fact someone has identified the investment risks is not a bad thing from our perspective. It makes for a more informed investment decision.”
Franklin Templeton's experience points to some investment management best practices:
“Our message from leadership is consistent: we encourage innovation and experimentation with AI within clearly defined risk guardrails. Not every initiative will succeed, but each should generate insights that strengthen our capabilities, inform future decisions, and drive continuous improvement,” Dudley says.
Get new tools into people's hands: Dudley says Franklin Templeton has brought practical labs to teams quickly after new technology launches, so they can test how it fits their work.
Help teams learn the tools: Dudley says, "The goal is getting them to actually understand the power of the technology."
Build with appropriate controls: Security review, expert support, and data agreements are part of Franklin Templeton’s path from experimentation toward production-grade tools.
“With OpenAI, our teams feel like they’re at the forefront of technology.”
—Katrina Dudley, Senior Vice President, Public Market Investments, Franklin Templeton
Dudley’s longer-term goal is to make that connected intelligence accessible across investment teams, from analysts to the leaders of each investment group.
She wants analysts to spend more time in the field, speaking with many different experts and professionals, including executives at private companies, and bringing what they learn back to their investment teams. For Dudley, that human perspective remains essential as the tools develop.
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