AI has the potential to transform productivity and growth. To really achieve this potential, however, companies need broad, deep and scaled adoption. At BNY, we are encouraged by what we have already seen AI do and are systematically investing in upskilling our employees and deploying AI throughout the company, all with strong governance in mind. Today, nearly all our employees are trained to use our enterprise AI platform, Eliza, with the majority of our AI builders now coming from outside of our engineering teams. We hear from clients and industry players around the world that they would like to better understand the pathways to AI adoption, so we have summarized our learnings here.
A Platform Approach to AI
Companies looking to harness AI have a wide range of technology options to consider — from off-the-shelf tools to custom-built platforms. While many start with enterprise integrations that embed AI into daily workflows for tasks like summarizing emails and meetings, others are carefully selecting vendor solutions for specific and siloed functionalities. Our AI strategy is straightforward: AI for everyone, everywhere and everything. We made a deliberate choice to build AI as a platform within our company — named “Eliza,” after the wife of BNY founder Alexander Hamilton — that leverages best-in-class models and vendor tools from a variety of leading providers. A menu of models is provided to our builders — any BNY employee — to power different solutions. Key considerations for our technology strategy include:
- Strategic Value and Differentiation: Eliza is a core asset, purpose-built in line with our data, risk, legal and compliance standards. It harnesses our expertise and unique data to generate actionable intelligence and deliver greater value to clients.
- Flexibility: Eliza enables us to continuously integrate best-in-class models as they become available and as our AI needs evolve.
- Efficiency: By deploying a single platform across our company, we eliminate redundant investments in similar tools and are helping cross-share tools, best practices and solutions to drive scale.
Democratizing AI – A Culture of Learning
Empowering our Employees
Technology alone does not drive transformation — people do, so while the investments we’ve made have been focused on creating the technology foundation to go faster, adoption and success will also be dependent on culture. Today, people from every discipline can use AI — and that prompts us to redefine what “AI expert” means. We still need data scientists and engineers to create models and build AI systems, but a fast-growing community is becoming expert at applying AI within their own lines of work. With AI, our people can do so much more, but first they need to learn AI so that AI can start to work for them. At BNY, we give our employees a variety of ways to upskill themselves: leader-led, peer-to-peer, team-based and self-directed learning. AI can make BNY a better, faster, more vibrant company. And AI, in our view, can create an even greater opportunity for our employees to thrive.
BNY recently announced an initiative with Carnegie Mellon University to support world-class research and development in AI, known as the BNY AI Lab. The BNY AI Lab brings students, faculty and staff from across the University together with BNY experts to advance the state-of-the-art in AI applications and systems and prepare the next generation of leaders.
Building AI Muscle
When BNY began its AI journey, we first focused on raising awareness and familiarity. We promoted Eliza and its capabilities: we hosted internal events, demos and teach-ins geared toward helping our people understand what AI is, how we built Eliza and how they could use it. We also developed trainings and self-directed learning opportunities to expand awareness-building. Colleagues brought each other along for the journey, based on the idea that sharing experiences is integral to adoption. For this reason, we set up peer learning circles and social networking. Our leaders led by example, championing AI efforts and cascading the importance of AI to their teams through initiatives such as leadership briefings, AI-focused townhalls and internal thought leadership content. Seeing our leadership team talk openly about AI in the media also drove our employees’ curiosity in our Eliza platform.
We then gave our employees a variety of fun and collaborative opportunities to work with each other to explore how AI could add value to their specific roles or teams. AI hackathons and bootcamps are happening across the company. Eliza adoption is up 175% this year, with 99% of employees fully trained and onboarded onto the platform — up from just over a third in January.
SCALING AI ENABLEMENT THROUGH ACCESS, SKILL-BUILDING AND COMMUNITY
Click through to see the six attributes of BNY's AI-first culture.
