BNY builds “AI for everyone, everywhere” with OpenAI

BNY builds “AI for everyone, everywhere” with OpenAI | OpenAI

December 12, 2025

BNY builds “AI for everyone, everywhere” with OpenAI

With frontier capabilities from OpenAI, BNY enables employees to build AI agents that help deepen client relationships and support every team’s success.

Company size: Enterprise

Region: Global, North America

Industry: Finance

Products: ChatGPT, API

Results

20k

Employees actively building AI agents

Results

75%

Reduction in legal review time

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When ChatGPT launched in late 2022, BNY made a decisive move to embrace generative AI across the enterprise. Rather than limiting experimentation to a few technologists, the firm created a centralized AI Hub, launched an internal AI deployment and education platform called Eliza, and trained its employees on responsible AI use.

“Our mantra is ‘AI for everyone, everywhere, and in everything,’” says Sarthak Pattanaik, Chief Data and AI Officer at BNY. “This technology is too transformative, and we decided to take a platform-based approach for execution.”

That platform now supports over 125 live use cases, with 20,000 employees actively building agents.

From its start, Eliza was designed not just as a tool, but as a system of work, pairing BNY’s governance rigor with leading models—including OpenAI frontier models—to help employees build safely and confidently.

“We’re not building side projects,” Pattanaik says. “We’re changing how the bank works.”

Maintaining trust in a systemically important institution

BNY plays a systemically important role in the global economy, managing, moving, and safeguarding assets, data, and cash across more than 100 markets. As one of the world’s largest financial institutions, with more than $57.8 trillion in assets under custody and/or administration, trust is non-negotiable.

“We are much like the circulatory system of the global financial services ecosystem,” says Pattanaik. “And from that perspective, we must ensure trust is built into everything we do.”

With that level of responsibility, deploying AI couldn’t be an afterthought or a side experiment. BNY needed an approach that balanced innovation with accountability.

> “A lot of folks could have said, you have such a huge responsibility - maybe we’ll wait and see what happens with AI. We believe AI is going to be like the operating system of technology going forward.”

—Sarthak Pattanaik, Chief Data and AI Officer, BNY

Scaling AI safely through governance by design

Key to Eliza’s success is a governance model that supports scale without slowing experimentation. “Some might see AI governance as a barrier, but in our experience, it’s been an enabler,” says Watt Wanapha, Deputy General Counsel and Chief Technology Counsel. “Good governance has allowed us to move much more quickly.”

At BNY, there are several cross-disciplinary groups that meet regularly to review and consider new AI use cases:

• A data use review board, which brings together cross-functional leaders in intellectual property rights, cybersecurity, engineering, data, privacy, third-party relationships, and others.
• An Artificial Intelligence release board, which aligns similar teams plus additional groups to reconsider initiatives before they are deployed into production.
• The Enterprise AI Council, providing senior oversight and policy alignment across the firm.

Insight from the data use review board flows daily to the AI Council, which then evaluates high-impact or novel scenarios. “We had to iterate as we went along,” Wanapha notes. “As our use cases expand, and as the models shift, we have to constantly evaluate AI projects to maintain accuracy.”

What makes BNY’s approach different is how governance is fully integrated into the tooling. Within Eliza, all prompting, agent development, model selection, and sharing happens inside a governed environment.

“Eliza embeds governance at the system level,” Wanapha explains. “It standardizes permissions, security, and oversight across all models and tools, ensuring every workflow meets the same level of protection.”

Empowering every employee through training and community

At BNY, governance isn't just about oversight - it’s how employees engage with AI every day. Eliza enforces responsible use by design. All employees complete mandatory training before they can use it, and that foundation is reinforced with additional trainings, tools, challenges, and community support. The company now has 99% of its workforce trained on Gen AI, with many more advanced enablement opportunities available.

“We introduced a number of different learning solutions to meet people where they are and to bring them along on the journey,” says Michelle O’Reilly, Global Head of Talent.

One standout initiative: Make AI a Habit Month, a daily series of seven-minute trainings designed to build confidence in prompting, agent building, and peer sharing. “From this month, we saw a 46% increase in the number of agents people were building,” notes O’Reilly.

This enablement model has unlocked a broader cultural shift. “People feel empowered to solve problems themselves,” says Pattanaik. “We’re seeing a culture shift in how teams operate.”

That culture shows up in events like bank-wide hackathons, where teams from Legal, Sales, and Engineering build side-by-side. “We had a recent hackathon in Sales,” says Ed Fandrey, Head of Sales and Relationship Management. “There were no IT or tech folks present, but everyone felt like a developer.”

Unlocking firmwide impact from early use case learnings

The first wave of agents built in Eliza, in collaboration with the AI Hub and different BNY departments, showed how quickly teams could turn ideas into impact:

• Contract Review Assistant: Reduces legal review time by 75%, from four hours to one, across 3,000+ annual vendor agreements each year.
• People Business Partner Agent: Provides fast answers about benefits and policies, cutting manual requests and improving consistency and accuracy.

These early projects sparked a cultural shift. “Before, collaboration meant more meetings,” says O’Reilly. “Today, it means experimenting together, sharing prompts, testing agents, and learning by doing.” That mindset created a flywheel of innovation, with one team’s agent often becoming another’s foundation.

Built for controlled autonomy, Eliza initially allowed only private agent builds. Now, agents created by certain teams and roles can be shared with up to ten…