Business Director, AI Strategy & Transformation – Enterprise Risk Management

Capital One•McLean, VA

1d•$230,400 - $263,000

About The Position

The Director of AI Strategy & Transformation for Enterprise Risk Management is a strategic leadership role focused on modernizing enterprise risk management through technology and data-driven insights. This leader will set the long-term vision and strategy for integrating Artificial Intelligence, Machine Learning, advanced language models, and transformational data analytics into ERM processes. This role will lead two complementary teams: an AI Strategy team and a specialized Data & Analytics Transformation team. Distinct from our established ERM Data, Analytics, and Reporting function, this specialized Data & Analytics team will be solely dedicated to transforming how we conduct risk management. The Director will guide this team to test hypotheses, identify opportunities to adjust our methodologies, and build data-driven business cases for our destination state. Acting as a bridge between risk professionals, product, and technology teams, this role will synergize these efforts—using D&A to uncover opportunities and build the case for change, and using the AI team to automate those modernized processes to increase the efficiency and effectiveness of the risk function. The ideal candidate will balance a multi-year vision with the delivery of immediate, practical quick wins.

Requirements

Practical experience identifying, scoping, and launching AI projects, with a solid understanding of how to use models like Gemini or Claude safely within a secure corporate environment.
Strong understanding of modern data setups, including how AI models search internal documents, connect to existing databases, and automate workflows.
Proven ability to work across departments, serving as the bridge between product, technology, data and risk and compliance professionals.
A practical, results-oriented mindset with the ability to take an idea from a simple test case all the way to a functioning tool used by the team.
Strong communication skills, with the ability to clearly explain the benefits and limitations of AI technologies to senior leaders.
Bachelor’s Degree
At least 4 years of experience performing quantitative analysis
At least 4 years of experience performing qualitative analysis
At least 2 years of experience performing people management
At least 2 years of experience performing project management

Nice To Haves

Master’s Degree
2+ years of experience in financial services
1+ year of experience in consulting
3+ years of experience in Enterprise Risk Management, Operational Risk, or Technology Management, with a track record of successfully delivering technology modernization projects

Responsibilities

Lead and develop a specialized Data & Analytics team focused exclusively on transformational initiatives, operating distinctly from the existing Business As Usual (BAU) data team.
Direct hypothesis-driven data exploration to identify where and how risk management programs, processes, and methodologies should evolve to drive value, time savings, and enhanced risk oversight.
Foster a complementary ecosystem between D&A and AI: leverage the D&A team to identify bottlenecks and build the business case for process changes, while deploying the AI team to automate and optimize those modernized processes via machine learning.
Use data to continuously measure the impact of transformational changes, define the "destination state" of our risk capabilities, and guide the strategic roadmap.
Formulate a multi-year AI vision and strategy for ERM that sets a clear long-term direction for modernizing enterprise risk management while remaining aligned with the overall enterprise strategy.
Design a balanced implementation roadmap that delivers immediate quick wins, such as automating highly manual tasks and processes to prove value early while simultaneously building toward long-term, foundational AI capabilities.
Establish a clear prioritization framework to evaluate potential AI use cases based on their complexity, speed to implementation, and long-term impact on effectiveness and efficiency.
Secure executive alignment through clear business cases that balance improving operational efficiency with the strategic value of long-term risk reduction.
Define the data, technology, and change-management plans required to sustainably support AI tools over time, ensuring the team transitions smoothly from legacy processes to AI-assisted workflows.
Identify and prioritize high-impact opportunities to use AI, Machine Learning, and Large Language Models to improve the speed, accuracy, and efficiency of enterprise risk management processes.
Partner directly with Product, Tech, and Data teams to build, test, and deploy custom internal AI tools specifically tailored for risk managers and compliance officers.
Review successful AI projects and tools used in other parts of the company (such as first line risk offices) and adapt those proven technologies for use within the ERM framework.
Use advanced models like Gemini and Claude in day-to-day risk management workflows to automate highly manual tasks in execution of enterprise risk processes.
Build automated workflows that use AI to parse and analyze large volumes of unstructured data.
Layer AI capabilities on top of existing risk management systems to extract better insights, flag operational anomalies, and reduce manual data entry for the team.
Lead the practical training and upskilling of the ERM team, ensuring risk professionals know how to effectively use, prompt, and validate the outputs of new AI tools.
Define and track clear metrics to measure the success of AI adoption, focusing on time saved, reduced manual errors, and earlier detection of risks.