AI ACCESS
State-of-the-art capabilities
Objective: Secure, unified AI access so teams can integrate it in everyday work
How: Single enterprise AI platform with secure chat, search, coding and agents
E-LEARNING
Curated and self-guided
Objective: Firmwide AI fluency and role-specific depth with responsible AI by design
How: Role-based AI learning paths with certifications and a responsible AI curriculum
BOOTCAMPS
In-depth, tailored programs
Objective: Convert priority use cases into deployable MVPs while upskilling cross-functional teams
How: Problem-driven bootcamps
HANDS-ON LEARNING
Practical experience
Objective: Industrialize delivery of agents and AI initiatives from prototype to production
How: Ability to prototype, test, and deploy AI agents with guardrails, telemetry and approvals
GAMIFIED LEARNING
Hackathons, promptathons
Objective: Make AI a daily habit and utilize the best ideas
How: Hackathons, promptathons and weekly demos with leaderboards
COMMUNITY
Likeminded practitioners
Objective: Sustain adoption through peer coaching and shared standards
How: Build a network of AI champions and pioneers to promote adoption
Driving Engagement and Application
Now that every part of the company has access to Eliza, our focus has shifted to driving engagement and application and encouraging our people to build their own Eliza agents. Expansive upskilling is essential to unlocking AI’s value at scale, so we are expanding the tools developed to raise awareness, with a focus on deepening employees’ AI skillsets and confidence. We are leaning into role-based skills for AI proficiency levels across engineering, operations, product management, client coverage and corporate functions, with upskilling programs tailored to these role-based personas. All personas are provided training around fundamentals, and advanced learnings are provided to engineers. We also have tenure-based programming, such as analyst bootcamps focused on our early-career employees, and an AI leadership series aimed at helping managers build a culture of experimentation.
Our employees — engineers and non-engineers — are creating Eliza agents and beginning to use them regularly. By embedding AI into workflows and empowering employees to build and apply their own solutions, we believe companies can accelerate adoption, deepen impact and create a workforce that is AI-empowered and AI-confident.
Delivering Tangible Value with AI
The next phase of establishing an AI culture involves supercharging our AI application through individual agents, AI solutions and digital employees. As of the end of the third quarter, we have 75% more AI solutions in production compared to the prior quarter — including solutions that help identify new business leads, write code, automate payment processing, accelerate client onboarding and increase automation of reconciliations.
1. We leverage AI-based solutions to improve quality and agility. For instance, AI allows us to continuously monitor transactions and market conditions — detecting risk signals in even more real-time and equipping our teams with the insights to proactively mitigate issues. Digital employees are part of our payment teams, working side by side with our people, so that clients can benefit from even faster processing. AI is helping us accelerate client onboarding by shortening research and processing times. By harnessing advanced reasoning, BNY’s AI-driven Contract Review Assistant benchmarks negotiated agreements against our corporate best practices and evolving regulatory requirements.
2. AI is helping us better understand and anticipate client needs. AI-enabled synthetic focus groups and data analysis allow us to quickly identify patterns and themes, which then inform how we design our products.
3. We have built, onboarded and deployed over 100 digital employees with distinct personas, credentials and supervisors to automate routine tasks. By putting AI in the hands of everyone at BNY, we intend to develop fluency and create capacity for our people to focus on higher-value work.
Applying Governance to Scale
Having the right governance frameworks not only helps deploy AI in a responsible, risk-managed way; it is essential for building scalable solutions. At BNY, our enterprise-wide Responsible AI approach is anchored in governance frameworks around data usage, transparency, fairness, compliance, employee training and technical guardrails, along with continuous oversight.
Good governance is never static. We are constantly evolving our approach to increase effectiveness and scale sustainably, such that it powers responsible innovation and the AI for everyone, everywhere and everything philosophy.
Final Thoughts
We are just getting started.
Michael Demissie, Michelle O'Reilly, Jordan Romanoff, Saed Shonnar and Jess Stern contributed to this article.
